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Solid Oxide-Based Electrochemical Devices: Advances, Smart Materials and Future Energy Applications
 0128182857, 9780128182857

Table of contents :
Cover
Solid Oxide-Based Electrochemical Devices: Advances, Smart Materials and
Future Energy Applications
Copyright
Contents
List of contributors
1 Tuning perovskite–based oxides for effective electrodes in solid oxide electrochemical cells
1.1 Introduction
1.2 Perovskite oxides: general structural and electronic features
1.2.1 Oxygen anion migration: vacancy formation and vacancy hopping
1.3 Mixed proton–electron conductor for proton-conducting solid oxide fuel cells
1.3.1 Ba-based perovskite oxides: stability versus hydration
1.3.2 Electron conduction and catalytic features at doped BaZrO3
1.4 Toward triple conducting oxides
1.4.1 Enhancing proton conduction in mixed ion-electron conductor materials
1.4.2 Electrocatalysis toward bifunctional oxygen evolution reaction/oxygen reduction reaction catalysts
1.5 Conclusions
References
2 Solid oxide fuel cell’s interconnectors
2.1 Introduction
2.2 Interconnectors
2.3 Metallic interconnectors
2.3.1 Ferritic stainless steels
2.4 Area-specific resistance
2.5 Protective coatings
2.6 Electrodeposition
2.6.1 Potenciodynamic and potentiostatic electrodeposition
2.6.2 Galvanostatic and pulsed current electrodeposition
2.7 Conclusion
Acknowledgment
References
3 In situ photoelectron spectromicroscopy for the investigation of solid oxide–based electrochemical systems
3.1 Introduction
3.2 The soft X-ray scanning photoemission microscope at the ESCA microscopy beamline at Elettra
3.2.1 Operating principle of X-ray photoelectron spectroscopy
3.2.2 Operating principle of SPEM and the experimental setup developed at ESCA microscopy
3.3 Examples of SOFCs SPEM characterization in different configurations and operating conditions
3.3.1 In situ SPEM characterization of the SOFC anodic systems
3.3.2 From in situ SPEM studies on SC-SOFCs to the SPEM characterization of self-driven cells
3.3.2.1 SPEM characterization of a SC-SOFC in a NAP cell
3.4 Conclusion
References
4 Protonic-based ceramics for fuel cells and electrolyzers
4.1 Mechanism of proton conduction
4.1.1 Proton defect formation
4.1.2 Proton transport
4.2 Electrolyte materials
4.2.1 BaCeO3 perovskite-based materials
4.2.2 BaZrO3
4.2.3 BaCeO3–BaZrO3 mixed systems
4.2.4 SrZrO3
4.2.5 Other proton-conductive materials
4.2.5.1 Perovskite-related material
4.2.5.2 Brownmillerite A2B2O5-based materials
4.2.5.3 Phosphates, niobates, and tantalates
4.3 Electrode materials
4.3.1 Fuel electrode material
4.3.1.1 Metals and alloys
4.3.1.2 Ceramic/metal composites
4.3.1.3 Mixed conductive oxides
4.3.2 Air electrode material
4.3.2.1 Mixed O2−/e− conductor
4.3.2.1 Composite ceramic/mixed conductor (O2−/e−)
4.3.2.3 Single-phase mixed triple conducting electrode material
References
5 Multilevel modeling of solid oxide electrolysis
5.1 Introduction
5.2 Theoretical background
5.2.1 Key performance indicators
5.3 Materials and micro-electrochemistry
5.3.1 Kinetic models
5.3.2 Global kinetics
5.3.3 Elementary mass-action kinetics
5.3.4 Equivalent circuit kinetics
5.4 Multidimensional approaches to cell/stack modeling
5.4.1 Zero-dimensional models
5.4.2 One- and two-dimensional models
5.4.3 Three-dimensional models
5.5 Typical operating conditions
5.6 Thermal management of solid oxide electrolyzer stacks
5.7 Thermal management of solid oxide electrolyzer through the use of heat pipes
5.8 System analysis and applications
5.8.1 Operation of solid oxide electrolyzer as a part
5.8.2 Solid oxide electrolyzer integration with thermal and electric sources
Acknowledgment
References
6 Sensors based on solid oxide electrolytes
6.1 Introduction
6.2 Brief history
6.3 Materials for sensors
6.3.1 Electrolytes
6.3.2 Electrodes
6.3.3 Sealants
6.3.3.1 Glassy sealants
6.3.3.2 Glassy-ceramic sealants
6.4 Types of sensors
6.4.1 Potentiometric sensors
6.4.1.1 Equilibrium potentiometric sensors
6.4.1.1.1 Operation principle
6.4.1.1.2 Reference electrodes
6.4.1.1.3 Isotope sensors
6.4.1.1.4 Humidity sensors
6.4.1.1.5 Hydrogen sensors
6.4.1.1.6 Sensors for melts’ analysis
6.4.1.1.7 Sensors for automotive application
6.4.1.2 Mixed potential sensors
6.4.2 Amperometric sensors
6.4.3 Coulometric sensors
6.5 Combined sensors
6.6 Concluding remarks
References
7 Solid-oxide metal–air redox batteries
7.1 Introduction
7.2 Concept of solid-oxide metal–air redox battery
7.3 Thermodynamics and kinetics of solid-oxide metal–air redox battery
7.4 Solid-oxide metal–air redox battery operated on different chemistries
7.4.1 Fe-based chemistry
7.4.2 Other metals-based chemistry
7.5 Performance improvement of SOIARB
7.5.1 Improving performance of the reversible solid-oxide fuel cell
7.5.2 Improving performance of the energy storage unit
7.5.3 Proton-mediated redox activity of iron oxide
7.5.4 Remarks on the cycling degradation of solid-oxide metal–air redox battery
7.6 Metal–air batteries derived from solid-oxide metal–air redox battery
7.7 Summary
Acknowledgments
References
8 Solid oxide fuel cell systems
8.1 Introduction to solid oxide fuel cell systems (benefits and limits)
8.1.1 Short energy scenario background
8.2 Solid oxide fuel cell systems current applications
8.2.1 Power generation
8.2.2 Automotive applications: auxiliary power units and propulsion
8.2.3 Power backup systems
8.2.4 Hybrid systems exploiting biogas/biofuel production
8.2.5 Combined heat (cooling) and power generation
8.2.6 Demonstration for critical environment applications
8.3 Basic system architecture
8.3.1 Ancillary devices
8.3.2 Blowers–pumps–reformer–heat exchangers–afterburner–power converter(s)
8.3.3 Power conditioning devices impacts
8.3.4 Control algorithms for automatic system optimization
8.4 Numerical models
8.4.1 Simulations of specific behavior
8.4.1.1 System/performance degradation over time
8.4.1.2 Gas leakage in solid oxide fuel cell system operation
8.4.1.3 Distributed generation and system dynamics simulation matters
8.4.1.4 Hybrid biofuel–fed plants simulation approach
8.5 Solid oxide fuel cell system costs
References
Index
Back Cover

Citation preview

Solid Oxide-Based Electrochemical Devices

Solid Oxide-Based Electrochemical Devices Advances, Smart Materials and Future Energy Applications

Edited by

MASSIMILIANO LO FARO Italian National Research Council (CNR), Institute for Advanced Energy Technologies “Nicola Giordano” (ITAE), Messina, Italy

Academic Press is an imprint of Elsevier 125 London Wall, London EC2Y 5AS, United Kingdom 525 B Street, Suite 1650, San Diego, CA 92101, United States 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom Copyright © 2020 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress ISBN: 978-0-12-818285-7 For Information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Brian Romer Acquisitions Editor: RZanol Editorial Project Manager: Ail Afzal Khan Production Project Manager: R. Vijay Bharath Cover Designer: Harris Greg Typeset by MPS Limited, Chennai, India

Contents List of contributors

ix

1. Tuning perovskite based oxides for effective electrodes in solid oxide electrochemical cells

1

Ana B. Muñoz-García, Arianna Massaro, Eduardo Schiavo and Michele Pavone 1.1 Introduction 1.2 Perovskite oxides: general structural and electronic features 1.3 Mixed proton electron conductor for proton-conducting solid oxide fuel cells 1.4 Toward triple conducting oxides 1.5 Conclusions References

2. Solid oxide fuel cell’s interconnectors

1 2 10 17 22 23

27

Sicele Luciana Abreu Gonçalves, Roberta de Carvalho Borges Garcia and Tulio Matencio 2.1 Introduction 2.2 Interconnectors 2.3 Metallic interconnectors 2.4 Area-specific resistance 2.5 Protective coatings 2.6 Electrodeposition 2.7 Conclusion Acknowledgment References

3. In situ photoelectron spectromicroscopy for the investigation of solid oxide based electrochemical systems

27 29 30 32 33 36 50 50 50

55

Benedetto Bozzini, Matteo Amati, Luca Gregoratti, Francesca Rossi and Maya Kiskinova 3.1 Introduction 3.2 The soft X-ray scanning photoemission microscope at the ESCA microscopy beamline at Elettra 3.3 Examples of SOFCs SPEM characterization in different configurations and operating conditions 3.4 Conclusion References

55 57 67 87 88 v

vi

Contents

4. Protonic-based ceramics for fuel cells and electrolyzers

91

Kawther Thabet, Annie Le Gal La Salle, Eric Quarez and Olivier Joubert 4.1 Mechanism of proton conduction 4.2 Electrolyte materials 4.3 Electrode materials References

5. Multilevel modeling of solid oxide electrolysis

91 94 104 115

123

Jakub Kupecki, Luca Mastropasqua, Konrad Motylinski and Domenico Ferrero 5.1 5.2 5.3 5.4 5.5 5.6 5.7

Introduction Theoretical background Materials and micro-electrochemistry Multidimensional approaches to cell/stack modeling Typical operating conditions Thermal management of solid oxide electrolyzer stacks Thermal management of solid oxide electrolyzer through the use of heat pipes 5.8 System analysis and applications Acknowledgment References

6. Sensors based on solid oxide electrolytes

123 125 128 132 139 143 149 154 159 159

167

A. Demin, E. Gorbova, A. Brouzgou, A. Volkov and P. Tsiakaras 6.1 Introduction 6.2 Brief history 6.3 Materials for sensors 6.4 Types of sensors 6.5 Combined sensors 6.6 Concluding remarks References

7. Solid-oxide metal air redox batteries

167 168 169 177 203 205 205

217

Cuijuan Zhang and Kevin Huang 7.1 7.2 7.3 7.4 7.5

Introduction Concept of solid-oxide metal air redox battery Thermodynamics and kinetics of solid-oxide metal air redox battery Solid-oxide metal air redox battery operated on different chemistries Performance improvement of SOIARB

217 219 221 223 227

Contents

7.6 Metal air batteries derived from solid-oxide metal air redox battery 7.7 Summary Acknowledgments References

8. Solid oxide fuel cell systems

vii 241 244 247 247

251

Giovanni Brunaccini 8.1 Introduction to solid oxide fuel cell systems (benefits and limits) 8.2 Solid oxide fuel cell systems current applications 8.3 Basic system architecture 8.4 Numerical models 8.5 Solid oxide fuel cell system costs References Index

251 255 266 276 285 288 295

List of contributors Matteo Amati Elettra Sincrotrone Trieste S.C.p.A., Basovizza-Trieste, Italy Benedetto Bozzini Departmento of Energy, Politecnico di Milano, Milan, Italy A. Brouzgou Laboratory of Alternative Energy Conversion Systems, Department of Mechanical Engineering, School of Engineering, University of Thessaly, Volos, Greece Giovanni Brunaccini Consiglio Nazionale delle Ricerche - Istituto di Tecnologie Avanzate per l’Eenergia “Nicola Giordano”, Messina, Italy A. Demin Laboratory of Electrochemical Devices Based on Solid Oxide Proton Electrolytes, Institute of High Temperature Electrochemistry, RAS, Yekaterinburg, Russia; Laboratory of Materials and Devices for Clean Energy, Ural Federal University, Yekaterinburg, Russia Domenico Ferrero Department of Energy, Polytechnic University of Turin, Torino, Italy Roberta de Carvalho Borges Garcia Department of Chemistry, Federal University of Minas Gerais, Belo Horizonte, Brazil Sicele Luciana Abreu Gonçalves Department of Chemistry, Federal University of Minas Gerais, Belo Horizonte, Brazil E. Gorbova Laboratory of Electrochemical Devices Based on Solid Oxide Proton Electrolytes, Institute of High Temperature Electrochemistry, RAS, Yekaterinburg, Russia; Laboratory of Materials and Devices for Clean Energy, Ural Federal University, Yekaterinburg, Russia; Laboratory of Alternative Energy Conversion Systems, Department of Mechanical Engineering, School of Engineering, University of Thessaly, Volos, Greece Luca Gregoratti Elettra Sincrotrone Trieste S.C.p.A., Basovizza-Trieste, Italy Kevin Huang Department of Mechanical Engineering, University of South Carolina, Columbia, SC, United States Olivier Joubert Institut des Matériaux Jean Rouxel (IMN), CNRS-Université de Nantes, 44322 Nantes Cedex 3, France Maya Kiskinova Elettra Sincrotrone Trieste S.C.p.A., Basovizza-Trieste, Italy Jakub Kupecki Department of High Temperature Electrochemical Processes (HiTEP), Institute of Power Engineering, Warsaw, Poland; National Fuel Cell Research Center (NFCRC), University of California, Irvine, Irvine, CA, United States ix

x

List of contributors

Annie Le Gal La Salle Institut des Matériaux Jean Rouxel (IMN), CNRS-Université de Nantes, 44322 Nantes Cedex 3, France Arianna Massaro Department of Chemical Sciences, University of Naples Federico II, Naples, Italy Luca Mastropasqua Advanced Power and Energy Program, University of California, Irvine, Irvine, CA, United States Tulio Matencio Department of Chemistry, Federal University of Minas Gerais, Belo Horizonte, Brazil Konrad Motylinski Department of High Temperature Electrochemical Processes (HiTEP), Institute of Power Engineering, Warsaw, Poland; Institute of Heat Engineering, Warsaw University of Technology, Warsaw, Poland Ana B. Muñoz-García Department of Physics E.Pancini, University of Naples Federico II, Naples, Italy Michele Pavone Department of Chemical Sciences, University of Naples Federico II, Naples, Italy Eric Quarez Institut des Matériaux Jean Rouxel (IMN), CNRS-Université de Nantes, 44322 Nantes Cedex 3, France Francesca Rossi Department of Innovation Engineering, University of Salento, Lecce, Italy Eduardo Schiavo Department of Chemical Sciences, University of Naples Federico II, Naples, Italy Kawther Thabet Institut des Matériaux Jean Rouxel (IMN), CNRS-Université de Nantes, 44322 Nantes Cedex 3, France P. Tsiakaras Laboratory of Electrochemical Devices Based on Solid Oxide Proton Electrolytes, Institute of High Temperature Electrochemistry, RAS, Yekaterinburg, Russia; Laboratory of Materials and Devices for Clean Energy, Ural Federal University, Yekaterinburg, Russia; Laboratory of Alternative Energy Conversion Systems, Department of Mechanical Engineering, School of Engineering, University of Thessaly, Volos, Greece A. Volkov Laboratory of Electrochemical Devices Based on Solid Oxide Proton Electrolytes, Institute of High Temperature Electrochemistry, RAS, Yekaterinburg, Russia; Laboratory of Materials and Devices for Clean Energy, Ural Federal University, Yekaterinburg, Russia Cuijuan Zhang School of Chemical Engineering and Technology, Tianjin University, Tianjin, P.R. China

CHAPTER 1

Tuning perovskitebased oxides for effective electrodes in solid oxide electrochemical cells Ana B. Muñoz-García1, Arianna Massaro2, Eduardo Schiavo2 and Michele Pavone2 1 Department of Physics E.Pancini, University of Naples Federico II, Naples, Italy Department of Chemical Sciences, University of Naples Federico II, Naples, Italy

2

Contents 1.1 Introduction 1.2 Perovskite oxides: general structural and electronic features 1.2.1 Oxygen anion migration: vacancy formation and vacancy hopping 1.3 Mixed protonelectron conductor for proton-conducting solid oxide fuel cells 1.3.1 Ba-based perovskite oxides: stability versus hydration 1.3.2 Electron conduction and catalytic features at doped BaZrO3 1.4 Toward triple conducting oxides 1.4.1 Enhancing proton conduction in mixed ion-electron conductor materials 1.4.2 Electrocatalysis toward bifunctional oxygen evolution reaction/oxygen reduction reaction catalysts 1.5 Conclusions References

1 2 4 10 13 14 17 18 21 22 23

1.1 Introduction The need to reduce operating temperature in solid oxide fuel cells (SOFCs) has led to the development of effective cathode materials with the characteristics of mixed ion-electron conductors (MIECs). The ability of these materials to transport the oxide ion makes them very effective for the oxygen reduction reaction (ORR). The latter can occur on the whole cathode surface instead of being restricted to the triple-phase boundary (TPB) among the cathode, electrolyte, and air [1] (Fig. 1.1). With these materials, low overpotentials for the ORR become available in the intermediate temperature range (600°C800°C). Most commonly, MIECs are transition metal (TM) oxides with perovskite structure Solid Oxide-Based Electrochemical Devices DOI: https://doi.org/10.1016/B978-0-12-818285-7.00001-0

© 2020 Elsevier Inc. All rights reserved.

1

2

Solid Oxide-Based Electrochemical Devices

Figure 1.1 Two possible oxygen incorporation paths: surface path (top) showing the TPB where the reaction occurs and bulk path (bottom) highlighting in red the ORR active area. ORR, Oxygen reduction reaction; TPB, triple-phase boundary. Reprinted with permission from A.B. Munoz-Garcıa, A.M. Ritzmann, M. Pavone, J.A. Keith, E.A. Carter, Oxygen transport in perovskite-type solid oxide fuel cell materials: insights from quantum mechanics, Acc. Chem. Res. 47 (11) (2014) 33403348. r2014 American Chemical Society.

and formula AMO3 where A is typically a large cation, and the M site is usually occupied by a first-row TM (Cr, Mn, Fe, and Co). Oxygen transport in these materials occurs via a vacancy-mediated hopping mechanism, with the diffusion coefficient having an Arrhenius form D 5 Ae2Q=kB T where the apparent activation energy strongly depends on the oxygen vacancy formation energy and on the activation enthalpy for O22 migration to a near vacant site [2] (vide infra). How the chemical formula and the crystal structure affect the electronic features and the defect chemistry of the perovskite oxides is not trivial. Here we aim at dissecting these fundamental structureproperty relationships behind the perovskite-based materials, which are employed as electrodes in solid oxide electrochemical cells, by means of first-principles theoretical simulations within the framework of the density functional theory (DFT).

1.2 Perovskite oxides: general structural and electronic features Perovskite oxides constitute the vast majority of MIEC materials. This is due to their high thermal stability, their catalytic activity toward ORR

Tuning perovskitebased oxides for effective electrodes in solid oxide electrochemical cells

3

Figure 1.2 Cubic perovskite structure of CaTiO3 in the Pm3m space group. Color code: Ca (yellow), Ti (blue), and O (red).

and the high electronic conductivity. Their general structure is ABO3 with the A and B ions in their (II) and (III) oxidation states, respectively. The A-site is usually occupied by a large cation, while the B-site is occupied by a TM in an octahedral cavity of the oxygen sublattice. The ideal perovskite structure has a cubic symmetry, in the Fm3m or Pm3m space groups, as the prototypical CaTiO3 perovskite depicted by Fig. 1.2. However, usually the size of the cations and the different occupations of the TM d manifold can induce distortions in the structure that lower the overall symmetry. Typical perovskite oxides used for MIEC applications are the ones with the A-site occupied by La and the B-site by a first-row middle or late TM (e.g., Cr, Mn, Fe, and Co). LaCrO3, LaMnO3, and LaFeO3 exhibit an orthorhombic distortion, while LaCoO3 a rhombohedral one. The LaMO3 (M 5 Cr, Mn, Fe) have a high-spin configuration and a preference for an antiferromagnetic ordering at low temperatures [3]. However, at operating temperatures of FCs, they all become paramagnetic. LaCoO3 is low-spin and nonmagnetic below 90K but becomes paramagnetic at higher temperatures [4,5]. The spin states of Co in such system have been largely debated in literature [610]. In the calculations described in this text, Co will be considered in an intermediate spin configuration [11]. Another interesting feature of perovskite oxides for MIEC applications is how their structural and electronic properties can easily be tuned by substitution both in the A and B sites. Throughout this chapter we will be focusing on two main classes of materials: the Sr-doped LaMO3 (M 5 Cr, Mn, Fe, Co) that represent the state-of-the-art for both high-temperature FCs and MIEC materials for intermediate-temperature

4

Solid Oxide-Based Electrochemical Devices

(IT) SOFCs, and the Sr2Fe22xMoxO6 (SFMO), which were proposed more recently and have shown good performances in symmetric SOFCs [12]. In the next sections, we will discuss the oxygen vacancy formation and diffusion of several perovskites and see how different substitutional defects affect such properties that are crucial features of an efficient MIEC material.

1.2.1 Oxygen anion migration: vacancy formation and vacancy hopping As mentioned in the introduction, the formation of oxygen vacancies is a key factor in MIEC materials. The hopping mechanism for oxide diffusion, in fact, needs a vacant site close to the migrating ion. We can express oxygen vacancy formation in KrögerVink notation as: 1 0 x 2MMx 1 OO -2MM 1 VO:: 1 O2ð gÞ 2

(1.1)

where the reaction enthalpy can be obtained from the calculation of the perfect crystal (without the oxygen vacancy), the defective crystal (in presence of the oxygen vacancy VO€ ), and the gas-phase oxygen molecule in 0 its triplet ground state. MMx and MM represent the two TM atoms that are close to the oxygen site where the vacancy will be formed in the pristine x and defective crystal, respectively. OO represents the oxygen atom in the parent crystal that is missing after the formation of the vacancy. The creation of a VO€ by removal of a neutral oxygen atom creates an AMO32δ lattice. First-principles calculations can be a powerful tool to compute such reaction enthalpies. It is common to model such extended solid systems with DFT [13,14]; however, strongly correlated materials as TM oxides require some treatment of the well-known self-interaction error. In cases where hybrid functionals are too expensive to be used, this can be done by means of DFT 1 U, setting the appropriate values of the UJ parameters [15]. A full description of the theoretical models used to characterize these materials and of their parametrization is beyond the scope of this chapter. We refer the interested reader to the references cited in the text for the computational details of each specific case. The simplest way to define the vacancy formation energy is the following: 1 ΔEf ;vac 5 Edefective 2 Eperfect 1 EO2 2

(1.2)

Tuning perovskitebased oxides for effective electrodes in solid oxide electrochemical cells

5

By including the zero-point energy contributions, we can approximate the ΔHf,vac at the absolute zero:   3ðN21 3N23 XÞ23 1 X1 1 1 ΔHf ;vac ð0Þ 5 ΔEf ;vac 1 hν i;defective 2 hν j;perfect 1 hν O2 2 2 2 2 j51 i52 (1.3) where h is the Planck’s constant, the νs are the vibrational frequencies calculated within the harmonic oscillator approximation, and N is the number of atoms in the cell without the defect. From Eq. (1.3) we can arrive to a finite temperature expression by integrating the heat capacities from zero to the temperature of interest as described in Ref. [16]. 3N23 X hν i;defective hν j;perfect 2 hν j;perfect =kB T 2 1 ehν i;defective =kB T 2 1 j51 e i51 ð  1 T 1 Cp;O2 ðT 0 ÞdT 0 2 0

ΔHf ;vac ðT Þ 5 ΔHf ;vac ð0Þ 1

3ðN21 XÞ23

(1.4) However, in the same article it is shown that for La12xSrxFeO32δ (LSF) the addition of vibrational and finite temperature contributions affects the vacancy formation energy by less than 0.1 eV. Hence, for many perovskite oxides it is sufficient to analyze the trends in ΔE values as calculated in Eq. (1.2). In LaMO3 (M 5 Cr, Mn, Fe, Co), oxygen vacancy formation energies exhibit a nonmonotonic trend along the period. Fig. 1.3 depicts both the experimental and calculated (both with HSE and DFT 1 U) energies [3,17]. In order to explain the Evac trend, we must look at the charge redistribution upon removal of the oxygen atoms. DFT calculations show that the two electrons introduced into the system are mostly localized on the two TM ions that were involved in the bonding with the oxygen atom that is removed. These bonds are in fact more covalent in character in the pristine material, while La ions are closer to their expected ionic charge (i.e., 3 1 ). No net charge variations on these atoms are observed when forming the VO:: . Thus the process of oxygen vacancy formation can be divided in two steps: (1) breaking the MOM bonds and (2) formal reduction of M31 ions to M21 ions. The energy needed to form the

6

Solid Oxide-Based Electrochemical Devices

Figure 1.3 Oxygen vacancy formation energies, Evac, for M 5 (Cr, Mn, Fe, Co) in LaMO3. Experimental data are taken from Ref. [17]. The theoretical value for Co is averaged over the high-spin and low-spin cases. Inset: pseudocubic supercell for LaMO3 structures (A). Scheme of the d orbital occupations before (left) and after (right) vacancy formation (B). Reproduced from M. Pavone, A.M. Ritzmann, E.A. Carter, Quantum-mechanics-based design principles for solid oxide fuel cell cathode materials, Energy Environ. Sci. 4 (2011) 49334937 with permission of the Royal Society of Chemistry.

vacancy can be traced back to how expensive it is to break the TMoxo bonds compared to the energy gain in reducing the TM ions. The latter factor is inherently connected to a quantum-mechanical quantity, that is, exchange energy. A closer look at the partially occupied 3d shells of these TMs will clarify the differences in Evac. When a spin-up electron goes to one TM and a spin-down electron goes to the antiferromagnetically coupled neighbor TM, the ground electronic states of the reduced TMs are formed. Moving from Cr31 to Mn31, the number of exchange interactions (between electrons of the same spin) increases when an electron is added. Hence, the reduced manganese ion is more stable than the reduced chromium one. Moving forward to high-spin Fe31, the additional electron must be added with an antiparallel spin with respect to the other five, occupying one of the partially filled t2g orbitals. As a result, no exchange stabilization is gained and the energy rises due to the repulsion of the two electrons in the doubly occupied orbital. The addition of an electron to the intermediate spin Co31 produces four extra dd exchange terms, which lowers Evac again. The oscillating energy trend we just explained is accompanied by an overall decrease from middle to late TMs. This is due to the different strengths of the TMoxo bonds that are broken in order to form the vacancy. Early TMs are in fact known to form

Tuning perovskitebased oxides for effective electrodes in solid oxide electrochemical cells

7

very strong bonds with oxygen with a polar covalent character. As the d shell is filled, moving toward late TMs, the repulsion between oxygen and metal lone pairs weakens the bonds. A way to improve the materials discussed earlier is via doping in the A (La) site with a divalent cation (e.g., Sr21, Ca21, Ba21). This substitution introduces a hole in the system, which has a twofold effect: it enhances the p-type conductivity by increasing the number of carriers (holes) and lowers the formation energies for oxygen vacancies due to charge compensation. Two important materials of this class are La12xSrxFeO3 (LSF) and La12xSrxMnO3 (LSM) with x 5 0.25 and 0.5. LSF is a good electrocatalyst, while LSM exhibits a better bulk oxide ion transport and is the parent material of La0.75Sr0.25Co0.2Fe0.8O3, which is the prototypical MIEC cathode [16,18,19]. Both LSM and LSF display a decreasing trend of oxygen vacancy formation energy with increasing Sr content. This effect is due to charge compensation between the holes introduced by the Sr defect and the electrons introduced by the oxygen vacancies. Still, the extent by which the ΔEf,vac is lowered is different in the two materials. The reason for this difference can be found again in the (de)localization of the excess electrons upon oxygen removal. As discussed previously for LaMO3, most of the charge is localized on the neighboring TM atoms. The remainder of this charge is delocalized on the oxygen sublattice due to the partial hybridization of M eg and O 2p orbitals. In the Sr-free materials, this charge is smaller than 30%. Sr substitution has been reported to increase the covalent character of the MO bonds, which increases the percentage of charge that is redistributed on the oxygen sublattice to 40%50% for Mn and 80% for Fe, explaining the larger effect on LSF (see Ref. [1], and references therein). Let us now address oxygen vacancy formation in the second class of MIEC materials we mentioned in the previous section: Sr2Fe22xMoxO62δ (SFMOx). In SFMO1.0 the vacancy can be formed in a FeOFe, FeOMo, or MoOMo site, the first one having a much lower ΔEf,vac than the other two. The trend follows the “bond strength rule” outlined earlier. That is, Fe is a late TM and Mo is an early TM and so the more MoO bonds we have to break, the higher the ΔEf,vac. Besides, when the defect occurs in a FeOFe site, the charge is partially delocalized over the oxygen sublattice, which does not happen in the other two cases. A material of this class that has shown outstanding MIEC properties is SFMO0.5. This is a nonstoichiometric solid, exhibiting

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Solid Oxide-Based Electrochemical Devices

an oxygen-deficient composition: Sr2Fe1.5Mo0.5O62δ (δexp 5 0.10(2)) [20]. Mo ions are randomly distributed at the B-site in the crystal, without any aggregation or specific ordering, forming a solid solution with the Fe cation. Calculated vacancy formation energies show, as expected, a lower energy for FeVO:: Fe with respect to FeVO:: Mo. No MoOMo is present due to the low concentration and random distribution of Mo in the cell. At oxygen vacancy concentrations close to the experimental ones, the ΔEf,vac is close to zero, which confirms the nonstoichiometric nature of SFMO0.5. As previously mentioned, the oxide ion transport occurs via a vacancy-mediated hopping mechanism. The self-diffusion coefficient of the oxide ion can be expressed in terms of transition state theory [21,22] as:     CV 1 ΔSf ;vac =kB 2ΔHf ;vac =kB T 1 2 ΔS¼ =kB 2ΔHmigr =kB T DV B pffiffiffiffiffiffiffi e e e 1 ν0a e DO 5 pO2 6 CO (1.5) where CO and CV are the oxygen and vacancy concentration, respectively, and DV is the vacancy diffusion coefficient. The activation energy is the sum of the vacancy formation energy and the oxygen migration energy. We have already extensively discussed the first one in MIEC materials and will now address the factors that affect ΔHmig in perovskites. Fig. 1.4A shows the minimum energy path (MEP) for the migration of the oxide ion in LaFeO3 modelled via the climbing image nudged elastic band (CI-NEB) model [23]. The corresponding energies along the reaction coordinate are shown in Fig. 1.4B. For the LaMO3 series, experimental values of the O22 migration barriers are around 0.80.9 eV and do not have a strong dependence on the Sr doping [24]. The migration path has a curved shape, with the oxide ion moving in a plane that contains four TM ions; two La ions are above and below the center of the plane. The change in the oxidation states of two TMs involved in the migration pathway allows us to follow the electron transfer coupled to the ionic one. Calculated migration barrier for LaFeO3 is 0.79 eV [16], which matches the experimental value of 0.77 eV [25]. In materials with a larger delocalization of charge, we will not observe a clear coupled ionelectron transfer. However, this will not affect the migration barriers, which are governed by steric and electrostatic effects. In SFMO0.5 the migration pathway exhibits the characteristic curved shape found in other perovskite oxides, as theoretically predicted and

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Figure 1.4 Minimum energy path for oxide ion hopping between two FeOFe sites in LaFeO3 (A). Relative CI-NEB energy profile (B). Magnetic moments of the three iron atoms involved in the migration process (C). CI-NEB, Climbing image nudged elastic band. Reprinted with permission from A.M. Ritzmann, A.B. Munoz-Garcıa, M. Pavone, J.A. Keith, E.A. Carter, Ab initio DFT 1 U analysis of oxygen vacancy formation and migration in La12xSrxFeO32δ (x 5 0, 0.25, 0.50), Chem. Mater. 25 (15) (2013) 30113019. r2013 American Chemical Society.

confirmed by neutron diffraction experiments [26]. In this material, the environment around the predicted energy path can vary with the varying concentrations and distribution of the Mo ions. An analysis on how the migration barriers are affected by the presence and positions of Mo can help us understand its role on oxide migration properties in SFMO. Fig. 1.5 depicts different migration pathways calculated with CI-NEB model in a cubic SFMO0.5 with δ 5 0.25. For this material, two distributions of the Mo ions in the cell are considered: (1) diagonal with two Mo ions at the opposite vertices of the cubic cell and (2) plane with the two ions on same plane, at the opposite vertices of a face of the cube. When an oxide ion jumps to its nearest vacancy, it passes over a saddle point on the potential energy surface lying on one of the planes highlighted in Fig. 1.5A and C, containing three Fe atoms and a Mo. The calculated migration energy for a 1-2 jump in the diagonal distribution is 0.24 eV (Fig. 1.5B). It increases to 0.33 eV at lower concentration of vacancies (δ 5 0.125). These values are much lower than the one calculated for the LaMO32δ series, suggesting an important role of Mo in oxide migration even if it is not directly involved in the vacancy formation (vide supra). For the 1-2 jump in the plane distribution, we observe a rise in the migration barrier (ΔEmig 5 0.61 eV) with respect to the diagonal one, even though the planes on which the MEP lies are identical.

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Figure 1.5 SFMO0.5 (δ 5 0.25) oxide ion migration features: diffusion planes in SFMO (A), energy profile of the minimum energy path (B), and oxide diffusion pathways (C). Reproduced from A.B. Munoz-Garcıa, M. Pavone, A.M. Ritzmann, E.A. Carter, Oxide ion transport in Sr2Fe1.5Mo0.5O62δ, a mixed ion-electron conductor: new insights from first principles modeling, Phys. Chem. Chem. Phys. 15 (2013) 62506259 [27] by permission of the PCCP Owner Society.

This indicates a long-range effect of the Mo distribution on migration barriers. The 1-3 jump exhibits an even higher ΔHmig of 0.80 eV. In this case, what we observe is a short-range effect, due to the fact that Mo is not present on the migration plane, resulting in migration barriers that are close to those observed in the parent SrFeO3 material. The reason for the positive effect of Mo on migration barriers can be found in classical electrostatic arguments: the positive Mo61 ion stabilizes the transition state that involves a negative oxide ion far away from its counter ions.

1.3 Mixed protonelectron conductor for protonconducting solid oxide fuel cells The need to move toward CO2-neutral and renewable energy technologies has led scientific research to focus on energy storage and conversion devices, which are required due to the intermittent nature of clean

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sources. In this context, the green hydrogen economy arises as a promising choice. Hydrogen is considered the most versatile and environmental-friendly energy carrier. It can be used as a clean fuel, generating water as the only combustion by-product (H2 1 O2-H2O), or as a feedstock to produce carbon-based fuels (e.g., CH3OH and CH4) via the carbon-neutral water splitting reaction (H2O-H2 1 O2). Efficient FC devices that can work reversibly are required for the deployment of renewable sources in self-consistent power/storage units. These devices can store the energy surplus by producing H2 as fuel in the electrolyzer cell mode and convert it back to electricity “on demand” in the reverse FC mode. Solid oxidebased electrolyzer and fuel cells (SOEC/FCs) are a potential alternative to the state-of-the-art lowtemperature cells based on polymer-exchange membrane electrolytes since they would enable medium-to-large scale H2 production/conversion [28]. Despite traditional SOEC/FCs are based on oxide-conducting materials, there is an increasing interest in proton-conducting oxides. One of the major advantages of using proton-conducting SOEC/FCs is the higher ionic conductivity in the desired IT range. Proton transport occurs via the Grotthus-type mechanism with activation energies that are much lower than those for O22 (0.30.5 eV vs typical 0.80.9 eV for O22 [29,30]). Doped perovskites ABxB0 12xO32δ (where A 5 Ca, Sr, Ba; B 5 Ce, Zr, Ti; B0 5 Y, Sc, Ln) show varying proton conductivity and thermodynamic stability. Insulating BaCe12x2yZrxYyO32δ (BCZY) is one of the most popular PC ceramic electrolytes, since it combines the good proton conduction of cerates with the large chemical stability of zirconates [3032]. Major advances on PC-electrolytes have not been sufficient to bring PC-SOEC/FCs to an applicative stage because of severe limitations on the electrodes. Besides compatibility with established electrolytes, PC-SOEC/FC electrode materials must have high catalytic activity, high electric conductivity and high rates of proton diffusion. Metal, MIEC and composite (MIEC-electrode/PC-electrolyte) electrodes provided so far showed poor performances in the PC regime. The main problems are related to the sluggish kinetics (high overpotentials) associated with the air electrode, that is, the electrocatalyst for O2-H2O conversion, leading to huge polarization resistance. Following the same logic adopted for oxideconducting systems, it is possible to extend the reaction area from the TPB to the whole electrode surface by developing electrode materials based on mixed proton and electron conductors (MPECs). Fig. 1.6 compares the state-of-the-art systems, that is, metal, MIEC and composite

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Figure 1.6 Schematic representation of the state-of-the-art and target features for proton-conducting solid oxide fuel cells.

electrodes faced to a PC-electrolyte, with the optimal configuration that could be achieved through an MPEC electrode. The schematic representation clearly highlights the chance to have a more effective device in the third case. In order to investigate and develop novel MPECs, it is essential to keep in mind the key processes of proton transport mechanism in ABO3 perovskite oxides. As for oxide conduction, a basic requirement is the presence of oxygen vacancies because they enable the insertion of water under moist atmosphere. In fact, proton charge carriers are formed upon dissociative adsorption of water in O-deficient perovskite lattices: the water molecule dissociates into an OH2 group that occupies a vacant site and an H1 that binds to an oxide forming a second OH2 group. This process has been proposed by Iwahara et al. [33]: x H2 O 1 VO:: 1 OO -2OHO

(1.6)

where oxygen vacancy forms according to the reaction reported in Eq. (1.1). The energy associated with the Eq. (1.6) can be defined as: ΔEhydr 5 E2OH 1 Edefect 2EH2 O

(1.7)

where E2OH is the energy of the two protons-containing cell, Edefect is the energy of the O vacancycontaining cell, and E H2 O is the energy of the isolated water molecule. Then, mobile protons are generated via a twostep mechanism: (1) fast rotation of the hydroxyl unit and (2) O vacancymediated hopping of a lone proton between two adjacent oxide sites, which has been identified as the rate-limiting step [30,34]. The design and search on MPECs is still a challenge due to H1/e2 recombination issues and only few materials have shown such features. Starting from the state-of-the-art PC-electrolytes, a possible design

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strategy consists of doping with suitable elements that can induce electron conductivity. We can summarize the key features needed for a perovskite oxide material to be a good MPEC in four descriptors: (1) low oxygen vacancy formation energy; (2) favorable hydration energy; (3) low energy barrier of proton migration; and (4) good electron conduction, even in the hydrated state. Before going through these points in Section 1.3.2, we provide a brief overview on Ba-based perovskite oxides as the main class of materials that are at the focus of intense research in this field.

1.3.1 Ba-based perovskite oxides: stability versus hydration Among all the perovskite oxides that are active in the proton conductivity regime, Ba-based ones have shown most promising properties [35]. However, the fabrication of high-performing Ba-based solid oxide cells strictly depends on the balance between two significant features: chemical stability and hydration. This is due to the operating conditions of SOEC/FC devices. The component materials have to be exposed to high steam concentration. From one side, the high steam concentration improves the hydrogen production and expands the application temperature range, since water depresses the formation of other charge carriers than protons. On the other side, the possible reactions with water may lead to the cell degradation. Thin films are more sensitive to chemical instability, but the use of thicker layers is hindered by possible ohmic losses that would require the application of high potentials [36]. Considering this important issue, cerate proton-conducting oxides are not suitable for reversible SOEC/FC applications due to their chemical instability in water, while zirconate proton-conducting oxides have been predicted to be thermodynamically stable in water [31]. For this reason, BaZrO3-based (BZO) perovskites would be the most promising PC ceramics for solid oxide cells because of the high bulk H1 conductivity and excellent chemical stability, provided better synthetic strategies are developed to overcome its poor sinterability [37]. The experimental techniques that have been developed so far in order to produce highperforming materials with cost-effective synthetic procedures are beyond the purpose of this chapter. Thus in the following sections, we will report the main advances concerning the electronic and catalytic properties of BZO-based electrodes that have been achieved by means of computational modelling and theoretical simulations.

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1.3.2 Electron conduction and catalytic features at doped BaZrO3 As already anticipated in Section 1.2, while PC ceramics have been extensively investigated as electrolytes for PC-SOEC/FCs, the development of corresponding single-phase electrode components has been hindered by difficulties in finding efficient MPECs with also effective catalytic activity toward ORR and oxygen evolution reaction (OER). Very few MPECs have been developed, owing to the fast protonelectron recombination that limits the chance to have good conductivity for both charge carriers. BaCe0.5Bi0.5O32δ and BaZr0.5Pr0.3Y0.2O32δ are two examples, where electronic conductivity has been induced into the state-of-the-art PC ceramic electrolytes (BaCeO3, BaZrO3) by expensive rare earth-metals doping [32,38]. This desired effect has been achieved also by doping BaZrO3 with cobalt (BaZr0.6Co0.4O32δ). However, avoiding cobalt in SOEC/FC devices is recommended for its high cost, compared to other TMs, but also because it induces high thermal expansion coefficients, which are detrimental to the electrode/electrolyte thermal compatibility and to the stability of the cell [39]. To this end, doping BZO with TMs that are cheaper and more abundant than Co, such as Fe and Mn, can be a possible strategy. A recent theoretical work compares the potential MPEC features of BaZr0.75Fe0.25O32δ (BZF) and BaZr0.75Mn0.25O32δ (BZM) [40]. For what concerns electronic properties, Mn doping results to be more efficient in enhancing electron conductivity, as revealed by the projected density of states reported in Fig. 1.7. In particular, BZF shows a semiconductive nature both when dry or hydrated, so that electron conduction can only occur via thermally activated small polaron hopping. In BZM, Mn d states cross the Fermi level leading to a quasimetallic electronic structure, which is retained upon hydration [40]. The doping can also affect other properties that are relevant to obtain a MPEC material, such as oxygen vacancy concentration, hydration and proton transport. Oxygen vacancy formation energies are significantly decreased with respect to BZO parent material. DFT 1 U calculations predict ΔEform 5 0, 0.924, and 6.711 eV for BZF, BZM, and BZO, respectively, with vacancy preferentially formed along FeOFe (in BZF) and MnOMn (in BZM) directions. As already demonstrated for Fe-rich OC-perovskites [16,20,27], the easy oxygen vacancy formation is correlated to the degree of charge

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Figure 1.7 PDOS of hydrated BZF and BZM calculated at the PBE 1 U level. The gray dashed line indicates the Fermi energy. PDOS, Projected density of states. Reproduced from A.B. Munoz-Garcıa, M. Tuccillo, M. Pavone, Computational design of cobalt-free mixed proton-electron conductors for solid oxide electrochemical cells, J. Mater. Chem. A 5 (23) (2017) 1182511833 by permission of The Royal Society of Chemistry.

delocalization on the O sublattice, which acts as an “electron buffer” by spreading the extra charge of the leaving oxygen (vide supra). This trend in vacancy formation explains the huge difference in hydration properties between the two materials: BZF shows a very convenient hydration energy equal to 20.500 eV, while Mn can only lead to a slight improvement of BZO hydration capabilities (ΔEhydr 5 0.531 and 0.638 eV for BZM and BZO, respectively). For what concerns proton transport, we can say that both dopants lower the migration barrier of the pure BZO. This has been attributed to a favorable local distortion induced by the dopant, which allows the TMO6 octahedral moieties to be more flexible and optimize their oxygen atoms during the proton jump. As can be noticed in Fig. 1.8, this effect is enhanced in a diagonal configuration (DC) of the dopants, that is, homogeneous and isotropic distribution in the cell. When analyzing less homogeneous cases, edge (EC) and plane (PC) configurations, there is a major difference between the two materials: local segregations of Mn can lead to trapping states for the moving proton, while Fe just causes a slight increase of the migration barrier. In order to characterize the catalytic features of such materials, the ORR and the OER can be modelled assuming a series of four consecutive proton-coupled electron transfer steps (after the initial O2/H2O adsorption step, respectively):

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Figure 1.8 Proton migration in BZF/BZM: (A) scheme of nonequivalent proton sites for diagonal (DC), plane (PC), and edge (EC) BZF/BZM. For PC and EC the symmetry planes are indicated; (B) energy profiles of the MEPs for O  H?O jumps in BZF (green) and BZM (purple) for every configuration. MEP for BZO is also shown in black solid lines as a reference. MEP, Minimum energy path. Reproduced from A.B. MunozGarcıa, M. Tuccillo, M. Pavone, Computational design of cobalt-free mixed protonelectron conductors for solid oxide electrochemical cells, J. Mater. Chem. A 5 (23) (2017) 1182511833 by permission of The Royal Society of Chemistry.

ORR R1:O2 1 T-TO2 R2:TO2 1 H1 1 e -TOOH R3:TOOH 1 H1 1 e -TO 1 H2 O R4:TO 1 H1 1 e -TOH R5:TOH 1 H1 1 e -OH2 OER E1:H2 O 1 T-TOH2 E2:TOH2 -TOH 1 H1 1 e E3:TOH-TO 1 H1 1 e E4:TO 1 H2 O-TOOH 1 H1 1 e E5:TOOH-O2 1 T 1 H1 1 e where T represents a surface active site and TOH2, TOH, TO, TOOH, and O2 represent the surface (intermediate) species that are chemisorbed on the active site.

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The electrocatalytic activity can be quantified via free-energy calculations of each step within the Nørskov approach [41] that allows to determine the ORR and OER overpotentials: ηORR 5 1:11 2 UORR ηOER 5 UOER 2 1:11

(1.8)

where UORR and UOER are the highest/lowest potential delivered/ required to/by the cell for which all the steps (R1R5/E1E5) are downhill in the ORR/OER process, respectively, and 1.11 eV is the ΔG per electron calculated at DFT-PBE level of theory for the reaction: 2H2 O$O2 12H2

(1.9)

We refer the interested reader to Ref. [40] and references therein for more details. Mn centers in the barium zirconate environment showed the lowest overpotentials in both reactions (ηORR 5 0.81 V, ηOER 5 0.93 V), while Fe centers seem to be inefficient for both ORR and OER (ηORR 5 1.04 V, ηOER 5 1.07 V). However, the doping does not affect the reaction mechanisms, with the formation of TOOH (R2) being the potential-determining step (PDS) for the ORR and the TOH oxidation step (E3) for the OER PDS in both BZM and BZF. In conclusion, both iron and manganese are promising dopants for BZO to obtain MPEC properties, the former in terms of hydration and proton transport and the latter for electronic and catalytic features. However, to date no single-phase MPEC electrode is used in PCSOEC/FCs. Despite the limitations especially concerning the electrocatalytic properties, current electrodes are mostly composites, made of MIEC oxides and the PC-electrolyte, which provide the electronic and proton conductivity, respectively. In the next section, we will discuss a new family of perovskite oxides that are at the forefront for the development of reversible SOEC/FC devices.

1.4 Toward triple conducting oxides Inspired by the good performance in PC regime of some perovskite oxides, an alternative approach has been proposed more recently by combining the conduction of the three charge carriers (e2/O22/H1) in a perovskite oxide [42]. These triple conducting oxides (TCOs) can be obtained in principle by inducing proton conduction into a state-of-theart MIEC material. MIEC perovskites and perovskite-related structures

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that show oxygen nonstoichiometry are potential TCOs because the easy formation of oxygen vacancy is required for an efficient hydration. Sr2Fe1.5Mo0.5O62δ (SFMO) represents the most promising electrode material for SOFCs developed so far because it pairs good catalytic activity with very good oxide and electronic conductivity (MIEC features). In particular, SFMO has been tested in symmetrical cells, showing an excellent activity and stability in both reducing and oxidizing conditions. This feature allows the SFMO-made cathode and anode to function reversely by switching the gases, making it suitable for SOEC/FCs. In a recent joint theoretical and experimental work, it has been shown that SFMO is inherently nonstoichiometric (with δ equal to 0.1 [20]), which turns this MIEC into a good candidate for hydration and subsequent proton conduction.

1.4.1 Enhancing proton conduction in mixed ion-electron conductor materials In principle, it is possible to induce proton conduction in a MIEC material that shows intrinsic nonstoichiometry, for example, SFMO. To this end, A-site doping with larger ions, such as the isovalent Ba21 and the aliovalent K1, has been proposed in order to estimate the conditions under which proton conduction might be enhanced in SFMO [43]. Experimental studies on SFMO-related materials have indicated that both Ba and K can be effectively included in the lattice as dopants [44,45]. The resulting Ba- and K-SFMO derivatives, Ba0.25Sr1.75Fe1.5Mo0.5O62δ (BSFMO) and K0.25Sr1.75Fe1.5Mo0.5O62δ (KSFMO), should lead to larger and more symmetric lattices, which have been proven to be more effective than distorted perovskite for proton transport in the case of BaCeO3 with respect to SrCeO3 [33,35,36]. This size effect can be evaluated by looking at the Goldschmidt tolerance factor of SFMO, BSFMO, and KSFMO, which is defined as follows: rA 1 rO t 5 pffiffiffi 2ðrB 1 rO Þ

(1.10)

where rA and rB are the average ionic radii at the A and B sites, respectively, and rO is the oxygen ionic radius. Ba21 and K1 in 12-fold cubododecahedral environment have ionic radius of 1.61 and 1.64 Å, respectively, both larger than that of Sr21 (1.44 Å). Thus considering that rA has a value of 1.46 Å for Sr(II):Ba(II) 5 7:1 and 1.47 Å for Sr(II):K (I) 5 7:1, rO 5 1.40 Å and rB 5 0:6315 Å for Fe(III):Mo(VI) 5 3:1, one

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obtains tolerance factors closer to unity for Ba- and K-SFMO than for SFMO (tBSFMO 5 0.996; tKSFMO 5 0.997; tSFMO 5 0.988). As stable perovskite structures with cubic symmetry are generally observed when t ranges between 0.95 and 1.04, Ba and K substitutions are expected to bring SFMO closer to the ideal cubic perovskite structure, thus boosting proton conduction. However, when looking at the desired properties for a TCO material, significant differences are found between BSFMO and KSFMO. Electronic structures of hydrated SFMO and BSFMO are qualitatively different from the dry counterparts: both materials likely lose the required electronic conductivity upon full hydration. Only in the case of KSFMO, the full hydrated system still presents the main electronic structure features of the dry material and thus could retain its good electron conduction properties at full proton loading (Fig. 1.9). Aliovalent K substitution increases the p-type character of SFMO, thus bringing a higher concentration of oxygen vacancies, δ values of 0.25, which can double the hydration capabilities of the parent material. The hydration energy is lowered to 21.2 eV [43], which is of the same order

Figure 1.9 PDOS of dry (left panel) and fully hydrated (right panel) SFMO derivatives containing oxygen vacancies (δ 5 0.125 for SFMO and δ 5 0.25 for BSFMO and KSFMO) at the PBE 1 U level of theory with (UJ)Fe 5 4.0 eV. Fe d (purple), Mo d (green), and O p (red) states are shown; the dashed line indicates the position of Fermi energy. PDOS, Projected density of states. Reprinted with permission from A.B. Munoz-Garcıa, P. Michele, First-principles design of new electrodes for protonconducting solid-oxide electrochemical cells: A-site doped Sr2Fe1.5Mo0.5O62δ perovskite, Chem. Mater. 28 (2) (2016) 490500. r2016 American Chemical Society.

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of magnitude than those of common proton-conducting electrolytes (approximately 21.6 eV). For what concerns proton transport properties, the computed migration barrier for SFMO is 0.5 eV, close to those of B-site-doped cerates and zirconates, in BSFMO a significant improvement can be achieved with a barrier of 0.32 eV, but the most promising results is obtained again with KSFMO. The migration barrier for the K-doped material (0.22 eV) lies in the range of proton migration barriers in prototypical undoped PC ceramics. The migration results are grouped in Fig. 1.10. A deep look at the electronic and structural features along the proton migration path is required to understand the rationale behind this trend. In the case of SFMO and BSFMO, the proton migration is coupled to a structural rearrangement of the perovskite TMs and oxide sublattices: the OH moiety is only stable in a distorted configuration where the O points outward in the TMO(H)TM bonds and during the proton transfer path a concerted octahedral rotation must occur to accommodate the forming OH

Figure 1.10 Proton migration features in SFMO derivatives. Energy profiles of the minimum energy path for OH O jumps. Insets: corresponding minima and transition state structures. Turquoise, blue, and orange lines refer to proton transfer in a TM plane framed by two Sr (Sr/Sr), one Ba and one Sr (Ba/Sr), and one K and one Sr (K/Sr) atoms, respectively. TM, Transition metal. Reprinted with permission from A.B. Munoz-Garcıa, P. Michele, First-principles design of new electrodes for protonconducting solid-oxide electrochemical cells: A-site doped Sr2Fe1.5Mo0.5O62δ perovskite, Chem. Mater. 28 (2) (2016) 490500. r2016 American Chemical Society.

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moiety in the desired configuration. The differences between SFMO and BSFMO are due to the larger lattice constants induced by Ba-doping, which allow for an easier passage of the proton. In KSFMO the large size of K1 ion also comes with a p-doping effect that shrinks the FeO average bond lengths (and the related FeO6 octahedron average volume) with respect to BSFMO. The balance between the large A-site cation radius and the TMO octahedron volume allows for the OH moiety to be easily accommodated at the center of the ideal 3Fe/Mo square in both outward- and inward-like configurations. As a consequence, there is no need for octahedral rotation during the proton migration, which ensures a lower energy barrier and a faster proton transport than in SFMO and BSFMO. The importance of having a larger lattice volume to accommodate the moving proton and the OH moieties that are forming along the migration path has been proved by computing such barrier heights for the undoped SFMO at the larger equilibrium lattice constants of BSFMO and KSFMO. Very low migration barriers are obtained again (0.27 eV), thus elucidating how relevant are the structural effects exerted by A-site dopants. Proton transport could be also boost in SFMO by applying a tensile stress, for example, via epitaxial growth of nano-sized SFMO thin layers on appropriate substrates.

1.4.2 Electrocatalysis toward bifunctional oxygen evolution reaction/oxygen reduction reaction catalysts Electrocatalysis at air electrodes is a crucial process in these devices. The sluggish kinetics of the ORR is the main source of potential loss in SOFCs, while in SOECs the slowest process for water splitting is the OER. Thus the development of effective catalysts is key to achieving good performances. A-site doping with large and aliovalent cation can be an alternative path for tuning also the electrocatalytic activity of a perovskite oxide. While the B-site doping only affects the electronic structure, it has been demonstrated that aliovalent doping at the A-site enables convenient electronic and structural properties for TCO bulk conductivity and for surface electrocatalytic activity. K-doped Sr2Fe1.5Mo0.5O62δ (KSFMO) has been proposed as efficient bifunctional air electrode for reversible PC-SOEC/FCs [46]. The catalytic capability of KSFMO for both ORR and OER can be explained by the structural and electronic features of the material. The low overpotentials (ηORR 5 0.54 V, ηOER 5 0.37 V) are due to the presence of highly undercoordinated

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Figure 1.11 Lateral and top views of the relaxed outermost layers after formation of MoVOFe. Color code: Sr (cyan), Fe (purple), Mo (green), and O (red). Reproduced from A.B. Munoz-Garcıa, M. Pavone, K-doped Sr2Fe1.5Mo0.5O62δ predicted as a bifunctional catalyst for air electrodes in proton-conducting solid oxide electrochemical cells, J. Mater. Chem. A 5 (25) (2017) 1273512739 by permission of the Royal Society of Chemistry.

Fe ions adjacent to MoO4 tetrahedron-like moieties that are formed upon oxygen vacancies along MoOFe bonds as a result of the surface reconstruction (Fig. 1.11). These Fe ions present the ideal d occupancy for the ORR catalysis [47] and allow the stabilization of the TOOH intermediates, that are PDS in the OER, by hydrogen bonding to the MoO4 unit. In conclusion the A-site aliovalent doping tunes the electronic features to be optimal for the ORR and lattice expansiondriven surface reconstruction stabilizes the key TOOH intermediate for the OER.

1.5 Conclusions This chapter highlights the effective use of first-principles tools for the rational design of perovskite-based TM oxides for application in innovative energy conversion devices such as SOFC and PC-SOFCs. The many results of ab initio calculations allowed us to analyze four key processes for optimizing oxide and proton bulk diffusion in perovskite oxides. 1. Low oxygen vacancy formation energy is crucial. Oxygen vacant sites are important for both the oxide diffusion and the hydration process to load proton carriers. Electronic structure features upon formation of the defect highlight the importance for an effective delocalization of the extra charge to stabilize the defect. 2. Energy barrier heights and diffusion rates for oxide migration are affected by the chemical environment. Stabilization of the transition state structure is key to achieve low barriers and efficient oxide transport.

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3. Proton migration barrier heights are strongly sensitive to the overall lattice structural features. Distortions from the ideal cubic perovskite lead to higher barrier heights and lower proton jump rates. Large cations at the A-site allow for an effective accommodation of the OH moiety within the perovskite oxide sublattice, minimizing the energy loss due to lattice reorganization along the proton migration barrier. 4. Electrocatalysis toward ORR and OER depends on several complex features, including the electronic structure of catalytic active moiety (e.g., the d occupation of the TM site), the structural reorganization upon formation of surface defects and subsequent stabilization of key reaction intermediates. In conclusion, we strongly believe that quantum-chemical approaches are going to contribute more and more for both the analysis of controversial experimental data and the rational design of functional materials for energy conversion devices. Our work in the next future will pursue these lines and will focus on the electrocatalytic properties of complex functional heterogeneous interfaces.

References [1] A.B. Munoz-Garcıa, A.M. Ritzmann, M. Pavone, J.A. Keith, E.A. Carter, Oxygen transport in perovskite-type solid oxide fuel cell materials: insights from quantum mechanics, Acc. Chem. Res. 47 (11) (2014) 33403348. [2] T. Ishigaki, S. Yamauchi, J. Mizusaki, K. Fueki, H. Tamura, Tracer diffusion coefficient of oxide ions in LaCoO3 single crystal, J. Solid State Chem. 54 (1) (1984) 100107. [3] M. Pavone, A.M. Ritzmann, E.A. Carter, Quantum-mechanics-based design principles for solid oxide fuel cell cathode materials, Energy Environ. Sci. 4 (2011) 49334937. [4] P.M. Raccah, J.B. Goodenough, A localizedelectron to collective electron transition in the system (La, Sr)CoO3, J. Appl. Phys. 39 (2) (1968) 12091210. [5] M.A. Senarıs-Rodrıguez, J.B. Goodenough, Magnetic and transport properties of the system La12xSrxCoO32δ (0 , x # 0.50), J. Solid State Chem. 118 (2) (1995) 323336. [6] J. Arai, K. Ozawa, T. Ishiguro, EPR study of spin-state transition in LaCoO3, J. Magn. Magn. Mater. 226230 (2001) 871873. [7] G. Thornton, B.C. Tofield, A.W. Hewat, A neutron diffraction study of LaCoO3 in the temperature range 4.2 , T , 1248K, J. Solid State Chem. 61 (3) (1986) 301307. [8] K. Asai, P. Gehring, H. Chou, G. Shirane, Temperature-induced magnetism in LaCoO3, Phys. Rev. B 40 (1989) 1098210985. [9] S. Yamaguchi, Y. Okimoto, Y. Tokura, Local lattice distortion during the spin-state transition in LaCoO3, Phys. Rev. B 55 (1997) R8666R8669. [10] P.M. Raccah, J.B. Goodenough, First-order localized-electron collective-electron transition in LaCoO3, Phys. Rev. 155 (1967) 932943.

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[11] A.M. Ritzmann, M. Pavone, A.B. Munoz-Garcıa, J.A. Keith, E.A. Carter, Ab initio DFT 1 U analysis of oxygen transport in LaCoO3: the effect of Co31 magnetic states, J. Mater. Chem. A 2 (2014) 80608074. [12] Q. Liu, X. Dong, G. Xiao, F. Zhao, F. Chen, A novel electrode material for symmetrical SOFCs, Adv. Mater. 22 (48) (2010) 54785482. [13] P. Hohenberg, W. Kohn, Inhomogeneous electron gas, Phys. Rev. 136 (1964) B864B871. [14] W. Kohn, L.J. Sham, Self-consistent equations including exchange and correlation effects, Phys. Rev. 140 (1965) A1133A1138. [15] V.I. Anisimov, J. Zaanen, O.K. Andersen, Band theory and Mott insulators: Hubbard U instead of Stoner I, Phys. Rev. B 44 (1991) 943954. [16] A.M. Ritzmann, A.B. Munoz-Garcıa, M. Pavone, J.A. Keith, E.A. Carter, Ab initio DFT 1 U analysis of oxygen vacancy formation and migration in La12xSrxFeO32δ (x 5 0, 0.25, 0.50), Chem. Mater. 25 (15) (2013) 30113019. [17] M. Abbate, J.C. Fuggle, A. Fujimori, L.H. Tjeng, C.T. Chen, R. Potze, et al., Electronic structure and spin-state transition of LaCoO3, Phys. Rev. B 47 (1993) 1612416130. [18] C. Sun, R. Hui, J. Roller, Cathode materials for solid oxide fuel cells: a review, J. Solid State Electrochem. 14 (7) (2010) 11251144. [19] M. Pavone, A.B. Munoz-Garcıa, A.M. Ritzmann, E.A. Carter, First-principles study of lanthanum strontium manganite: insights into electronic structure and oxygen vacancy formation, J. Phys. Chem. C 118 (25) (2014) 1334613356. [20] A.B. Munoz-Garcıa, D.E. Bugaris, M. Pavone, J.P. Hodges, A. Huq, F. Chen, et al., Unveiling structure-property relationships in Sr2Fe1.5Mo0.5O62δ, an electrode material for symmetric solid oxide fuel cells, J. Am. Chem. Soc. 134 (15) (2012) 68266833. [21] G.H. Vineyard, Frequency factors and isotope effects in solid state rate processes, J. Phys. Chem. Solids 3 (1) (1957) 121127. [22] K.A. Marino, E.A. Carter, First-principles characterization of Ni diffusion kinetics in β-NiAl, Phys. Rev. B 78 (2008) 184105. [23] G. Henkelman, B.P. Uberuaga, H. Jonsson, A climbing image nudged elastic band method for finding saddle points and minimum energy paths, J. Chem. Phys. 113 (22) (2000) 99019904. [24] Y.A. Mastrikov, R. Merkle, E.A. Kotomin, M.M. Kuklja, J. Maier, Formation and migration of oxygen vacancies in La12xSrxCo12yFeyO32δ perovskites: insight from ab initio calculations and comparison with Ba12xSrxCo12yFeyO32δ, Phys. Chem. Chem. Phys. 15 (2013) 911918. [25] T. Ishigaki, S. Yamauchi, K. Kishio, J. Mizusaki, K. Fueki, Diffusion of oxide ion vacancies in perovskite-type oxides, J. Solid State Chem. 73 (1) (1988) 179187. [26] L. Wang, R. Merkle, J. Maier, Surface kinetics and mechanism of oxygen incorporation into Ba12xSrxCoyFe12yO32δ SOFC microelectrodes, J. Electrochem. Soc. 157 (12) (2010) B1802B1808. [27] A.B. Munoz-Garcıa, M. Pavone, A.M. Ritzmann, E.A. Carter, Oxide ion transport in Sr2Fe1.5Mo0.5O62δ, a mixed ion-electron conductor: new insights from first principles modeling, Phys. Chem. Chem. Phys. 15 (2013) 62506259. [28] S. Dalgaard Ebbesen, S. Højgaard Jensen, A. Hauch, M.B. Mogensen, High temperature electrolysis in alkaline cells, solid proton conducting cells, and solid oxide cells, Chem. Rev. 114 (21) (2014) 1069710734. [29] K.D. Kreuer, Proton-conducting oxides, Annu. Rev. Mater. Res. 33 (1) (2003) 333359. [30] L. Malavasi, C.A.J. Fisher, M.S. Islam, Oxide-ion and proton conducting electrolyte materials for clean energy applications: structural and mechanistic features, Chem. Soc. Rev. 39 (2010) 43704387.

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[31] L. Bi, S. Boulfrad, E. Traversa, Steam electrolysis by solid oxide electrolysis cells (SOECs) with proton-conducting oxides, Chem. Soc. Rev. 43 (2014) 82558270. [32] E. Fabbri, D. Pergolesi, E. Traversa, Materials challenges toward proton-conducting oxide fuel cells: a critical review, Chem. Soc. Rev. 39 (2010) 43554369. [33] H. Uchida, N. Maeda, H. Iwahara, Relation between proton and hole conduction in SrCeO3-based solid electrolytes under water-containing atmospheres at high temperatures, Solid State Ionics 11 (2) (1983) 117124. [34] J.A. Dawson, J.A. Miller, I. Tanaka, First-principles insight into the hydration ability and proton conduction of the solid state proton conductor, Y and Sn co-doped BaZrO3, Chem. Mater. 27 (3) (2015) 901908. [35] T. Hibino, K. Mizutani, T. Yajima, H. Iwahara, Evaluation of proton conductivity in SrCeO3, BaCeO3, CaZrO3 and SrZrO3 by temperature programmed desorption method, Solid State Ionics 57 (3) (1992) 303306. [36] H. Iwahara, T. Esaka, H. Uchida, T. Yamauchi, K. Ogaki, High temperature type protonic conductor based on SrCeO3 and its application to the extraction of hydrogen gas, Solid State Ionics 1819 (1986) 10031007. [37] Y. Yamazaki, R. Hernandez-Sanchez, S.M. Haile, High total proton conductivity in large-grained yttrium-doped barium zirconate, Chem. Mater. 21 (13) (2009) 27552762. [38] E. Fabbri, I. Markus, L. Bi, D. Pergolesi, E. Traversa, Tailoring mixed protonelectronic conductivity of BaZrO3 by Y and Pr co-doping for cathode application in protonic SOFCs, Solid State Ionics 202 (1) (2011) 3035. [39] Y.F. Bu, D. Ding, S. Yuxiu Lai, D.-C. Chen, X.-H. Xiong, T. Wei, et al., Evaluation of La0.4Ba0.6Fe0.8Zn0.2O32δ 1 Sm0.2Ce0.8O1.9 as a potential cobalt-free composite cathode for intermediate temperature solid oxide fuel cells, J. Power Sources 275 (2015) 808814. [40] A.B. Munoz-Garcıa, M. Tuccillo, M. Pavone, Computational design of cobalt-free mixed proton-electron conductors for solid oxide electrochemical cells, J. Mater. Chem. A 5 (23) (2017) 1182511833. [41] J.K. Nørskov, J. Rossmeisl, A. Logadottir, L. Lindqvist, J.R. Kitchin, T. Bli-Gaard, et al., Origin of the overpotential for oxygen reduction at a fuel-cell cathode, J. Phys. Chem. B 108 (46) (2004) 1788617892. [42] A.B. Munoz-Garcıa, M. Pavone, From oxide to proton conduction: a quantumchemical perspective on the versatility of Sr2Fe1.5Mo0.5O62δ-based materials, Int. J. Quantum Chem. 116 (21) (2016) 15011506. [43] A.B. Munoz-Garcıa, P. Michele, First-principles design of new electrodes for proton-conducting solid-oxide electrochemical cells: A-site doped Sr2Fe1.5Mo0.5O62δ perovskite, Chem. Mater. 28 (2) (2016) 490500. [44] N. Dai, Z. Wang, T. Jiang, J. Feng, W. Sun, J. Qiao, et al., A new family of barium-doped Sr2Fe1.5Mo0.5O62δ perovskites for application in intermediate temperature solid oxide fuel cells, J. Power Sources 268 (2014) 176182. [45] Y.C. Hu, H.Y. Wang, X.W. Wang, G.L. Song, J. Su, Y.W. Cui, et al., Effects of K doping on structure and magnetic transport properties of Sr22xKxFeMoO6, J. Alloys Compd. 622 (2015) 819823. [46] A.B. Munoz-Garcıa, M. Pavone, K-doped Sr2Fe1.5Mo0.5O62δ predicted as a bifunctional catalyst for air electrodes in proton-conducting solid oxide electrochemical cells, J. Mater. Chem. A 5 (25) (2017) 1273512739. [47] W.T. Hong, M. Risch, K.A. Stoerzinger, A. Grimaud, J. Suntivich, Y. Shao-Horn, Toward the rational design of non-precious transition metal oxides for oxygen electrocatalysis, Energy Environ. Sci. 8 (2015) 14041427.

CHAPTER 2

Solid oxide fuel cell’s interconnectors Sicele Luciana Abreu Gonçalves, Roberta de Carvalho Borges Garcia and Tulio Matencio Department of Chemistry, Federal University of Minas Gerais, Belo Horizonte, Brazil

Contents 2.1 Introduction 2.2 Interconnectors 2.3 Metallic interconnectors 2.3.1 Ferritic stainless steels 2.4 Area-specific resistance 2.5 Protective coatings 2.6 Electrodeposition 2.6.1 Potenciodynamic and potentiostatic electrodeposition 2.6.2 Galvanostatic and pulsed current electrodeposition 2.7 Conclusion Acknowledgment References

27 29 30 31 32 33 36 40 46 50 50 50

2.1 Introduction Solid oxide fuel cells (SOFCs) are energy-generating devices that operate in medium-high-temperature environments with relatively high-energy conversion efficiency, low-pollutant emission, and fuel flexibility compared with other types of fuel cells [13]. In this context, these cells have been developed for a variety of portable and stationary applications, such as power assist devices for trucks and power plants. SOFCs typically operate in a high-temperature range between 700°C and 1000°C, can internally reform fuels such as natural gas and biogas and, combined with a gas turbine, can produce electrical efficiencies of up to 75% [4,5]. A unit cell consists of anode, cathode, and solid electrolyte, and each one can produce low voltage, around 1 V, so that to achieve sufficient energy densities, several units need to be stacked. In the stacking, the Solid Oxide-Based Electrochemical Devices DOI: https://doi.org/10.1016/B978-0-12-818285-7.00002-2

© 2020 Elsevier Inc. All rights reserved.

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Solid Oxide-Based Electrochemical Devices

electrical contact between two adjacent cells is promoted by the interconnectors, which also have the function of separating and distributing fuel and oxidant gases at the electrode [6,7]. The interconnecting material selection depends on the good compatibility of their properties with the other components of the stack and, furthermore, still be economically feasible. Acceptable thermal expansion coefficient (TEC) and area-specific resistance (ASR) values in an SOFC are, for example, between 10.5 and 12.5 3 1026K21 and 0.1 Ω cm2, respectively. However, high working temperatures imply higher costs with compatible materials, resulting in increased manufacturing costs and shortened cell life [1,2,6]. Ceramic materials such as lanthanum chromite (LaCrO3) (TEC 9.5 3 1026K21) have traditionally been used in the manufacture of high-temperature (1000°C) interconnectors of SOFCs [6,8]. However, recent technological advances in the production and design of the batteries allowed the reduction of the working temperature for intermediate ranges between 700°C and 850°C, allowing, under the operating conditions, the application of interconnecting materials that have excellent chemical and mechanical properties with a lower cost [8,9]. As a good alternative, ferritic stainless steels (17%20% Cr) have been extensively studied in the process of manufacturing interconnectors because of their low cost and good mechanical properties compared to the previously used materials [1014]. However, at high temperatures, chromium can form gaseous oxides that migrate to the cathode and gradually reduce cell performance, a phenomenon known as chromium poisoning. As an alternative, the application of protective coatings has been widely studied because it is a simple, efficient, and low-cost method that inhibits cathode poisoning of chromium and maintains a good electrical resistance specific to the interconnectors [7,11,1518]. CoMn-based spinels have been developed as a protective layer that improves the performance of ferritic steels by inhibiting the phenomenon of poisoning and can be obtained by different techniques [19] such as slurry coating [9,20,21], plasma spray [22], electrodeposition [11,2325], and others [2628]. Electrodeposition technique involves deposition of a metal or alloy coating over a conducting surface by electrolysis from a well-formulated electrolyte known as a bath, which can be an aqueous solution of a pure salt or a complex salt type [29,30]. Process parameters, such as current and application potential, and those of the solution, such as pH, concentration, are easily controlled, at a low cost and in little time. The method is

Solid oxide fuel cell’s interconnectors

29

followed by a high-temperature oxidation heat treatment stage for the transformation of the metal alloy into a spurious protective oxide.

2.2 Interconnectors Under the SOFC working conditions, the most important properties to be respected when choosing an interconnecting material are thermal and chemical stability, high electronic conductivity, and TEC compatible with those of the other components of the cell [6,8,31,32]. These requirements, also to a viable and low-cost manufacturing process, limit the group of materials suitable for the function. The most used materials in the interconnectors manufacture are rare earth perovskites, such as lanthanum perovskites (LaCrO3), chromiumnickel alloys, and ferritic stainless steels. Each utilization depends on the operating temperature of the cell to be projected, being from the largest (B1000°C) to the smallest (B700°C), respectively. However, still, no material fills all the requested resources. SOFC’s static applications are at least 40,000 h at working temperature, which can to lead problems such as mechanical deformation, corrosion, and surface displacement, causing a severe impact on cell useful life [33]. The main requirements for electrical interconnectors are [2]: 1. high electrical conductivity (140 S cm21); 2. chemical, dimensional, and structural stability under oxidizing and reducing atmospheres; 3. linear TEC compatible with the cell materials from room temperature to working cell temperature, to avoid mechanical stresses; 4. impermeability to oxygen and hydrogen; 5. high thermal conductivity; 6. low manufacturing costs to enable commercialization. Ceramic materials, such as the perovskites of lanthanum, were widely used as interconnectors during the first years of cells technological development. Stability characteristics at high temperatures and cell-friendly condition have made it the most commonly used material in the last decades. However, the mechanical fragility, high costs, and difficulty modeling make worrying its use in some current projects of planar SOFCs, in which the interconnector, besides promoting the separation of the oxidizing and combustible gases, also acts as mechanical support of the cathode and anode. The development of new manufacturing technologies and new materials has enabled the decrease in the fuel cell temperature from

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Solid Oxide-Based Electrochemical Devices

1000°C to around 800°C or even lower. This reduction made it possible to replace the ceramic materials with the metallic ones, and as a consequence, a new field of exploration and evaluation about the metal’s characteristics as an SOFC interconnection material [3,6,31,34].

2.3 Metallic interconnectors In modern SOFC designs and plans, metallic interconnection is also used as mechanical support for basic units and some features are particularly important in choosing the material for the project [1,34,35]. Regarding ceramic materials, the interconnectors are preferable in five main aspects: 1. Excellent electronic conductors and ionic insulation. 2. Lower cost and greater plasticity during the manufacturing process. 3. Good mechanical strength. 4. Good electrical conductivity. 5. TEC is compatible with other components of the cell. Oxidation resistance is also an essential requirement in the interconnector material selection. Under these requirements, only superalloys based on aluminum, nickel, iron, and chromium are potential candidates [31,36]. Alloys containing chromium or aluminum, when in contact with the corrosive medium usually form Cr2O3 or Al2O3 layers that protect the material against corrosion, a phenomenon known as “passivation.” These layers, typical of the interaction of water with metals or alloys with sufficient levels of oxidizable metals, such as chromium in stainless steels, can provide excellent oxidation resistance, electrical conductivity, and stability at medium-high temperatures, but for a short period of time [3739]. Table 2.1 shows the composition of the leading alloys used as SOFC’s interconnectors. Table 2.1 Chemical composition (mass percentage) of the main metal alloys used as interconnectors [28,31,40]. Fe (%)

Ni (%)

Cr (%)

Mn (%)

Al (%)

Si (%)

W (%)

Mo (%)

AISI 430 Crofer 22 APU

Base Base

 

17 23

0.5 0.6

 

0.52 0.05

 

0.02 

AISI 304 Inconel 601

Base 3

8 Base

18 23

2 0.5

 -

1 0.4

 5

 2

Outros (%)

0.08 Ti 0.06 La  

Solid oxide fuel cell’s interconnectors

31

Nickel-based alloys such as Inconel 601 exhibit excellent oxidation resistance, high electrical conductivity, and thus are potentially acceptable for interconnection requirements; however, a high coefficient of thermal expansion and high cost of nickel make commercial applications more expensive and complicated than the ironchromium alloys [28,36]. Austenitic stainless steels, such as AISI 430, are low-carbon FeCrNi alloys, with chromium ranging from 16% to 20% and a minimum of 8% nickel. They are nonmagnetic, with good mechanical properties, weldability, cold workability, and resistance to corrosion [33]. This steel class can be considered as an alternative for Ni-based alloys but presents high TEC values and high costs when compared to the type of ferritic stainless steels, such as AISI 430 and Crofer 22 APU [14,33,41].

2.3.1 Ferritic stainless steels Since technological advances made possible its application in SOFCs, a variety of stainless steels and alloys based on chromium and nickel have been developed for this purpose. Based on the fact that CrNi and Ni-based alloys are expensive and difficult to manufacture, ferritic stainless steels have become the most studied class to meet the interconnector requirements in SOFCs. Ferritic stainless steels are FeCr alloys with low carbon ( less than 0.08%) and chromium content between 17% and 20%. There may also be additions of low alloying elements ( less than 1%) such as manganese, niobium, titanium, nickel, and molybdenum to improve the oxidation resistance. The Mn addition tends to form a CrMn spinel on the external surface layer and consequently decreases the formation of volatile Cr species. Elements such as molybdenum and tungsten can also be added to match the better TEC of the alloys to those of other fuel cell components. The amount of aluminum and silicon must be kept low to prevent the formation of their insulating oxides, alumina, and silica [4244]. The absence or low addition of nickel gives this family of steel cost competitiveness compared to the austenitic ones, which present nickel in its composition. Thus as a good alternative, ferritic stainless steels have been extensively studied for interconnectors manufacturing process due to their low cost, suitable mechanical properties (TEC 1112.5 3 1026K21), and good plasticity when compared to previously used materials [14,15,37,45,46]. However, at high temperatures, the chromium present in its composition can form gaseous oxides that migrate to cathode and gradually reduce cellular performance, a phenomenon known as chromium poisoning represented by the following equations:

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Solid Oxide-Based Electrochemical Devices

1 3 Cr2 O3ðsÞ 1 O2ðgÞ -CrO3ðgÞ 2 4

(2.i)

1 3 Cr2 O3ðsÞ 1 O2ðgÞ 1 H2 O-CrO2 ðOHÞ2ðgÞ 2 4

(2.ii)

Also, a decrease in Cr concentration at the base alloy promotes a reduction in the chromium oxide protective layer thickness and allows the appearance of an iron oxide layer. The oxidation/spallation phenomena result in a decrease in electrical conductivity and an increase in contact resistance between the cells [6,41,47]. As an alternative to chromium poisoning, several technologies have been studied, including modification of the steel composition [13,14], surface treatments [48], and application of coatings and protective agents [7,15,16,49]. Some commercial ferritic alloys have been specially developed for applications at high temperatures and have shown good results [8,13,14]. Crofer 22 APU (20%24% Cr, 0.03% C, 0.3%0.8% Mn, 0.5% Si, 0.5% Al, 0.2% Ti; 0.2% La) was developed especially for applications in SOFC’s environments [41,50]. The oxide layer formed in this steel is predominantly composed of Cr2O3 spinel oxides and a columnar outer layer (Mn, Cr)2O3. This outer layer presents excellent resistance to corrosion in atmospheres relevant for applications up to 900°C, reducing the evaporation of chromium very effectively. However, the manufacturing process and the presence of noble metals in their composition increase the final cost and, therefore, do not meet the economic viability requirement [7,9]. Though, for the AISI 430 stainless steel, Cr and Mn percentages are low to promote the formation of compounds such as (Mn, Cr)2O3. Therefore for a short time, the AISI 430 steel presents good resistance to corrosion at 800°C and in air atmosphere, but for longer times the corrosion resistance decreases drastically due to the displacement of the oxide film, leaving the exposed to oxidizing gas [51]. As an alternative, the application of protective coatings in ferritic stainless steels has been widely studied as a simple, efficient, and inexpensive method that inhibits the phenomenon of chromium poisoning and maintains a good specific electrical resistance [15,17,20,23,27].

2.4 Area-specific resistance The electrical contact resistances between the interconnectors and the fuel cell electrodes play a crucial role in the good performance of the fuel cell.

Solid oxide fuel cell’s interconnectors

33

When a fuel cell is supplying current, its working potential can be expressed by the following equation [52]: E 5 Eocp 2 EΩ 2 Eact 2 Econ 2 Ecro

(2.1)

where EOCP is the open circuit potential of the fuel cell; E is the potential loss related to the polarization resulting from the electrical resistances present in the elements of the fuel cell; Eact is the potential loss due to the activation polarization resulting from the constraint imposed by the rate of charge transfer; Econ is the potential loss established by the concentration polarization resulting from the depletion of the fuel and the oxidant at the anode/electrolyte and cathode/electrolyte interfaces, respectively; and Ecro is the potential loss due to fuel crossover. The potential for ohmic loss E is related to the current i and the ASR by the following equation: EΩ 5 iUASR

(2.2)

ASR takes into account all electrical resistances of the fuel cell. The main contributions are due to the electrolyte, the electrodes, the electrode/electrolyte interfaces, and the sum of the electrical contact resistances between the interconnectors and the electrodes, ASRcon. The oxide layers that form on the surface of the interconnectors are responsible for ASRcon. The experimental determination of ASRcon can be performed by electrical measurements through a two-point, four-wire probe approach or by electrochemical impedance spectroscopy. Currently, the maximum acceptable value for ASRcon is 0.1 Ω cm2 [53].

2.5 Protective coatings The basic requirements for an efficient protective coating are as follows [26]: 1. Function as a barrier against chromium volatility/cathode poisoning. 2. Prevent the critical oxidation of the support metal. 3. Maintain low electrical resistance and oxidation. Studies such as Larring and Norby [54] have begun the first indications that the spinel (Mn, Co)3O4 could act as a promising barrier to the volatility of chromium in ferritic steel. Recently, several authors have studied spinel coatings with nominal composition Mn1.5Co1.5O4 and presented satisfactory results regarding the inhibition of chromium diffusion and oxidation resistance at high temperatures [18,22,5557]. Some methods can

34

Solid Oxide-Based Electrochemical Devices

be used to obtain spinel coatings such as slurry coating [20], plasma spraying [58], and electrodeposition [57,5961]. Electrodeposition followed by oxidation at medium-high temperatures has been extensively studied, and the results show an efficient and low-cost method. Pinto et al. [59] studied the initial stages of the transformation of CoMn metal alloys into spinel phases during oxidation at temperatures of 600°C, 700°C, and 800°C. The Co and Mn metal layers were sequentially electrodeposited onto AISI 430 stainless steel substrate from cobalt and manganese acid sulfate solutions. The metal deposits showed a thickness above 20 μm. The oxidation was performed for 1 h and the coatings obtained were composed of layers of unreacted metal elements and Mnbased oxides. The spinel phase was studied by X-ray diffraction (XRD) and revealed a tetragonal structure based on (Mn3O4) and Co in a solid solution and undetermined Co/Mn ratio. The complete conversion was not obtained in that time interval as indicated by the presence of primary manganese oxides (MnO and Mn2O3) and metallic cobalt. Jia et al. [11] evaluate the high-temperature corrosion resistance of AISI 430 ferritic stainless steel coated with MnCo alloys as a possible material for SOFC’s application. The samples were exposed to oxidation in humidified air for 1250 h at 800°C. A thick cubic layer of MnCoFe spinel is formed on the surface, showing a significant effect on reducing corrosion compared to uncoated samples. For the experiment, samples of AISI 430 20 3 20 mm2 were sandwiched and washed with MnCo alloy and subjected to a preheat treatment at 800°C for 2 h, indicating that this time was sufficient for transformation of the metallic coating on a dense and homogenous spinel. During the oxidation heat treatment, the samples were periodically removed from the furnace and weighed for subsequent observation of the kinetics of corrosion related to the mass gain. In the case of the authors, the experiment showed results of up to 0.21 mg for coated samples after 1250 h of oxidation, while uncoated samples obtained a gain of 0.51 mg on average. The MnCo spinel coatings reduced the corrosion rate by a factor of 4, showing great effect in increasing the corrosion efficiency of the steel. For quantitative analysis, the kinetics of corrosion related to mass gain is expressed by Wagner’s parabolic law, described in 1933, shown in the following equation:  2 Δm 5 kp t (2.3) A

Solid oxide fuel cell’s interconnectors

35

where Δm is the mass gain of the sample (g); A is the sample surface area (cm2); kp is the parabolic corrosion constant (g2 cm24 s21); and t is the oxidation time (s). This law describes the parabolic growth of oxides, sulfides, and other compounds. When the thickness growth of the oxide film on the metal surface (diffusion-controlled) develops as a square root of the time function, the film growth kinetics have a parabolic dependence on the oxidation time. Parabolic oxidation is characteristic of metals whose ratio between the volumes of oxide formed and metal consumed is higher than1, that is, those which form mediocre porous protective films. The thickness of this film does not increase significantly with the time since the presence of the oxide hinders ionic and electronic diffusion [62]. Still on the research of Jia et al. [11], after the oxidation tests, the microstructures of the samples were analyzed by X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS). The XRD spectra indicated that to uncoated samples only the signal of the FeCr alloy at the initial stage of 2 h, while the spinel and chromium oxide signals were detected for the long oxidation time process. For samples coated with MnCo, no spinel signal was available at the initial stage; only Mn and Co metal signals were found, and the FeCr peak was also apparent. After initial oxidation, the Mn and Co metal signals almost disappeared while the cubic spinel structure was detected. Its peak intensity increased over time to 250 h and was stable from that time. The authors draw attention to the fact that in comparison with previous references, the position of the spinel spikes formed was shifted to 2-degree (2θ) lower angles. As exemplified above, the MnCo alloy has been extensively studied at room temperature as a mixture of the tetragonal and cubic phase. For the spinel compositions Mn2CoO4 and MnCo2O4, the stable structures at room temperature are tetragonal and cubic, respectively. With the increase in temperature, around 400°C, the tetragonal spinel phase becomes unstable and becomes the cubic spinel phase [11,20,23,63]. Once the grid parameters, atomic coordinates, position, and intensity of the peaks have been determined, there are databases of the known diffraction pattern, and, in the first analysis, a simple search and matching operation of the most intense diffraction data peaks collected is usually performed. These standards are made from dust samples and are compiled into the databases by mathematical calculations [64]. Therefore if data are collected from a sample showing preferential orientation, as is common in

36

Solid Oxide-Based Electrochemical Devices

Figure 2.1 Crystallographic charts for the CoMn2O3, MnCo2O3, and Co3O4 phases provided by Crystallographica Search Match software.

thin films, the peak positions will match, but the intensities may be quite different, and, where the film consists of a mixture of phases, and quantification is desired, this requires special care. Thus the phase boundaries between tetragonal and cubic MnCo spinel are, unfortunately, still not well determined (Fig. 2.1). Also, this spinel has slow diffusion kinetics and difficulty in sintering dense samples. Therefore the phase information obtained in the XRD spectra of the authors samples probably reflects the imbalance phases at room temperature, at which the analyses are performed. No chromium signal was detected from XRD measurements of coated samples, indicating that the spinel layer is probably quite thick and prevented the underlying chromium scale from being caught in this type of analysis. Thus the coating of ferritic stainless steels such spinel coatings have been widely studied as an alternative to improve their corrosion resistance properties under the SOFC working conditions. The protective layers can be obtained by a low-cost and straightforward electrodeposition technique, combining different parameters, such as pH, electrolytic concentration, and the current/potential applied during the process. The electrodeposition techniques to obtain films and the influence of some settings in the process will be better addressed in the next section.

2.6 Electrodeposition Electrodeposition of metals stands out among other methods to obtaining protective coatings by advantages such as fast deposition rate, good costeffectiveness, and simplicity of control in the thickness of the films. The technique involves depositing a metal coating or alloy on a conductive

Solid oxide fuel cell’s interconnectors

37

surface by electrolysis of a well-formulated bath, known as an electrolyte, which may be an aqueous solution of a single salt or a complex salt type [65]. The principles underlying the electrodeposition method, centered on Faraday’s original idea, to electrolyze a metal salt to reduce the metal on the cathode. An electrolysis circuit consists of an anode, cathode, electrolyte, and a current collector. Reduction and oxidation reactions occur at the cathode and anode, respectively, due to metal ions and electrons that can cross the electrode-electrolyte interface. The cathode is the conducting substrate on which deposition must occur; the anode may be a soluble or inert material. The overall reactions that occur during electrolysis can be represented in the following equations: Mz1 1 ne2 -M

(2.iii)

M-Mz1 1 ne2

(2.iv)

In simple salt solutions, metallic ions are present as hydrated ions and are represented as M(H2O)xz1, where x is the number of water molecules in the primary hydration process [29]. The electrochemical metallic films growth occurs in a vessel where cathode and anode are immersed in the electrolyte; each one of the electrodes must be in contact with the same external source of electric energy. The electrodeposition occurs by the application of a current/potential through the solution between the two electrodes, resulting in the growth of the film in the negatively polarized electrode, where the process of reduction of the metal ions occurs. An oxidation process must occur at the anode to close the circuit. The reaction may be the anode dissolution or the electrolyte components oxidation and, in some cases, the water. Laboratory cells use a third electrode to closely monitor and control the potential of the cathode compared to a known reference, called a reference electrode. This electrode ideally holds a constant potential regardless of the magnitude of the current flowing between the anode and the cathode [29,66]. The morphology and properties of the coatings can be easily adjusted by the composition and pH of the electrolytes or by electrochemical parameters modification, such as deposition potential or current density [30,67]. The electrodeposition involves charge transference by anode and cathode process to maintain a balance of charges between these two processes, that is, the amount of anodic charge included in the oxidation process (Qo) must be the same as reduction process (Qr) (Eq. 2.4).

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Solid Oxide-Based Electrochemical Devices

Qo 5 Qr

(2.4)

The electrochemical reaction occurs when the electrons pass through the electric circuit connected to the two electrodes. Under these conditions, the current I (A) becomes a useful measure of the rate of reaction in the cell, while the charge Q (C), which passes over a period t (h), indicates the total amount of reaction that occurred (Eq. 2.5). Q5I  t

(2.5)

Faraday, in 1833, formulated two laws that relate the balance of charge and mass in electrochemical reactions in equilibrium. The first law states that the number of moles N produced or consumed in an electrochemical system should be proportional to the charge flowing through the circuit, Q. The second law states that the mass N of different substances formed by the flow of the same charge is proportional to molar mass divided by the oxidation state of the species, z. In the mathematical form, the two laws can be summarized by the following equation: N5

Q zF

(2.6)

where N is the number of moles of material involved; Q is the charge involved in the reaction (C); z is the number of electrons exchanged; and F is the Faraday constant (B96,485 C mol21). In an electrodeposition process, not all the applied current is used only to electrodeposit the material of interest, a fraction of this current can be used by another redox reaction in parallel, as the reduction of hydrogen. In this way the current efficiency is calculated as the ratio between the anodic charge (Qa) and the cathodic charge (Qc), which are used in the deposition process (Eq. 2.5). These parameters can be obtained by the integration of the plot curves in a current 3 time voltammetric graphs (Fig. 2.2). Freitas and Garcia [68] studied the electrochemical recycling of cathodes of Li-ion batteries of cell phones by the potentiostatic electrodeposition method. The cobalt-rich electrolyte solution is obtained by hydrometallurgical recycling route had its pH adjusted to four values between 5.4 and 1.5. The measurements were performed in potentials of electrodeposition 20.8, 20.9, 21.0, 21.1, and 21.2 V, with charge density equal to 10 C cm22, for all pHs. In the study the authors identified the deposition potentials by a potentiodynamic method, also called

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39

Figure 2.2 Calculation of cathodic and anodic charge integrals by OriginPro 8.0 software.

cyclic voltammetry (CV). The analysis of the cathodic reduction peaks allowed the authors to evaluate that the reduction of cobalt starts at 20.8 V, under the studied conditions. For potentials more negative than 21.1 V, increases in cathodic current density are explained by the hydrogen reduction, which occurs in parallel with the cobalt reduction. In a later study, Freitas et al. [69] showed the dependence of the process of nucleation and growth of the films with the pH of the electrolytic solution. At pH 5 2.7, the films were less porous than at pH 5 5.4. The authors explain the fact by the nucleation model proposed by Scharifker and Hills and prove that for pH 5 2.7 the instantaneous two-dimensional nucleation and growth model, in which the nuclei are formed instantaneously under the substrate and the film presents more homogeneous morphology. At pH 5 5.4, the growth of the film tries to a slow and progressive three-dimensional nucleation mechanism with a small number of active sites, which results in a film with larger and less homogeneous grains. Karpuz et al. [57] investigated the growth of CoMn alloys during electrodeposition to better understand the influence of film thickness, pH and manganese concentration on electrolyte, microstructure, chemical composition, and magnetic properties of the deposited tank. They found that the decrease in pH reduces the size of the surface grains from micro to nanoscale and that for films of different thicknesses, the morphology varied from a ribbed structure to acicular, with the decrease of film

40

Solid Oxide-Based Electrochemical Devices

thickness. The deposition potentials were determined by CV, the potential window between 22.0 and 1.0 V, and a scanning speed of 20 mV s21. For Mn, a 0.1 M MnSO4 electrolytic solution indicated the beginning of manganese electrodeposition at 21.7 V. The potential of 21.9 V was chosen for the electrodeposition of MnCo alloys from a 0.1 M MnSO4 1 0.25 M CoSO4 electrolytic solution. For these conditions, a decrease in pH from 4.7 to 2.6 produces no effect on the increase in the proportion of Mn in the deposit (0.5%m m21 of Mn and 99.9%m m21 of Co). However, the authors also studied the effect of Mn concentration on the magnetic and morphological properties of deposits. The results showed that all the films obtained considering different amounts of manganese (0.02, 0.03, and 0.06 mol L21) presented the same morphology, but solutions more concentrated in manganese ions reduce the coercivity coefficient (Hc) values on the grains, producing films of high quality and low microstructural tensions. Apelt et al. [24]. related four aspects in a coelectrodeposition process: concentration of Mn3O4 particles in the electrolytic bath (350 g L21 CoSO4  7H2O), agitation, current density, and pH of the solution. With different combinations of the electrodeposition parameters, the amount of Mn3O4 particles incorporated in the coatings varied from 0% to 12% by volume. The results indicated that the pH, followed by the concentration of the electrolytic solution, had a greater influence on both the incorporation of the Mn3O4 particles and the total deposition efficiency, which was significantly reduced at pHs below 2.0. According to the authors, increasing the concentration of Mn3O4 particles in the solution increases the availability of particles to be included in the film. For less concentrated solutions, the incorporation of particles is limited by their supply in the electric double-layer region near the cathode by diffusion or agitation. However, this increase in concentration is limited; for more concentrated solutions the transport of the species becomes controlled by transfer of charge, and a gradual rise in the concentration may, on the contrary, increase the chance of collisions between the particles and harm the incorporation.

2.6.1 Potenciodynamic and potentiostatic electrodeposition In the potentiodynamic technique, also called CV, the variation of the electrode potential is controlled from an initial resting value to a specific more negative potential (direct direction), then to a more positive

Solid oxide fuel cell’s interconnectors

0.08 0.06 0.04 0.02 0.00 –0.02 –0.04 –0.06 –0.08 –0.10

(B)

0.06 0.04 0.02

[Co] = 0.03 [Mn] = 0.01 pH = 2.0 pH = 3.0 pH = 3.5 –2.0 –1.5 –1.0 –0.5 0.0

0.5

1.0

I (A)

I (A)

(A)

41

0.00 –0.02 [Co] = 0.02 [Mn] = 0.02 pH = 2.0 pH = 3.0 pH = 3.5

–0.04 –0.06 –0.08 –0.10

–2.0 –1.5 –1.0 –0.5 0.0

I (A)

(C)

0.5

1.0

E (V)

E (V) 0.02 0.01 0.00 –0.01 –0.02 –0.03 –0.04 –0.05 –0.06 –0.07

[Co] = 0.01 [Mn] = 0.03 pH = 2.0 pH = 3.0 pH = 3.5 –2.0 –1.5 –1.0 –0.5 0.0

0.5

1.0

E (V)

Figure 2.3 Cyclic voltammograms for solutions with different concentrations (mol L21) of cobalt and manganese: (A) [Co] 5 0.03 [Mn] 5 0.02; (B) [Co] 5 0.02 [Mn] 5 0.02; and (C) [Co] 5 0.01 [Mn] 5 0.03.

potential (the reverse direction), and returns to the initial. At the direct direction a negative current, called the cathodic current, is observed, associated with the reduction of the metallic ions. In the reverse direction a positive current, called anodic current, is associated with the oxidation or dissolution of the previously electrodeposited metallic film. The relationship between the cathodic and anodic charge density provides significant information on the charge efficiency of the electrodeposition reaction [70]. Fig. 2.3 shows the scan potential versus time for aqueous solutions containing Co and Mn in different proportions. For these solutions, the charge efficiencies can be calculated by Eq. (2.7) as are shown below: Ð t2 icat´odica dt εð%Þ 5 Ðt1t2 3 100 (2.7) dt ´ t1 ianodica Narrower for the solutions of lower pH, a little gap in the anodic potential, can mean deposits less resistant to the dissolution process. Since in acid pHs the formation of the films happens with intermediate reactions of adsorption of the metallic phases by molecules of hydrogen, the

42

Solid Oxide-Based Electrochemical Devices

Figure 2.4 Charge efficiency for all electrolytic solutions.

crystalline structure can be weaker by including these. For these electrolytic solutions, small increases in manganese proportion allow the formation of more stable phases at pH 5 3.0. However, at this pH, phase stability becomes almost zero for the solution where manganese concentration becomes higher than that of cobalt. The pH 5 3.5 revealed deposits with intermediate stability, which also become less stable with the increase in the manganese proportion. The highest efficiencies, from 25% to 40%, were observed for solutions at pH 5 3.0 (Fig. 2.4). It can be seen that increasing the proportion of manganese in the solution decreases the total charge efficiency of the process, and that value decreases progressively, for all pHs, to the condition in which the ratio of Mn becomes greater than or equal to Co. The pH 5 3.5 showed intermediate efficiencies for higher cobalt concentrations, but it is worth noting that for the solution most concentrated in manganese, this pH was the most efficient, around 8%. At lower pH, the process efficiency does not exceed 13% and becomes even lower for high concentrations of manganese. By potentiostatic technique, the working electrode is polarized through a fixed potential application. In this case, the electrodeposition is controlled by the activation and nucleation energy, and in the first instants, due to the growth of nuclei that results in a significant increase in the electroactive area of the deposit, the current increases from a value io until reaching a maximum value i. After reaching the maximum i, the current decreases due to the growth and coalescence of the nuclei and the consequent decrease of the electroactive area. The current density stabilizes, and the control of the reaction becomes predominant by mass transport or diffusion [67].

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43

Simple mathematical manipulation of Faraday’s law (Eq. 2.8) allows the calculation of the mass efficiency (Em) acquired during electrodeposition as the ratio between the real mass of the process (mr) and the theoretical mass calculated (mt) (Eq. 2.11). N5

Q zF

(2.8)

N5

mt M

(2.9)

mt 5 Q  Em 5

M zF

mr mt

(2.10)

(2.11)

Among different pHs, electrolytes, and electrodeposition potentials, Fig. 2.5 shows the relationship between these parameters in terms of the mass efficiency obtained. This type of investigation may be sufficient to complement the choice of a more efficient electrodeposition potential under the analyzed conditions. For the two solutions less concentrated in manganese, the higher mass efficiency was obtained for deposits with a 21.5 V electrodeposition potential, at pH 3.5 and 3.0, respectively. For the solution with a higher proportion of Mn, the most efficient condition was 21.3 V and pH 5 3.5.

Figure 2.5 Mass efficiency as a function of manganese concentration and of the applied potential and pH of the solution.

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Solid Oxide-Based Electrochemical Devices

Figure 2.6 X-ray diffractograms for the sample of uncoated AISI 430 steel subjected to 800°C for 300 h.

Figure 2.7 Characterization by MEV and EDS for AISI 430 steel sample without coating, after oxidation thermal treatment at 800°C for 300 h.

However, for a more detailed microstructure and chemical behavior understanding, characterization techniques are required. The most widely used today are XRD, SEM, and EDS. The information collection obtained from these analyses allows a more detailed study about homogeneity, chemical composition, and microstructure of the grains formed during the deposit. Figs. 2.7, 2.9 and 2.10 show the chemical composition and microstructural for the uncoated AISI 430 sample and coated samples from the same cobalt/manganese concentration solution, electrodeposited with potential 21.1 V, at pH 5 3.0 and 3.5, respectively. The samples were

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45

Figure 2.8 X-ray diffractograms for the sample electrodeposited at 21.1 V, pHs 3.0 and 3.5 submitted at 800°C for 300 h.

Figure 2.9 Microstructural characterization by SEM and EDS for a sample at pH 5 3.0, 21.1 V, after oxidation thermal treatment at 800°C for 300 h.

subjected to oxidation thermal treatment for 300 h and the complete formation of spinel oxides under both conditions is indicated by X-ray diffractograms (Figs. 2.6 and 2.8). As can be seen, SEM amplified images, coupled with semiquantitative EDS data, show the superficial coatings chemical composition and the microstructural heterogeneities. These results are essential in the characterization of a dense, resistant, homogeneous deposit well adhered to the substrate.

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Solid Oxide-Based Electrochemical Devices

Figure 2.10 Microstructural characterization by SEM and EDS for a sample at pH 5 3.5, 21.1 V, after oxidation thermal treatment at 800°C for 300 h.

2.6.2 Galvanostatic and pulsed current electrodeposition In the galvanostatic electrodeposition method, the current flowing between the working electrode and the counter electrode is kept constant. In the first instants, the potential tends to change rapidly due to the charge of the double electric layer until it reaches the potential of reducing the metallic ions in solution. When the concentration of the electroactive species near the working electrode becomes close to zero, the potential becomes more negative to compensate for the capacitive effect. The time spent on this phenomenon is called induction time [71]. Fig. 2.11 shows a chronopotentiogram (potential vs. time) obtained in a potentiostatic electrodeposition in 1 M Na2SO4 solution at current densities 25.0, 21.0, 21.5, 22.0, 22.5, and 23.0 mA cm22. The substrate used was AISI 430 steel stabilized to niobium. In pulsed electrodeposition, the current alternates rapidly between two values. It is resulting in a series of pulses of equal amplitude, duration, and polarity, separated by distinct pulses. Each pulse consists of an on time (ton) of applied current and a zero time (toff) of zero current. The pulsed current waveforms can be divided into two groups: unipolar pulses (cathode only) and bipolar pulses (cathode and anodic).

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Figure 2.11 Chronopotentiogram (potential vs time) obtained in a potentiostatic electrodeposition in 1 M Na2SO4 solution at current densities 25.0, 21.0, 21.5, 22.0, 22.5, and 23.0 mA cm22.

In the electrodeposition by pulsed current, four parameters can be varied independently [72]: 1. cathode pulse current density (ic); 2. density of anodic or zero pulse current (ia); 3. cathode pulse duration (ton); and 4. anodic or null pulse duration (toff). where ton is the time during which cathodic current is applied. The time of imposition of the pulse must be sized in such a way that it does not simulate the direct current [72,73]; toff is the interval where there is no current passing, that is, time relaxation of the pulsing layer and recovery of the double layer; ic is the cathodic current applied during the pulse; and period or cycle of work: it is composed of the sum of the “on” time and “off time” used in a process. An essential parameter in the pulsed process is time. The sum of time “on” and “off” composes a period (P, unit second) and the inverse, the frequency ( f, Hertz unit). P 5 ton 1 toff f5

1 1 5 P ton 1 toff

(2.12) (2.13)

48

Solid Oxide-Based Electrochemical Devices

During the period “on” occurs the processes of nucleation and growth of the film. During the “off” time the phenomenon of atomic rearrangement occurs in the crystalline nuclei. The duty cycle or cycle yield is the ratio of the time on and the period (ton 1 toff) applied, which can be calculated as follows in the following equation: γ5

ton  100 ton 1 toff

(2.14)

where γ is the duty cycle; ton is the cathodic current pulse duration; and toff is the duration of the null pulse. The duty cycle can vary from 1% to 100%, with 100% corresponds to the conventional direct current, that is, the galvanostatic, because there is no time off. “On” and “off” times range from microseconds to milliseconds. If the duty cycle is high, it approximates the electrodeposition by direct current. To move away from this behavior, one must work with the least possible work cycle. Values in the order of 33%0% are of practical use and where the best results are obtained. In the case of electrodeposition of precious metals, the duty cycle may vary from 10% to 40%. For particular conditions, such as the generation of nanocrystals, we opt for low cycles of work, usually less than 10% [74]. The average current density (im) is equivalent to the density of current applied to direct current deposition [75]. The average current is expressed as a function of three main parameters, as shown in the following equations: im 5

ic  ton ton  toff

(2.15)

Or im 5 ic  γ

(2.16)

where im is the average current density; ic is the cathodic current density; ton is the cathodic current pulse duration; toff is the duration of the null pulse; and γ is the duty cycle. In Figs. 2.12 and 2.13 we have examples of waveforms applied in the frequencies of 10 and 1 Hz, respectively, and duty cycles (A) 10%, (B) 33%, and (C) 50%. The electrodeposition by pulsed current has been replacing, in many cases, the electrodeposition by the direct current that through this technique it is possible to obtain a reduction of the consumption mainly of

49

Solid oxide fuel cell’s interconnectors

...

ton 0.050s

toff 0.050s

(C)

...

j (mA.cm–2)

ton 0.033s

toff 0.067s

(B)

...

ton 0.01s

toff 0.09s

(A)

–0.02 0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

t (s)

Figure 2.12 Waveforms applied in the frequencies of 10 Hz and duty cycles (A) 10%, (B) 33%, and (C) 50%.

...

ton 0.50s

toff 0.50s

j (mA.cm–2)

(C)

...

ton 0.33s

(B)

toff 0.67s

...

ton 0.1s

toff 0.9s

(A)

–0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

t (s)

Figure 2.13 Waveforms applied in the frequencies of 1 Hz and duty cycles (A) 10%, (B) 33%, and (C) 50%.

additives, reduction of the consumption of electrical energy, and production of coatings of better quality. These factors are in line with the new guidelines of the metal/ mechanics industries worldwide, as they reduce production costs, improve product quality, and contribute to making production processes more

50

Solid Oxide-Based Electrochemical Devices

environmentally sound. The metals deposited by pulsed current have a lower amount of hydrogen adsorbed to the surface, reducing the internal stress of the coatings when compared to those obtained by direct current [76].

2.7 Conclusion Protective coated layers as a barrier to the chromium volatility in metallic interconnectors have been extensively studied for medium-high temperatures applications in SOFCs. A good choice, in terms of chemical and physical compatible properties, are Co-based and CoMn spinels. These coatings can be obtained easily and inexpensively by electrodeposition. This technique involves several methods, and the characteristics of the deposits can be optimized by varying the appropriate parameters to each one.

Acknowledgment The authors wish to thank CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior); CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico); and FAPEMIG (Fundação de Amparo a Pesquisa do Estado de Minas Gerais) for their financial support. Also wish to thank the Microscopy Center of the Federal University of Minas Gerais for the technical support.

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[6] L. Niewolak, F. Tietz, W.J. Quadakkers, Interconnects. High-Temperature Solid Oxide Fuel Cells for the 21st Century, Elsevier, 2016. Available from: http://doi. org/10.1016/B978-0-12-410453-2.00007-5. [7] M. Bednarz, et al., High-temperature oxidation of the Crofer 22 H ferritic steel with Mn1.45Co1.45Fe0.1O4 and Mn1.5Co1.5O4 spinel coatings under thermal cycling conditions and its properties, Mater. Chem. Phys. 225 (2019) 227238. [8] N. Mahato, A. Banerjee, A. Gupta, S. Omar, K. Balani, Progress in material selection for solid oxide fuel cell technology: a review, Prog. Mater. Sci. 72 (2015) 141337. [9] Z. Yang, K.S. Weil, D.M. Paxton, J.W. Stevenson, Selection and evaluation of heat-resistant alloys for SOFC interconnect applications, J. Electrochem. Soc. 150 (2003) A1188A1201. [10] K. Föger, in: M. Gasik (Ed.), Materials Basics for Fuel Cells, Woodhead Publishing Limited, 2008, pp. 663. Available from: http://doi.org/10.1533/ 9781845694838.6. [11] C. Jia, et al., High temperature oxidation behavior of SUS430 SOFC interconnects with Mn-Co spinel coating in air, J. Alloys Compd. 787 (2019) 13271335. [12] Å. Kvick, X-ray diffraction, materials science applications, in: J.C. Lindon, D.W. Koppenaal, G.E. Tranter (Eds.), Encyclopedia of Spectroscopy and Spectrometry, Elsevier, 2017, pp. 648655. Available from: http://doi.org/10.1016/B978-0-12803224-4.00198-9. [13] K.H. Jo, J.H. Kim, K.M. Kim, I. Lee, S. Kim, Development of a new cost effective FeCr ferritic stainless steel for SOFC interconnect, Int. J. Hydrogen Energy 40 (2015) 95239529. [14] C. Hsu, A. Yeh, W. Shong, C. Liu, Development of advanced metallic alloys for solid oxide fuel cell interconnector application, J. Alloys Compd. 656 (2016) 903911. [15] Z. Sun, et al., CuMn1.8O4 protective coatings on metallic interconnects for prevention of Cr-poisoning in solid oxide fuel cells, J. Power Sources 378 (2018) 125133. [16] E. Stefan, et al., Spinel-based coatings for metal supported solid oxide fuel cells, Mater. Res. Bull. 89 (2017) 232244. [17] N.V. Demeneva, O.V. Kononenko, D.V. Matveev, V.V. Kharton, S.I. Bredikhin, Composition-gradient protective coatings for solid oxide fuel cell interconnectors, Mater. Lett. 240 (2019) 201204. [18] B. Talic, P.V. Hendriksen, K. Wiik, H.L. Lein, Thermal expansion and electrical conductivity of Fe and Cu doped MnCo2O4 spinel, Solid State Ionics 326 (2018) 9099. [19] J.C.W. Mah, A. Muchtar, M.R. Somalu, M.J. Ghazali, Metallic interconnects for solid oxide fuel cell: a review on protective coating and deposition techniques, Int. J. Hydrogen Energy 42 (2017) 92199229. [20] Z. Yang, G. Xia, X. Li, J. Stevenson, (Mn, Co)3O4 spinel coatings on ferritic stainless steels for SOFC interconnect applications, Int. J. Hydrogen Energy 32 (2007) 36483654. [21] N. Hosseini, M.H. Abbasi, F. Karimzadeh, G.M. Choi, Development of Cu1.3Mn1.7O4 spinel coating on ferritic stainless steel for solid oxide fuel cell interconnects, J. Power Sources 273 (2014) 10731083. [22] N. Grünwald, D. Sebold, Y.J. Sohn, N.H. Menzler, R. Vaßen, Self-healing atmospheric plasma sprayed Mn1.0Co1.9Fe0.1O4 protective interconnector coatings for solid oxide fuel cells, J. Power Sources 363 (2017) 185192. [23] S. Molin, et al., Microstructural and electrical characterization of Mn-Co spinel protective coatings for solid oxide cell interconnects, J. Eur. Ceram. Soc. 37 (2017) 47814791.

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[24] S. Apelt, Y. Zhang, J.H. Zhu, C. Leyens, Electrodeposition of CoMn3O4 composite coatings, Surf. Coatings Technol. 280 (2015) 208215. [25] J. Wu, R.S. Gemmen, A. Manivannan, X. Liu, Investigation of Mn/Co coated T441 alloy as SOFC interconnect by on-cell tests, Int. J. Hydrogen Energy 36 (2011) 45254529. [26] M. Stange, et al., Improvement of corrosion properties of porous alloy supports for solid oxide fuel cells, Int. J. Hydrogen Energy 42 (2017) 1248512495. [27] J. Puranen, et al., High temperature oxidation tests for the high velocity solution precursor flame sprayed manganesecobalt oxide spinel protective coatings on SOFC interconnector steel, Int. J. Hydrogen Energy 40 (2015) 62166227. [28] N. Shaigan, W. Qu, D.G. Ivey, W. Chen, A review of recent progress in coatings, surface modifications and alloy developments for solid oxide fuel cell ferritic stainless steel interconnects, J. Power Sources 195 (2010) 15291542. [29] G. Zangari, Fundamentals of electrodeposition, Reference Module in Chemistry, Molecular Sciences and Chemical Engineering, Elsevier Inc., 2017, pp. 141160. Available from: http://doi.org/10.1016/b978-0-12-409547-2.11700-7. [30] D. Sobha Jayakrishnan, Electrodeposition: the versatile technique for nanomaterials, in: V.S. Saji, R. Cook (Eds.), Corrosion Protection and Control Using Nanomaterials, Woodhead Publishing Limited, 2012, pp. 86125. Available from: http://doi.org/10.1533/9780857095800.1.86. [31] K. Huang, J.B. Goodenough, Materials for solid oxide fuel cells (SOFCs), in: M. Gasik (Ed.), Solid Oxide Fuel Cell Technology, Elsevier, 2009, pp. 220268. Available from: http://doi.org/10.1533/9781845696511.220. [32] B.K. Kaushik, M.K. Majumder, Interconnects. Springer Briefs in Applied Sciences and Technology (2015). Available from: https://doi.org/10.1007/978-81-322-20473_1. [33] M. Bianco, M. Linder, Y. Larring, F. Greco, J. Van herle, Lifetime issues for solid oxide fuel cell interconnects, in: N.P. Brandon, P. Boldrin, E. Ruiz-Trejo (Eds.), Solid Oxide Fuel Cell Lifetime and Reliability: Critical Challenges in Fuel Cells, Elsevier Ltd., 2017, pp. 121144. Available from: http://doi.org/10.1016/B978-008-101102-7.00007-6. [34] F. Tietz, H.P. Buchkremer, D. Stöver, Components manufacturing for solid oxide fuel cells, Solid State Ionics 152153 (2002) 373381. [35] B. Lis, Selected aspects of the design and diagnostics of solid oxide fuel cells, E3S Web Conf. 10 (2016) 00128. [36] P. Piccardo, R. Amendola, SOFC’s interconnects materials development, in: Int. Work. Innovations SOFCs, 2009, pp. 189194. [37] P. Piccardo, et al., ASR evaluation of different kinds of coatings on a ferritic stainless steel as SOFC interconnects, Surf. Coatings Technol. 202 (2007) 12211225. [38] S. Fontana, S. Chevalier, G. Caboche, Metallic interconnects for solid oxide fuel cell: performance of reactive element oxide coating during 10, 20 and 30 months exposure, Oxid. Met 78 (2012) 307328. [39] S. Chevalier, G. Bonnet, G. Borchardt, J.C. Colson, J.P. Larpin, Mechanisms involved by reactive elements upon high temperature chromia scale growth, Mater. Sci. Forum 369372 (2009) 327336. [40] M.F. Ashby, Material profiles, Mater. Environ. (2012) 459595. Available from: https://doi.org/10.1016/b978-0-12-385971-6.00015-4. [41] L. Niewolak, E. Wessel, L. Singheiser, W.J. Quadakkers, Potential suitability of ferritic and austenitic steels as interconnect materials for solid oxide fuel cells operating at 600°C, J. Power Sources 195 (2010) 76007608.

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[42] S. Fontana, et al., Metallic interconnects for SOFC: characterisation of corrosion resistance and conductivity evaluation at operating temperature of differently coated alloys, J. Power Sources 171 (2007) 652662. [43] J.E. Hammer, et al., The oxidation of ferritic stainless steels in simulated solid-oxide fuel-cell atmospheres, Oxid. Met. 67 (2007) 138. [44] J.W. Fergus, Metallic interconnects for solid oxide fuel cells, Mater. Sci. Eng. A 397 (2005) 271283. [45] B. Talic, P.V. Hendriksen, K. Wiik, H.L. Lein, Diffusion couple study of the interaction between Cr2O3 and MnCo2O4 doped with Fe and Cu, Solid State Ionics 332 (2019) 1624. [46] J. Wu, X. Liu, Recent development of SOFC metallic interconnect, J. Mater. Sci. Technol. 26 (2010) 293305. [47] J. Li, et al., Investigation of MnCu0.5Co1.5O4 spinel coated SUS430 interconnect alloy for preventing chromium vaporization in intermediate temperature solid oxide fuel cell, Int. J. Hydrogen Energy 42 (2017) 1675216759. [48] A. Yeh, Y. Chen, C. Liu, W. Shong, Development of an advanced bond coat for solid oxide fuel cell interconnector applications, J. Power Sources 296 (2015) 426432. [49] H. Zhang, J. Wu, X. Liu, A. Baker, Studies on elements diffusion of Mn/Co coated ferritic stainless steel for solid oxide fuel cell interconnects application, Int. J. Hydrogen Energy 38 (2013) 50755083. [50] L. Niewolak, F. Tietz, W.J. Quadakkers, F. Ju, 7.1 Introduction, 2016. Available from: http://doi.org/10.1016/B978-0-12-410453-2.00007-5. [51] X. Deng, P. Wei, M.R. Bateni, A. Petric, Cobalt plating of high temperature stainless steel interconnects, J. Power Sources 160 (2006) 12251229. [52] X.-D. Zhou, L.R. Pederson, J.W. Templeton, J.W. Stevenson, Electrochemical performance and stability of the cathode for solid oxide fuel cells, J. Electrochem. Soc. 157 (2010) B220B227. [53] K.-Z. Fung, : Advanced materials for high-temperature solid oxide fuel cells (SOFCs), in: Electrochemical Energy, 2016, 270297. [54] Y. Larring, T. Norby, Spinel and perovskite functional layers between Plansee metallic interconnect (Cr-5 wt% Fe-1 wt% Y[sub 2]O[sub 3]) and ceramic (La[sub 0.85]Sr [sub 0.15])[sub 0.91]MnO[sub 3] cathode materials for solid oxide fuel cells, J. Electrochem. Soc. 147 (2000) 32513256. [55] M.N. Mohd Fairulnizal, B. Vimala, D.N. Rathi, M.N. Mohd Naeem, Atomic absorption spectroscopy for food quality evaluation, in: J. Zhong, X.) Wang (Eds.), Evaluation Technologies for Food Quality, Elsevier Inc, 2019, pp. 145173. Available from: http://doi.org/10.1016/B978-0-12-814217-2.00009-3. [56] J. Wu, Y. Jiang, C. Johnson, X. Liu, DC electrodeposition of MnCo alloys on stainless steels for SOFC interconnect application, J. Power Sources 177 (2008) 376385. [57] A. Karpuz, H. Kockar, M. Alper, Properties of electrodeposited CoMn films: influence of deposition parameters, Appl. Surf. Sci. 358 (2015) 605611. [58] N. Grünwald, et al., Microstructure and phase evolution of atmospheric plasma sprayed Mn-Co-Fe oxide protection layers for solid oxide fuel cells, J. Eur. Ceram. Soc. 39 (2019) 449460. [59] R. Pinto, M.J. Carmezim, M.F. Montemor, Electrodeposition and isothermal aging of Co and Mn layers on stainless steel for interconnectors: Initial stages of spinel phase formation, J. Power Sources 255 (2014) 251259. [60] F. Saeidpour, M. Zandrahimi, H. Ebrahimifar, Evaluation of pulse electroplated cobalt/yttrium oxide composite coating on the Crofer 22 APU stainless steel interconnect, Int. J. Hydrogen Energy 44 (2019) 31573169.

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[61] M. Lekka, Electrochemical deposition of composite coatings, Reference Module in Chemistry, Molecular Sciences and Chemical Engineering, Elsevier, 2016. Available from: http://doi.org/10.1016/b978-0-12-409547-2.11716-0. [62] V. Gentil, Corrosão, LTC Editora S.A., 1996. [63] Y.V. Golikov, S.Y. Tubin, V.P. Barkhatov, V.F. Balakirev, Phase diagrams of the Co-Mn-O system in air, J. Phys. Chem. Solids 46 (1985) 539544. [64] B. Ingham, M.F. Toney, X-ray diffraction for characterizing metallic films, in: K. Barmak, K. Coffey (Eds.), Metallic Films for Electronic, Optical and Magnetic Applications, Woodhead Publishing Limited, 2014, pp. 338. Available from: http://doi.org/10.1533/9780857096296.1.3. [65] F. Liu, Y. Deng, X. Han, W. Hu, C. Zhong, Electrodeposition of metals and alloys from ionic liquids, J. Alloys Compd. 654 (2016) 163170. [66] M. Joulié, R. Laucournet, E. Billy, Hydrometallurgical process for the recovery of high value metals from spent lithium nickel cobalt aluminum oxide based lithiumion batteries, J. Power Sources 247 (2014) 551555. [67] E.M. Garcia, V.F. Lins, T. Matencio, Metallic and oxide electrodeposition, Mod. Surf. Eng. Treat. (2013). Available from: https://doi.org/10.5772/55684. [68] M.B.J.G. Freitas, E.M. Garcia, Electrochemical recycling of cobalt from cathodes of spent lithium-ion batteries, J. Power Sources 171 (2007) 953959. [69] M.B.J.G. Freitas, V.G. Celante, M.K. Pietre, Electrochemical recovery of cobalt and copper from spent Li-ion batteries as multilayer deposits, J. Power Sources 195 (2010) 33093315. [70] A.J. Bard, L.R. Faulkner, Electrochemical methods, fundamentals and applications, J. Chem. Educ. 2001. https://doi.org/10.1021/ed060pa25.1 [71] E.M. Garcia, The electrochemical behavior of cobalt electrodeposits on 430 stainless steel as solid oxide fuel cell interconnect, Surf. Coatings Technol. 235 (2013) 1014. [72] G. Perger, et al., Pulse plating  retrospects and prospect, Metal Finish. 77 (1979) 1719. [73] R. Olson, Applications of pulse plating, Plat. Surf. Finish. 68 (1981) 3839. ISSN 0360-3164. [74] Q.X. Yao, The effects of duty cycle and frequency on the crystal size of pulse-plated gold, Plat. Surf. Finish. 76 (8) (1989) 5253. ISNN0360-3164. [75] T. Pearson, J.K. Dennis, Facts and fiction about pulse plating, Trans. Inst. Metal Finish. 69 (1991) 7579. [76] M.S. Chandrasekar, M. Pushpavanam, Pulse and pulse reverse plating—conceptual, advantages and applications, Electrochim. Acta 53 (2008) 33133322.

CHAPTER 3

In situ photoelectron spectromicroscopy for the investigation of solid oxidebased electrochemical systems Benedetto Bozzini1, Matteo Amati2, Luca Gregoratti2, Francesca Rossi3 and Maya Kiskinova2 1 Departmento of Energy, Politecnico di Milano, Milan, Italy Elettra Sincrotrone Trieste S.C.p.A., Basovizza-Trieste, Italy Department of Innovation Engineering, University of Salento, Lecce, Italy

2 3

Contents 3.1 Introduction 3.2 The soft X-ray scanning photoemission microscope at the ESCA microscopy beamline at Elettra 3.2.1 Operating principle of X-ray photoelectron spectroscopy 3.2.2 Operating principle of SPEM and the experimental setup developed at ESCA microscopy 3.3 Examples of SOFCs SPEM characterization in different configurations and operating conditions 3.3.1 In situ SPEM characterization of the SOFC anodic systems 3.3.2 From in situ SPEM studies on SC-SOFCs to the SPEM characterization of self-driven cells 3.4 Conclusion References

55 57 57 59 67 69 75 87 88

3.1 Introduction Solid oxide fuel cells (SOFCs), together with their reversible counterparts, sometimes denominated solid oxide electrolysis cells (SOECs), are one of the most promising electrochemical technologies in the field of energy conversion and storage. They are efficient and environmentally friendly; however, the low stability of the electrode and electrolyte materials under Solid Oxide-Based Electrochemical Devices DOI: https://doi.org/10.1016/B978-0-12-818285-7.00003-4

© 2020 Elsevier Inc. All rights reserved.

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operation conditions is still an obstacle for large-scale commercialization [1]. Optimization of these devices is extremely challenging because of the inherent complexity of the processes occurring at the thin (submicron length scales) electrode/gas and electrode/electrolyte interfaces under working conditions, such as local morphological and chemical changes of the materials constituting the interface. Bulk techniques, such as X-ray diffraction, X-ray absorption spectroscopy, and fluorescence spectroscopy, can be used to investigate these phenomena; however, they provide incomplete information about the processes occurring specifically at the interface. For this reason, in the last few decades, scientists have been putting a lot of effort in implementing surface-sensitive techniques suitable for investigating electrochemical interfaces at the nanoscale. Chemical information from sample surfaces is usually obtained by performing X-ray photoelectron spectroscopy (XPS): a surface-sensitive technique that can provide quantitative information about elemental composition, chemical state, and electronic state of the elements constituting the sample surface. With the advent of third-generation synchrotron facilities, which provide photon beams with tuneable energy, high brightness, and variable polarization, it has been possible to add imaging capabilities to XPS [2] with a spatial resolution of c. 2030 nm in the full-field mode or 70100 nm in the scanning mode [3,4]. Despite the lower lateral resolution, scanning X-ray photoelectron microscopy (SPEM) is usually preferred because of its flexibility in terms of sample morphology and geometry. Traditional XPS studies are carried out in ultrahigh vacuum (UHV, 1029 mbar) or high vacuum (HV, 1025 mbar) environments, which in principle do not prevent the characterization of electrochemical systems based on solid-state electrodes and electrolytes under in operando conditions [57]. However, for electrochemical studies, ambient pressure is preferable to investigate systems in real operando conditions in different environments. This “pressure gap” [8] was partially overcome with the development of the differentially pumped electron analyzers that nowadays permit XPS analysis at near-ambient pressure (NAP, tens of millibar), in gas and liquid environments, even with conventional (not synchrotron based) instruments [9,10], but it does not allow to achieve sufficient lateral resolution to carry out microscopy. In the last decade the team of the electron spectroscopy for chemical analysis (ESCA) microscopy beamline at Elettra synchrotron facility developed and implemented some technical solutions in order to perform NAP photoemission spectromicroscopy, keeping at the same time the SPEM properties [11,12]. In this chapter,

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after an introduction to XPS and SPEM techniques, we shall review the in situ electrochemical work performed by our group and present the novel instrumental developments aimed at achieving NAP conditions at the sample.

3.2 The soft X-ray scanning photoemission microscope at the ESCA microscopy beamline at Elettra In this section a description of the experimental setup developed at the ESCA microscopy beamline at the Elettra synchrotron facility in Trieste is presented. As a premise an introduction to the operation principle of the X-ray photoemission spectroscopy is laid out, in order to help the general reader in the understanding of the details underlying the SPEM technique and the issues associated with the experimental setup for NAP experiments.

3.2.1 Operating principle of X-ray photoelectron spectroscopy XPS is a technique that exploits the photoelectrons elastically emitted by irradiating a material with an X-ray beam, in order to get quantitative information about the chemical composition, the chemical state and the electronic state of the material. Moreover, since the elastically scattered photoelectrons have a low escape depth (0.52 nm) [13], XPS is an extremely surface-sensitive technique. A scheme illustrating a typical XPS experiment is shown in Fig. 3.1. An XPS spectrum is obtained by measuring both the kinetic energy and the number of the emitted photoelectrons that arrive at the detector, typically through a hemispherical energy analyzer (HEA): since the energy of the impinging beam is known and the kinetic energy is measured, it is possible to obtain the binding energy (BE) of the electrons, that is typical for each element, by considering the conservation of energy; thus: Eb 5 Ep 2 ðEk 1 φÞ

(3.1)

where Ep is the photon energy, Ek the photoelectron kinetic energy, φ is the work function of the spectrometer (an instrumental parameter), and Eb the BE of the electrons. From the analysis of the peaks present in an XPS spectrum, it is possible to obtain several pieces of information about the sample, the most typically sought after of which are listed next. (1) The peak positions (binding energies) identify the elements constituting the surface material and their electronic configuration; in particular,

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Figure 3.1 Scheme of a typical XPS experiment. Starting from the left: a photon beam (X-rays, UV light, laser, or synchrotron radiation) impinges on a sample surface, mounted on a sample manipulator with different degrees of freedom (linear and rotational). The emitted electrons are focused toward an energy analyzer and arrive at the detector.

a shift in the BE for the same element in different conditions suggests a change in the oxidation state. (2) The intensity of a given peak (say, the ith one) is related to the atomic density of the corresponding species (denoted by x) through the following expression [13]: Iix 5 Bσix λix Tix nx

(3.2)

where B is an instrumental factor, σ is the photoabsorption cross section for the considered level, λ is the total electron escape depth for the core-level energy and sample material, T is the transmission coefficient of the electrons through the surface, and n is the atomic density of element x.

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In order to avoid photoelectron energy losses, XPS experiments should be carried out in UHV environments. However, as already mentioned in the introduction, some workers developed experimental setups that enable NAP measurements [10]. In NAP experiments the energy dissipation, due to electron scattering by the gas molecules present in the chamber, must be kept very low. This energy dissipation can be minimized by placing the sample in a high-pressure cell, close to a differentially pumped aperture, behind which the pressure drops significantly (Fig. 3.2A). X-rays reach the sample through an X-ray-transparent window with an area of B1 mm2. In this way the beam is kept under vacuum and both the gas molecules and the electrons can escape from the aperture near the sample. The number of the pressure drop stages behind the aperture is determined by the operation pressure of the sample (Fig. 3.2B and C), while the ultimate pressure is defined by the operative pressure range of the energy analyzer (Fig. 3.2D). In the configuration of Fig. 3.2B, the maximum pressure achievable is B1 mbar. If electrostatic lenses are placed in order to focus the electrons onto the apertures (Fig. 3.2C), then it is possible to achieve a pressure of B10 mbar. In order to reach higher pressures, the sample should be moved closer to the aperture, however, there is a minimum distance at which the sample should be placed, to guarantee homogeneous pressure conditions near the sample surface. Many other instrumental solutions have been implemented to improve the analysis chamber layout and the sample manipulation flexibility, to carry out higher resolution and more sophisticated analyses, but these topics are beyond the scope of this chapter. Readers interested in instrumental technicalities could refer, for example, to Ref. [13] and the reference therein.

3.2.2 Operating principle of SPEM and the experimental setup developed at ESCA microscopy The development of third-generation synchrotron facilities made the upgrade from XPS to X-ray photoelectron microscopy possible. A thirdgeneration synchrotron facility (a schematic drawing is shown in Fig. 3.3) is a synchrotron radiation source able to produce tuneable energy X-ray beams with a very high brilliance, that is, the ratio between the spectral flux and its geometrical distribution, determining the smallest spot into which a beam can ideally be focused [14]. The radiation generated is exploited in the beamlines, where the experimental setups are assembled.

Figure 3.2 (A) Schematic drawing of the operating principle of HP-XPS. (B) 1 mbar HP-XPS setup with the different pressure stages. (C) 10 mbar HP-XPS setup with differentially pumped electrostatic lens system. (D) The complete system with the hemispherical analyzer (Phoibos 150, Specs GmbH, Berlin) of the HP-XPS instruments at ALS Beamline 11.0.2 and BESSY. high-pressure X-ray photoelectron spectroscopy (HP-XPS) Reproduced with permission from H. Bluhm, M. Hävecker, A. Knop-Gericke, M. Kiskinova, R. Schlögl, M. Salmeron, In situ X-ray photoelectron studies of gassolid interfaces at near- ambient conditions, MRS Bull. 32 (2007) 10221030. https://doi.org/10.1557/ mrs2007.211. r2007 Materials Research Society.

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Figure 3.3 A schematic drawing of the main components of a third-generation synchrotron. Electrons are generated from a source and accelerated in the LINAC. Then they are further accelerated in the booster ring and injected in the storage ring, where they are driven in a closed path by using bending magnets. The beamlines exploit the radiation emitted from the insertion devices and the bending magnets, in order to carry out experiments. The energy lost by the emitted electrons is replenished by a RF supply. LINAC, linear accelerator; RF, radio frequency.

A general SPEM setup is shown in Fig. 3.4. The undulator is a device, placed in a straight section of the ring (hence the alternative name “insertion device”) that forces the electrons to undergo oscillations in order to produce a very intense and concentrated radiation beam, with a spectrum characterized by narrow energy bands. Photons from the undulator are transported by appropriate optics to the monochromator, which selects the photons with the energy of interest. The SPEM instrument is formed by the focusing optics that form a spot on the sample, that is raster-scanned across it, and by a HEA equipped with a detector that collects the emitted photoelectrons. With this configuration a spatial resolution down to c. 100 nm can be reached, whence high-resolution microscopy can be performed. At the ESCA microscopy beamline, Fresnel zone plates (FZP) are

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Figure 3.4 Scheme of the elements constituting a general SPEM beamline: from the left, an undulator generates the X-ray beam, which is carried toward the monochromator by dedicated optics and focused on the sample by appropriate optics. The emitted electrons are energy selected by the HEA and finally collected by a detector (not shown). HEA, Hemispherical energy analyzer; SPEM, scanning X-ray photoelectron microscopy.

used as focusing optics (see Fig. 3.5A). FZPs are diffractive lenses consisting of a set of radially symmetric rings made of alternating opaque and transparent materials [15]. These lenses are characterized by the typical optical parameters of lenses: the focal length f, the diameter D, and the numerical aperture NA, which depend on the light wavelength λ, the total number of zones N, and the outer zone width Δr (see Eqs. 3.33.4 and Fig. 3.5B). In the following discussion, we will only consider the relationships between the FZP parameters and the first diffractive order, because it is the one most commonly used in SPEM experiments. For this reason the focusing stage is usually equipped also with a central stop and order sorting aperture, in order to cut the undesired orders (see Fig. 3.5C). From geometrical considerations, detailed, for example, in Ref. [15], one can obtain the following relationships: f 

4N ðΔr Þ2 4N ðΔr Þ2  EðeVÞ λ 1240 NA 

λ 1240  2Δr 2ΔrEðeVÞ

(3.3)

(3.4)

It is possible to demonstrate that FZPs obey the visible lens rule 1=f 5 1=p 1 1=q, where p is the source distance and q is the image width. The spatial resolution for a FZP is defined by the Rayleigh criterion ΔrRayl: 5 1:22Δr, and it is also influenced by chromatic aberration that can be avoided if E=ΔE $ N [15]. Then the depth of focus (DOF)—which is

Figure 3.5 (A) SEM image of a Fresnel zone-plate used in soft X-ray microscopy. (B) Scheme of a zone plate with plane-wave illumination and selection of first diffractive order, together with the different parameters characterizing the FZP (see text for details). (C) Scheme of a complete SPEM focusing system. FZP, Fresnel zone plates; SPEM, scanning X-ray photoelectron microscopy. Elaborated with permission from the sources mentioned below. Panel (A) O. Wilhelmi, S. Reyntjiens, C. Mitterbauer, L. Roussel, D.J. Stokes, D.H.W. Hubert, Rapid prototyping of nanostructured materials with focused ion beam, Jpn. J. Appl. Phys.47 (2008) 50105014. r2008 The Japan Society of Applied Physics. Panel (B) J. Pourahmadazar, T.A. Denidni, Toward millimeter-wavelength: transmission-mode Fresnel-zone plate lens anteas using platic material porosity control in homogeneous medium, Sci. Rep. 8 (2018) 5300 (14 pages). This article is available under the Creative Commons CC-BY-NC-SA license. http://creativecommons.org/licenses/by/4.0/. Panel (C) Reprinted from R. Heine, T. Gorniak, T. Nisius, C. Christophis, M.E. Pettitt, F. Staier, T. Wilhein, S. Rehbein, M. Grunze, A. Rosenhahn, Digital in-line X-ray holography with zone plates, Ultramicroscopy 111 (2011) 11311136. r 2011 Elsevier B.V. with permission from Elsevier.

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the permitted displacement away from the focal or image plane, for which the image resolution is only slightly degraded—can be described by [15]: DOF 5 6

λ 2ðΔr Þ2 5 6 λ 2ðNAÞ2

(3.5)

The value obtained from Eq. (3.5) defines the region of a thick sample that is in focus. The FZPs used at ESCA microscopy have diameters ranging from 200 to 250 μm and a minimum outermost zone width of 50 nm, which allows to achieve a spot diameter of B130 nm [8]. The focal distances, depending on the photon energy used (see Eq. 3.3), range from 4 to 15 mm: for this reason, when scanning the photon energy, it is necessary to move the sample, in order to keep a constant spot size [16]. Due to these short focal distances, it is now clearer why it is not convenient to equip the SPEM setup with the differentially pumped system developed for NAP-XPS illustrated in the previous section. In general, a SPEM can operate in two modes: imaging spectromicroscopy and microspot spectroscopy. In the imaging mode, photoelectrons, with a selected kinetic energy window, are collected in order to obtain elemental maps while scanning the sample with respect to the microprobe. In this way, it is possible to obtain simultaneously information about the concentration and the distribution of the chemical states of a selected element. The microspot mode is essentially a local XPS measurement in a microspot area selected within an image. These two operating modes are in principle independent, and this allows their separated optimization, in view of the required spectral and lateral resolution and acquisition time. The complete UHV/HV-SPEM setup developed at the ESCA microscopy beamline is illustrated in Fig. 3.6 [8]. The zone plate focuses the normally impinging X-ray beam on the sample, which is raster scanned in the xy directions with respect to the X-ray micropobe through a fine Piezo stage. The photoelectrons are collected and energy selected by an HEA, equipped with a 48-channel detector, and their take-off angle is fixed at 30 degrees, in order to enhance surface sensitivity. This setup performs core-level spectroscopy, working in the 4001200 eV photon energy range. The sample temperature can be varied between 150 and 1300K and electrical biases of several volts can be applied, in order to perform electrochemical studies [16]. With a conventional analysis chamber, the highest allowable pressure, in case of experiments in which gases are needed, is 1025 mbar.

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Figure 3.6 Schematic drawing of the UHV/HV-SPEM instrument installed at the ESCA microscopy beamline: the X-ray beam is focused on the sample, which is scanned in the xy directions with respect to the beam. The emitted photoelectrons are selected by the HEA and detected by a multichannel detector (not shown). HEA, Hemispherical energy analyzer; HV-SPEM, high vacuum-scanning X-ray photoelectron microscopy; UHV, ultrahigh vacuum. Reproduced from B. Bozzini, D. Kuscer, M. Amati, L. Gregoratti, P. Zeller, T. Dobrovolska, I. Krastev, Spatially resolved XPS characterization of electrochemical surfaces, Surfaces 2 (2019) 295314. This article is available under the Creative Commons CC-BY-NC-SA license. http://creativecommons.org/licenses/by/4.0/.

As mentioned previously, it is not possible to transfer the conventional NAP-XPS technology to SPEM. For this reason the team of ESCA microscopy developed two novel solutions for in operando NAP experiments: the dynamic high pressure (DHP) setup and the NAP cell [8]. The DHP exploits a highly collimated pulsed gas jet that points to the sample surface in order to achieve high local pressure on the sample surface while maintaining the chamber within a pressure of 1025 mbar. The DHP setup is shown in Fig. 3.7: the gas jet is produced with a thin needle, placed at a distance of 2 mm from the surface and connected to a pulsed valve. The pressure in the DHP gas line is set to 3.5 mbar, while the valve aperture time is set to 3.2 ms, with a pulse frequency of 0.35 Hz. In this configuration the sample surface experiences a gas pressure of B10 mbar, that is, NAP conditions (see Fig. 3.8A), while the SPEM chamber remains below the 1025 mbar pressure limit (see Fig. 3.8B). Thus with this setup, it is possible to perform NAP-SPEM experiments at the sample surface without changing the fundamental structure of the UHV/HV-SPEM chamber, nevertheless, it is not possible to perform experiments with continuous gas injection, because the background pressure would exceed the HV pressure limit. Further details are provided in Ref. [12]. In order to perform NAP-SPEM experiments with a constant pressure environment, the NAP cell has been developed [8,16]. A cross-sectional

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Figure 3.7 Sketch of the DHP setup developed at the ESCA microscopy beamline: a needle connected to a pulsed valve is located inside the UHVHV chamber described in Fig. 3.6 and allows the generation of gas jets toward the sample surface. DHP, Dynamic high pressure; HV, high vacuum; UHV, ultrahigh vacuum.

Figure 3.8 (A) Time profile of the pressure at the sample surface for a single pressure shot at a valve aperture of 3.2 ms. (B) Corresponding time profile of the pressure inside the chamber. Reproduced from B. Bozzini, D. Kuscer, M. Amati, L. Gregoratti, P. Zeller, T. Dobrovolska, I. Krastev, Spatially resolved XPS characterization of electrochemical surfaces, Surfaces 2 (2019) 295314. This article is available under the Creative Commons CC-BY-NC-SA license. http://creativecommons.org/licenses/by/4.0/.

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Figure 3.9 (A) Scheme of the NAP cell developed by the team of ESCA microscopy: the X-ray beam impinges normally on the photon-in pinhole of the sample holder and photoelectrons are emitted through an electrons-out nozzle, pointing toward the HEA. The gases are supplied by a metallic bellows through the gas inlet port. (B) Real NAP cell. HEA, Hemispherical energy analyzer; NAP, near-ambient pressure.

scheme of the cell is shown in Fig. 3.9A, together with an image of the real device (Fig. 3.9B). The sample is encapsulated inside a small vacuumsealed cell that is provided with two small (400 μm diameter) pinholes as photon-in/photon-out apertures: the photon-in pinhole is normal to the impinging beam, while the photon-out laterally extends in a conical shape pointing toward the HEA, complying with the acceptance angle of the HEA. The small width of these pinholes controls a very weak gas leak, ensuring a NAP (B0.1 mbar) environment inside the cell; moreover, the dimension of the photon-in pinhole also defines the accessible window on the sample. The reactive gases are delivered into the cell through a flexible metal bellows connected to the dosing line hosted inside the SPEM chamber. The cell can be heated from the back by an encapsulated heater up to 900K950K, and electric contacts are available for biasing the sample during electrochemical experiments. During the SPEM experiment the cell is scanned with respect to the X-ray beam as for conventional UHV-HV experiments. This experimental setup is unique, and it is the only one available at the moment to carry out in operando NAPSPEM experiments.

3.3 Examples of SOFCs SPEM characterization in different configurations and operating conditions In this section, we report a representative selection of studies on the SPEM characterization of SOFCs in different configurations and operating

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conditions, demonstrating the unique capability of this technique to follow the in situ changes in the morphology, composition, and overvoltage profiles of SOFC constituents. Since a traditional SOFC cannot be implemented in a SPEM setup because of absorption and current-density distribution issues, we developed an electrolyte-supported planar cell (see Fig. 3.10A), in which both cathode and anode are assembled on the same side of the solid electrolyte, with thicknesses conveniently chosen to optimize the X-ray absorption. A schematic drawing of the complete SPEM setup in this configuration is shown in Fig. 3.10B. In particular, the following cell configurations can be conveniently implemented: (1) half-cells—with an auxiliary electrode that is not analyzed during the experiment; (2) symmetric cells—with the same electrodic material for both anode and cathode; and (3) single chamber—with both fuel and oxidant supplied in a single gas flow.

Figure 3.10 (A) Scheme of an electrolyte-supported planar cell: (top image, from the bottom) a 1 mm thick and 10 mm wide YSZ support, upon which two 50 nm thick electrodes lie, together with two 50 nm thick interconnects. In the bottom image, we show a more detailed scheme and a picture of the current feeder employed on the cell electrodes. (B) Scheme of the SPEM setup operating with an electrolytesupported planar cell. SPEM, Scanning X-ray photoelectron microscopy. Panel (A): reprinted by permission from Nature/Springer: B. Bozzini, D. Kuscer, S. Drnovˇsek, M. Al-Hada, M. Amati, H. Sezen, L. Gregoratti, Spatially resolved photoemission and electrochemical characterization of a single-chamber solid oxide fuel cell, Top Catal 61 (2018) 21852194. https://doi.org/10.1007/s11244-018-1064-5. r Springer Science 1 Business Media, LLC, part of Springer Nature 2018.

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3.3.1 In situ SPEM characterization of the SOFC anodic systems The anodic side of an SOFC is generally constituted by a Ni/YSZ cermet, in contact with a ferritic stainless interconnect [1], and its stability is determined by the changes in distribution of the elements constituting these materials during operating conditions. In order to investigate how SOFC operating conditions can influence the electrode composition, electrolytesupported planar half-cells were employed (a schematic drawing of different half-cell operating configurations is shown in Fig. 3.11) [5,7,8]. Fig. 3.12 (top) shows the schematic side view of the Cr/Ni|YSZ|Ni/Cr half-cell exploited in the experiment carried out in Ref. [17]. The SPEM analysis under pristine conditions at room temperature shows a welldefined separation of the Ni and Cr patches constituting the anode (Fig. 3.12A), while the local Cr 3s and Ni 3p spectra, taken inside the Ni and Cr patches as indicated in Fig. 3.12A, confirm the single-element compositions (in metallic state) of these regions. Then the cell was run at different polarizations under 1026 mbar O2 atmosphere at 650°C (Fig. 3.12BE). Heating at open circuit potential (OCP) conditions already mobilizes the Cr and Ni atoms, which diffuse away from their initial patches (Fig. 3.12B). In particular, from the spectra acquired in the electrolyte area, the presence of Ni islands inside the YSZ electrolyte is evident. At the same time, Cr moves toward the original Ni patch. If a bias of 20.625 V is applied, further rearrangement of the Ni and Cr patches occurs (Fig. 3.12C):

Figure 3.11 Schematic drawing of the operating environments for electrolytesupported planar half-cells: (top) fuel environment, (bottom) oxidizing environment.

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Figure 3.12 (Top) Side view sketch of the Ni-based YSZ electrolyte-supported planar half-cell with Cr interconnects. (Bottom) Evolution of the elemental distribution (Ni and Cr) across the cell under different polarization and temperature conditions. The drawings summarize the SPEM results. The arrows point to the Ni (white) and Cr (black) spreading directions and the white-dashed lines indicate the initial patch border. The spectra shown are representative of the areas pointed by the arrows. (A) Pristine cell at room temperature. The Ni 3p and Cr 2p spectra show the initial condition of the cell. (B) OCP conditions at 650°C. The set of spectra in the Ni patch highlights Cr diffusion and the spectrum taken in the electrolyte evidences Ni diffusion. (C) Bias 20.625 V at 650°C. (On the left) The Ni 3p and Cr 2p maps show Ni spreading upward and downward and the partial retraction of Cr. (D) SPEM Ni 3p image of the upper half of the cell. The Ni islands in the YSZ electrolyte close to the Ni patch are shown. (E) OCP conditions at 650°C. The sketch shows the final Ni and Cr distribution in the cell. Reproduced with permission from: B. Bozzini, E. Tondo, M. Prasciolu, M. Amati, In situ X-ray spectromicroscopy investigation of the material stability of SOFC metal interconnects in operating electrochemical cells, ChemSusChem 4 (2011) 10991103. r2011 Wiley-VCH Verlag GmbH& Co. KGaA, Weinheim.

at the cathode the Ni diffuses toward the Cr patch, whereas Cr retracts back; at the anode the Cr and Ni behavior is the same as OCP conditions. The SPEM Ni 3p image in Fig. 3.12D clearly shows the aggregation of the Ni species in the YSZ zone. The presence of these Ni islands induces a loss of electric contact to the catalyst, resulting in anode degradation. Fig. 3.12E highlights the irreversibility of the rearrangement of Ni islands on the anode and electrolyte patches and the poisoning of the electrocatalyst by the Cr atoms. It was demonstrated that these mass transport and restructuring processes do not depend on the gas ambient but are mostly

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Figure 3.13 Ni 3p maps taken at 21 and 22 V. The boundary displacement between the connected and disconnected Ni islands as a result of the potentialpromoted Ni diffusion is shown and the arrows on the top of the images point to the direction of the movement. Adapted with permission from: B. Bozzini, M. Amati, L. Gregoratti, M.K. Abyaneh, M. Prasciolu, A.L. Trygub, M. Kiskinova, Microscale evolution of surface chemistry and morphology of the key components in operating hydrocarbonfuelled SOFCs, J. Phys. Chem. C 116 (2012) 2318823193. r2012 American Chemical Society.

driven by temperature and current density [18]. This progressive movement of the boundary between isolated and connected Ni islands, promoted by the current density, is well visible in Fig. 3.13, in which the arrows indicate the diffusion direction [18]. Together with atom migration, the applied potential also induces a change in the distribution of the oxidation states of the involved species [17]. In Fig. 3.14 the Cr 2p3/2 and 3s and Ni 3p spectra taken at the Cr and Ni patches and inside the YSZ electrolyte close to the Ni patch are shown at OCP and cell voltage of 23V. At OCP, both Cr and Ni are present in oxidized forms in all the regions considered; in particular, the Cr 3s peak in the Ni patch confirms the Cr poisoning of Ni at high temperature and OCP. If a cathodic voltage is applied, a shift toward the metallic state is evident for both Ni and Cr in

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Figure 3.14 (On the left) Cr 2p3/2 and 3s spectra taken in the Cr patch, showing the evolution of the Cr oxidation state. The bottom spectrum is measured at OCP conditions. The middle spectrum is measured at 23 V in the Cr patch near the Ni patch, while the top spectrum is measured near the electric contact. (On the left, top) Ni 3p and Cr 3s spectra taken at the Ni/YSZ interface. The presence of the oxidized Ni islands is evident. (On the left, bottom) Ni 3p spectra taken in the Ni patch showing the Ni oxidation-state evolution under electrochemical conditions. The bottom spectrum is measured at OCP conditions. The top spectrum is measured at 23 V. Reproduced with permission from: B. Bozzini, E. Tondo, M. Prasciolu, M. Amati, In situ Xray spectromicroscopy investigation of the material stability of SOFC metal interconnects in operating electrochemical cells, ChemSusChem 4 (2011) 10991103. r2011 WileyVCH Verlag GmbH&Co. KGaA, Weinheim.

their respective patches. Specifically, in the Cr patch, the two spectra shown in Fig. 3.14 were taken in different positions: the top one is closer to the electric contact, while the middle one is closer to the Ni patch. Both spectra highlight the presence of metallic Cr; however, the deconvolution into the single components of the top spectrum shows a progressive reduction of the oxidized species, due to the low overvoltage prevailing in that area (an analog example can be found in Ref. [5]). A similar, but opposite, behavior is evident in the Ni spectra taken in the electrolyte zone: the oxidized Ni species do not undergo reduction when a cathodic bias is applied, because they are no longer in electric contact with the conductive Ni patch. An illustrative schematic drawing of the surface morphology and the potential drops in different regions of the cell in these conditions is shown in Fig. 3.15. From the previous discussion, it is possible to assert that SPEM not only gives information about the chemical composition and oxidation-state distribution of the surface, but also it can be exploited in order to map the spatial overvoltage distribution. In

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Figure 3.15 (A) Schematic sketch of the cell surface morphology, illustrating the spatial distribution of the Ni species. (B) Scheme of the potential drops across the cell and the corresponding overvoltage types.

particular, the relationship between the kinetic energy of the photoemitted electrons and the spatial overvoltage distribution is: Ek ðxÞ 5 hν 2 Eb 1 eηðxÞ

(3.6)

Inspection of the oxidation-state distribution not only gives a chemical characterization of the surface, but also it can provide useful information about the areas in which the catalytic activity is either enhanced or suppressed. This piece of information is of fundamental importance when running SOFCs in reactive gas environments, such as mixtures of hydrocarbons, because it allows to achieve a deeper understanding of the C adsorptiondesorption dynamics, which can influence the durability of the device. Fig. 3.16 shows the C 1s spectra measured in the Ni and Cr patches at the anodic and cathodic sides of a NiCr half-cell exposed to 1026 mbar 1:1 C2H4/H2O environment at 650°C, under different polarization conditions [18]. Under reductive conditions the transformation of Ni and Cr oxides into their metallic forms (see Fig. 3.14) promotes the adsorption of C atoms, which gives rise to an intense C 1s peak both in

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Figure 3.16 C 1s spectra taken in the Ni and Cr patches at the anodic and cathodic electrodes under different polarization conditions. (A) The three spectra on the top are measured at the cathodic electrode (23 V), while the bottom spectrum is measured at the anode (13 V). The peaks on the top indicate the presence of C atoms adsorbed on the Cr and Ni patches. (B) Spectra measured after overnight OCP exposure. The least intense spectrum indicates the presence of C atoms in the Ni patch on the anodic side, which was initially clean. (C) Time evolution of the spectra after switching to 13 V on the Cr patch. Reproduced with permission from: B. Bozzini, M. Amati, L. Gregoratti, M.K. Abyaneh, M. Prasciolu, A.L. Trygub, M. Kiskinova, Microscale evolution of surface chemistry and morphology of the key components in operating hydrocarbon-fuelled SOFCs, J. Phys. Chem. C 116 (2012) 2318823193. r2012 American Chemical Society.

the Ni and Cr patches at the cathode (top of Fig. 3.16A). The narrow spectra C 1s inside the cathodic patches suggest the presence of Ni and Cr carbide species on the surface, while the absence of a corresponding peak on the anodic side (bottom spectra in Fig. 3.16A) confirms the oxidative activity of the anode. Fig. 3.16B shows the C 1s spectra after overnight exposure to OCP conditions: these spectra suggest a strong presence of

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Ni and Cr carbides on the cathodic side and the formation of C-containing species on the anodic side: the lower intensity associated with the NixC species on the cathodic side indicates a lower stability of the Ni carbides with respect to Cr carbides in these operating conditions. Finally, Fig. 3.16C shows the system under strongly oxidizing conditions: the fall in intensity and the progressive shift to higher BEs indicates the formation of CC species at the Cr surface.

3.3.2 From in situ SPEM studies on SC-SOFCs to the SPEM characterization of self-driven cells The half-cells explored in the previous sections are useful tools in order to understand the transformations of the single-cell components under operating conditions. However, they cannot provide exhaustive information about the processes occurring during the operation of a complete real system. In Refs. [19,20], we demonstrated, for the first time, the characterization by means of synchrotron-based in situ SPEM of both externally driven and self-driven single-chamber SOFCs (SC-SOFCs). The first SC-SOFC designed for in situ SPEM experiments was a planar YSZ(1 0 0)-supported cell with AuMnO2 and NiO as cathodic and anodic materials, respectively, that were obtained by oxidizing in 1026 mbar O2 at 650°C the previously deposited metal precursors [20]. A sketch of the cell design is shown in Fig. 3.17, together with Mn 2p, Ni 2p, and Zr 3d maps of the pristine cell, in which the regular and welldefined disposition of the cell materials is evident. The cell evolution in 1025 mbar 1:1 CH4:O2 at 650°C was monitored by starting from two different initial conditions: with fully preoxidized electrodes and after the in situ reduction of the NiO anode by applying 21 V with respect to the AuMn electrode. The Ni and Mn 2p spectra of the electrodes in the two different initial conditions are shown in Fig. 3.18A, combined with the OCP measurements acquired by switching to the reactive environment (see Fig. 3.18B), which indicate the achievement of a controlled steady state. In operando measurements were then performed by setting the applied voltage to 75 mV and monitoring the current time profile (see Fig. 3.19A). After the reduction treatment of the NiO anode, the current increased by one order of magnitude, due to the presence of metallic Ni, which catalyzes the anodic reaction, as already discussed. Instead, the current decay, in conjunction with the progressive redistribution of the species constituting the cell, also confirms the previous assertions regarding the association of the SOFC degradation with this redistribution process occurring under

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Figure 3.17 Sketch of the SC-SOFC together with the Ni and Mn 2p and Zr 3d maps of the pristine cell. SC-SOFCs, Single-chamber solid oxide fuel cells. Elaborated from B. Bozzini, M. Amati, L. Gregoratti, C. Mele, M. Kazemian, Electrochemistry communications in-situ photoelectron microspectroscopy during the operation of a single-chamber SOFC, Electrochem. Commun. 24 (2012) 104107. r2012 Elsevier B.V. with permission from Elsevier.

Figure 3.18 (A) Ni 2p and Mn 2p spectra acquired inside the electrode patches and representing the initial conditions before running the cell in the reactive mixture. The bottom spectra were acquired in 1025 O2 ambient at 650°C, while the top spectra were acquired after applying 21 V on the NiO anode. (B) OCP measurements in 1025 mbar 1:1 CH4/O2 ambient at 650°C: (1) preoxidized cell (2) after 21 V reduction. Elaborated from: B. Bozzini, M. Amati, L. Gregoratti, C. Mele, M. Kazemian, Electrochemistry communications in-situ photoelectron microspectroscopy during the operation of a single-chamber SOFC, Electrochem. Commun. 24 (2012) 104107. r2012 Elsevier B.V. with permission from Elsevier.

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Figure 3.19 (A) Current generated by applying 75 mV in 1025 mbar 1:1 CH4/O2 ambient. (B) Au 4f, Mn and Ni 2p maps after long operation at 75 mV in 1025 mbar 1:1 CH4/O2 ambient at 650°C. Elaborated from B. Bozzini, M. Amati, L. Gregoratti, C. Mele, M. Kazemian, Electrochemistry communications in-situ photoelectron microspectroscopy during the operation of a single-chamber SOFC, Electrochem. Commun. 24 (2012) 104107. r2012 Elsevier B.V. with permission from Elsevier.

Figure 3.20 Schematic drawing of the operating principle of a self-driven cell.

operating conditions (see Fig. 3.19B). These SC-SOFCs are useful tools to investigate the morphochemical aspects of processes occurring during the operation of a complete SOFC, which are not accessible with half- or symmetric-cell approaches. This cell configuration allows self-driven operation, in which not only the electrochemical activity at the electrode/ electrolyte interface can be characterized but also the coupling between the anodic and cathodic phenomena. In a self-driven cell the potentials at the electrodes are generated by the electric current provided by the electrochemical reactions controlled by the gas reactant environment, as schematically shown in Fig. 3.20. In Ref. [19] the authors investigated a planar, YSZ(1 1 0)-supported cells with Ni/NiO and MnO2/MnO electrodes at 650°C in different ambient: fuel (H2), oxidant (O2), and fuel and oxidant mixture (O2 1 H2). Before switching to the reactant environment, the cell was maintained at 1025 mbar O2 and Ni 2p2/3, and Mn 2p SPEM maps were taken, together with some representative spectra, in order to visualize the cell initial condition (see Fig. 3.21A). At variance with the system

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Figure 3.21 (A) (Top) Ni 2p2/3 and Mn 2p SPEM maps of the pristine cell in 1025 mbar O2 at 650°C. The dashed line marks the electrode/electrolyte edge. (Bottom) Ni 2p2/3 and Mn 2p microspot spectra of the electrodes. (B) Reaction scheme of the cell in 1025 mbar O2 at 650°C. Chemical reactions are indicated with α, electrochemical reactions with β. Elaborated from B. Bozzini, M. Amati, L. Gregoratti, M. Kiskinova, In-situ photoelectron microspectroscopy and imaging of electrochemical processes at the electrodes of a self-driven cell, Sci. Rep. 3 (2013) 15. This article is available under the Creative Commons CC-BY-NC-SA license. http://creativecommons.org/licenses/by/4.0/.

studied in Ref. [17], no mass transport is evident at 650°C and the cell presents a well-defined distribution of constituents. As expected, the spectra highlight the presence of oxidized species at the electrodes.

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The electrochemical reaction scheme for this cell configuration is shown in Fig. 3.21B: the presence of O2 does not induce a reduction of MnO2 to MnO, because MnO2 is a stable species in oxidizing environments. However, O2 is reduced due to the catalytic effect of MnO2 and, at the anode, Ni0 oxidizes to NiO because of the simultaneous presence of O2 and O22 2 . After switching from O2 to H2 or H2 1 O2 environment, no structural changes occur, in contrast with the externally driven cells [17,18,20]. In Fig. 3.22A the Ni p2/3 spectra show the time evolution of the oxidation state and local potential of the Ni electrode exposed to H2 (left panel of Fig. 3.22A) and H2 1 O2 (right panel of Fig. 3.22A). The corresponding reaction schemes are illustrated in Fig. 3.22B (top for H2, bottom for H2 1 O2). In both cases the presence of H2 induces a partial reduction of the NiO electrode; in particular, in the H2 1 O2 ambient, the amount of the metallic component reaches a maximum and then slightly decreases, because the H2 oxidation and anodic oxidation occur at the same time. In correspondence, the Ni21 component in the spectra undergoes a rigid energy shift (see also Fig. 3.15 and related details), due to the overpotential generated by the current flow induced by the hydrogen oxidation at the NiO electrode: the maximum shift is 0.75 eV for H2 and 0.85 eV for H2 1 O2 ambient. Fig. 3.22C illustrates a conceptual sketch of the spatial overvoltage distribution in this cell. The MnO2 cathode is both ionically and electronically conductive and it is grounded through the Au matrix; for this reason, it should exhibit a homogeneous potential, whence no spectral shifts are expected. The NiO electrode is only electronically conductive, so there is a spatial inhomogeneity in the electrochemical activity between the active electrolyte/electrode interface and the inactive inner region: in these conditions an overpotential gradient develops over the Ni/NiO patch and, when anodic reactions occur, a spectral shift takes place. From Fig. 3.22A it is evident that a constant current is set after 10 minutes in the H2 1 O2 ambient, while in the H2 ambient, a backward shift occurs at longer reaction times, indicating a decrease in current due to the cathode reduction (see Fig. 3.22B, top). By exploiting the imaging mode of SPEM, that is, starting the Ni 2p image and switching to the desired gas ambient after some scans, it is possible to achieve higher temporal resolution (32 seconds) and higher statistics in order to better follow the progressive NiO reduction. An example is shown in Fig. 3.23, where the spectra on the right panel are acquired in three different locations of the top Ni 2p image on the left, which are representative both of the initial oxide state of the system in O2 ambient and of the reduced states, resulting

Figure 3.22 (A) Ni 2p3/2 spectra illustrating the time evolution of the anode under 1025 mbar: (left) H2, (right) H2 1 O2. (B) Reaction scheme of the cell under 1025 mbar: (top) H2, (bottom) H2 1 O2. Chemical reactions are indicated with α, electrochemical reactions with β. (C) Conceptual drawing of the spatial overvoltage distribution of the cell. Elaborated from B. Bozzini, M. Amati, L. Gregoratti, M. Kiskinova, In-situ photoelectron microspectroscopy and imaging of electrochemical processes at the electrodes of a self-driven cell, Sci. Rep. 3 (2013) 15. This article is available under the Creative Commons CC-BY-NC-SA license. http://creativecommons.org/licenses/by/4.0/.

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Figure 3.23 (Left) Ni 2p maps in which each vertical scan corresponds to 32 s. (Right) Ni 2p spectra corresponding to spots 1, 2, 3 indicated in the first map on the left, representing the Ni initial, transient, and final state after switching to 1025 mbar H2 environment at 650°C. The blue and red boxes highlight the energy windows outlining the Ni0 and Ni21 evolution, which are used for the construction of the Ni0 reduction map (middle map, left) and the Ni21 map (bottom map, left) tracing the current-induced shift. (C) Plots of the current-induced shift. Elaborated from B. Bozzini, M. Amati, L. Gregoratti, M. Kiskinova, In-situ photoelectron microspectroscopy and imaging of electrochemical processes at the electrodes of a self-driven cell, Sci. Rep. 3 (2013) 15. This article is available under the Creative Commons CC-BY-NC-SA license. http://creativecommons.org/licenses/by/4.0/.

from the subsequent H2 injection. From the inspection of these spectra, it is possible to confirm the presence of an overpotential shift and the reduction evolution that were observed also in Fig. 3.22. Moreover, by choosing the proper channels covering the selected photon energy, it was possible to obtain the Ni0 and ΔNi21 maps on the left of Fig. 3.23, in which the brightness level indicates the stage of evolution of the single components constituting the surface. Then by averaging the signal over the areas indicated by the blue and red boxes, it is possible to obtain the time evolution of the intensity of the Ni0 component and the spectral shift associated with the oxidized species. In this system, a steady, partially reduced Ni state is reached after 25 and 30 minutes after switching to H2 and H2 1 O2 ambient, while the ΔNi21 plots show the same trend of the spectra

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in Fig. 3.22. Thus with this analysis, it is possible to quantitatively measure the transient dynamics of the partial NiO reduction and current generation. At last, the DHP setup was exploited in order to investigate the propagation of the reaction front. The Ni0 map in Fig. 3.24A was taken immediately after switching from 1025 mbar O2 to 1 mbar H2. It is

Figure 3.24 (A) (Left) Ni0 map after switching to 1 mbar H2 ambient at 650°C. (Right) Ni 2p spectra taken in the indicated locations of the left map. (B) (Left) Chemical maps obtained by removing the topography contrast from (A) (top) and after 35 min (bottom). The topography contrast was removed by dividing the Ni0 image to the background image. (Right) Time evolution of the Ni region indicated by the ellipse in map (A). Elaborated from B. Bozzini, M. Amati, L. Gregoratti, M. Kiskinova, In-situ photoelectron microspectroscopy and imaging of electrochemical processes at the electrodes of a self-driven cell, Sci. Rep. 3 (2013) 15. This article is available under the Creative Commons CC-BY-NC-SA license. http://creativecommons.org/licenses/by/4.0/.

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evident that a brighter area appears on the right, denoting the growth of the metallic species due to the penetration of the reaction front: this is also confirmed by the spectra extracted from different points of the sample (see right panel). By removing the topography by dividing the image by the background, it is possible to obtain the chemical maps of the sample (see Fig. 3.24B). After 35 minutes, no chemical contrast appears, since the whole area has been reduced. These results are also confirmed by the spectra on the right panel, in which a vanishing of the Ni21 peak indicates the complete reduction of the species. 3.3.2.1 SPEM characterization of a SC-SOFC in a NAP cell The NAP cell, recently developed at ESCA microscopy (see Fig. 3.9), allows the in operando characterization of SC-SOFCs at constant pressure in the NAP range, without any modifications of the standard UHV chamber (see Section 3.1.2.). In Ref. [21] the first SPEM study on a NiO|YSZ(100)|(La0.8Sr0.2)0.95 MnO2 (LSM) SC-SOFC assembled in the NAP cell was reported. In Fig. 3.25 the C 1s image of the whole accessible field of view is shown, together with a zoomed image of the electrode/electrolyte interface. Experiments were carried out at 923K in a 0.1 mbar 2:1 CH4/O2 ambient, while cell conditioning was performed in a 0.1 mbar H2 ambient for 30 minutes, to reduce NiO to metallic Ni. The measurements were carried out in short-circuited conditions, to simulate operating stress

Figure 3.25 (Left) C 1s map of the whole field of view for XPS analysis. (Right) Zoomed C 1s map of the electrodeelectrolyte interface. XPS, X-ray photoelectron spectroscopy. Reprinted by permission from Nature/Springer: B. Bozzini, D. Kuscer, S. Drnovˇsek, M. Al-Hada, M. Amati, H. Sezen, L. Gregoratti, Spatially resolved photoemission and electrochemical characterization of a single-chamber solid oxide fuel cell, Top Catal 61 (2018) 21852194. https://doi.org/10.1007/s11244-018-1064-5. rSpringer Science 1 Business Media, LLC, part of Springer Nature 2018.

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Figure 3.26 (A) OCP transients at 923K measured while injecting 2:1 CH4/O2 mixture into the chamber at different pressures. The OCP variations in the dashed box are due to suboptimal operation of the pressure-management system. (B) Current density transients for the short-circuited SC-SOFC at different pressures of 2:1 CH4/O2 at 923K. (C) EIS spectrum (Nyquist plot) recorded after 10 h of exposure in 0.1 mbar 2:1 CH4/O2 at 923K. SC-SOFCs, Single-chamber solid oxide fuel cell s. Panels (A) and (C): reprinted by permission from Nature/Springer B. Bozzini, D. Kuscer, S. Drnovˇsek, M. Al-Hada, M. Amati, H. Sezen, L. Gregoratti, Spatially resolved photoemission and electrochemical characterization of a single-chamber solid oxide fuel cell, Top Catal 61 (2018) 21852194. https://doi.org/10.1007/s11244-018-1064-5. rSpringer Science 1 Business Media, LLC, part of Springer Nature 2018. Panel (B): reproduced from B. Bozzini, D. Kuscer, M. Amati, L. Gregoratti, P. Zeller, T. Dobrovolska, I. Krastev, Spatially resolved XPS characterization of electrochemical surfaces, Surfaces 2 (2019) 295314. This article is available under the Creative Commons CC-BY-NC-SA license. http://creativecommons.org/licenses/by/4.0/.

conditions of a real device and to study only the effects due to the gas environment. Before running the experiments the system was calibrated: a sequence of OCP measurements in different pressure conditions, starting from UHV, was collected and they are shown in Fig. 3.26A. Various trends are visible in the OCP time series: a rapid increase in the OCP value is evident at pressures lower than 10 mbar, followed by a decrease to lower values, while at 0.10 and 0.15 mbar the asymptotic value reaches the one recorded at UHV conditions. For pressures of 3 and 8 mbar, higher asymptotic values are reached, whereas for higher pressures the OCP value progressively increases. In Fig. 3.26B the current transients measured by short-circuiting the cell are shown [8]. A rapid increase of current is evident, followed by a relaxation to a well-defined steady condition. The electrochemical stability of the system under NAP-SPEM conditions (0.1 mbar, 1:2 CH4/O2, 923°C) was checked also by means of electrochemical impedance spectroscopy (EIS) measurements after an overnight exposure to the gas under OCP conditions (see Fig. 3.26C): the RC loop indicates stable cell operation. After the system calibration and in all standby periods, the cell was kept under 5 3 1022 mbar O2 in order to avoid the reduction of the electrode/electrolyte surface due to

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the combination of HV and temperature. The SPEM analysis focused only on the cathodic electrode, because it is a better benchmark, owing to its lower reactivity with respect to the NiO anode. The pristine conditions in 5 3 1022 mbar O2 of the electrode/electrolyte interface are shown in the top maps of Fig. 3.27A, while the bottom spectrum illustrates the chemical composition of the spots numbered in the La 4d map. From the peak analysis, all the elements constituting the involved materials were identified, together with C and Si impurities in the electrolyte. The differences in the peaks intensity for O, C, and Zr in the 1 and 2 spectra reveal a heterogeneity of the cathode surface, typical of the fabrication process (see Ref. [21] for more details). In Fig. 3.27B, further Sr 3d and La 4d maps are shown, together with the Sr 3d and La 4d intensity profiles extracted along the dotted lines. Also, several microspot spectra were measured along this line at different distances from the interface (see Fig. 3.27C). A partial overlap between the La 4d and Si 3p spectra provides an internal reference in order to investigate the relative intensity variations of the perovskite component. A constant signal is evident from the Sr 3d spectra all along the investigated zone, which stresses the constant coverage of this component, while the La 4d spectra show a spatial gradient, due to its different surface diffusion coefficients with respect to Sr. The evolution of the cathode elements (La 4d, Zr 3d, O 1s, Mn 2p) was investigated in different ambient: 5 3 1022 mbar O2, 0.1 mbar H2, 0.1 mbar 2:1 CH4/O2 at different operating conditions, that is, OCP in all the ambient and short-circuited condition in the reactive ambient [8]. The analysis of the La 4d, Zr 3d, and Mn 2p core levels, acquired on different areas of the cathode and electrolyte, did not show any effect either of the environment or of the electrochemical polarization. Instead, the Sr 3d manifests chemical sensitivity to the ambient (see Fig. 3.28), in particular in H2 and reactive gas mixture ambient. From ex situ XPS measurements (Ref. [8] and references therein), the Sr spectra measured under different conditions can be interpreted as LaSr perovskite, characterized by BE between 131.4 and 132.5 eV, and as diffused in YSZ, with BE between 132.8 and 133.8 eV. In the H2 ambient, a well-defined spectral variation in the low BE tail of the cathodic Sr is evident with respect to the O2 atmosphere, that is due to a partial reduction; instead, the spectrum of the diffused species does not reveal any change (Fig. 3.28AE). At the same time the Sr species in the cathode patch show an irreversible change in the reactive ambient (see Fig. 3.28C), whereas the diffused Sr, also in this case, does not show any variation. This irreversible change occurs at OCP conditions, and it is no longer modified by applying

Figure 3.27 Cell analysis in 5 3 1022 O2 ambient at 923K. (A) (Top) La 4d and Zr 3d maps of the LSMYSZ interface. (Bottom) Microspot spectra acquired at the 1, 2, 3 positions indicated in the La top map. (B) (Top) Sr 3d and La 4d maps together with the concentration profiles acquired along the dashed line. (Bottom) Microspot spectra measured at the indicated distances from the interface along the dashed lines. Panel (A): Reprinted by permission from Nature/Springer B. Bozzini, D. Kuscer, S. Drnovˇsek, M. Al-Hada, M. Amati, H. Sezen, L. Gregoratti, Spatially resolved photoemission and electrochemical characterization of a single-chamber solid oxide fuel cell, Top Catal 61 (2018) 21852194. https://doi.org/10.1007/ s11244-018-1064-5. r Springer Science 1 Business Media, LLC, part of Springer Nature 2018. Panels (B) and (C) reproduced from: B. Bozzini, D. Kuscer, M. Amati, L. Gregoratti, P. Zeller, T. Dobrovolska, I. Krastev, Spatially resolved XPS characterization of electrochemical surfaces, Surfaces 2 (2019) 295314. This article is available under the Creative Commons CC-BY-NC-SA license. http://creativecommons.org/licenses/by/4.0/.

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Figure 3.28 Sr 3d microspot spectra acquired at the cathode (AC) and at the electrolyte (DF) patches at 924K. Spectra (A), (B), (D), and (E) are compared at OCP conditions in 5 3 1022 mbar O2 and 0.1 mbar H2. Spectra (C) and (F) are compared in 5 3 1022 mbar O2 and 0.1 mbar 2:1 CH4/O2. Reproduced from: B. Bozzini, D. Kuscer, M. Amati, L. Gregoratti, P. Zeller, T. Dobrovolska, I. Krastev, Spatially resolved XPS characterization of electrochemical surfaces, Surfaces 2 (2019) 295314. This article is available under the Creative Commons CC-BY-NC-SA license. http://creativecommons.org/ licenses/by/4.0/.

electrochemical polarization. From the analysis of the binding energies, it is possible to say that the prevalent species at the cathode is surface Sr, corresponding to the formation of a SrO surface phase, while in the electrolyte perovskite-type Sr is prevalent.

3.4 Conclusion XPS has been exploited for decades to investigate the surface chemistry of materials, including ex situ and postmortem analyses of compounds used for SOFC electrodes, thanks to its surface- and chemical-state sensitivity. Moreover, a few examples of electrochemical studies of single-electrode model systems with applied bias have also been reported. These measurements have provided a good deal of fundamental information on the materials as such, but the scanty information regarding the full cell and the localization processes has limited the concrete impact of this approach on the SOFC community. In this chapter, we present the recent achievements of our group, regarding instrumental and electrochemical developments aimed at achieving space resolution and NAP conditions. In particular, we briefly

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describe the issues associated on the one hand with microscopic capability applied to full fuel cells with precise space-dependent electrochemical control, accessibility of all the cell components to the probe beam and compositionally realistic gas feeds, and, on the other hand, with the transfer of this technology to NAP conditions. The essay is completed by a selection of in situ electrochemical results that cover a comprehensive range of topics of interest for SOFC technology: degradation and contamination of electrocatalysts and interconnects, dynamic mapping of electrocatalyst activity, including overvoltage mapping with submicrometer precision and single-grain activity monitoring, observation of anode, cathode, and electrolyte under identical operating conditions, operation and characterization of single-chamber SOFCs. Systematic development of instrumental solutions, aimed at achieving progressively more realistic operating conditions, along the lines expounded in this chapter, will allow a deeper understanding of solid oxidebased fuel cell and electrolyzers, that is likely to contribute otherwise inaccessible information for the knowledge-based design and management of next-generation, more efficient and durable electrochemical energy storage systems.

References [1] S.P.S. Badwal, K. Foger, Solid oxide electrolyte fuel cell review, Ceram. Int. 8842 (1996) 257265. Available from: https://doi.org/10.1016/0272-8842(95)00101-8. [2] S. Günther, B. Kaulich, L. Gregoratti, M. Kiskinova, Photoelectron microscopy and applications in surface and materials science, Prog. Surf. Sci. 70 (2002) 187260. Available from: https://doi.org/10.1016/S0079-6816(02)00007-2. [3] K. Horiba, Y. Nakamura, N. Nagamura, S. Toyoda, H. Kumigashira, M. Oshima, et al., Scanning photoelectron microscope for nanoscale three-dimensional spatialresolved electron spectroscopy for chemical analysis, Rev. Sci. Instrum. 82 (2011) 06. Available from: https://doi.org/10.1063/1.3657156. [4] M. Amati, A. Barinov, V. Feyer, L. Gregoratti, M. Al-Hada, A. Locatelli, et al., Photoelectron microscopy at Elettra: recent advances and perspectives, J. Electron. Spectros Relat. Phenom. 224 (2018) 5967. Available from: https://doi.org/ 10.1016/j.elspec.2017.06.006. [5] B. Bozzini, M. Amati, L. Gregoratti, M. Kazemian, M. Prasciolu, E. Tondo, et al., In situ electrochemical X-ray spectromicroscopy investigation of the reduction/reoxidation dynamics of Ni 2 Cu solid oxide fuel cell anodic material in contact with a Cr interconnect in 2 3 1026 mbar, J. Phys. Chem. C 116 (2012) 72437248. Available from: https://doi.org/10.1021/jp208478n. [6] A.K. Huber, M. Falk, M. Rohnke, B. Luerßen, L. Gregoratti, M. Amati, et al., In situ study of electrochemical activation and surface segregation of the SOFC electrode material La0.75Sr0.25Cr0.5Mn0.5O3 6 δ, Phys. Chem. Chem. Phys. 14 (2012) 751758. Available from: https://doi.org/10.1039/c1cp21743g.

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[7] M. Backhaus-Ricoult, K. Adib, K. Work, M. Badding, T. Ketcham, M. Amati, et al., In-situ scanning photoelectron microscopy study of operating (La, Sr)FeO3based NO x-sensing surfaces, Solid State Ion. 225 (2012) 716726. Available from: https://doi.org/10.1016/j.ssi.2012.03.007. [8] B. Bozzini, D. Kuscer, M. Amati, L. Gregoratti, P. Zeller, T. Dobrovolska, et al., Spatially resolved XPS characterization of electrochemical surfaces, Surfaces 2 (2019) 295314. Available from: https://doi.org/10.3390/surfaces2020022. [9] A. Jürgensen, N. Esser, R. Hergenröder, Near ambient pressure XPS with a conventional X-ray source, Surf. Interface Anal. 44 (2012) 11001103. Available from: https://doi.org/10.1002/sia.4826. [10] H. Bluhm, M. Hävecker, A. Knop-Gericke, M. Kiskinova, R. Schlögl, M. Salmeron, In situ X-ray photoelectron studies of gassolid interfaces at near-ambient conditions, MRS Bull. 32 (2007) 10221030. Available from: https://doi.org/ 10.1557/mrs2007.211. [11] H. Sezen, B. Alemán, M. Amati, M. Dalmiglio, L. Gregoratti, Spatially resolved chemical characterization with scanning photoemission spectromicroscopy: towards near-ambient-pressure experiments, ChemCatChem 7 (2015) 36653673. Available from: https://doi.org/10.1002/cctc.201500637. [12] M. Amati, M. Kazemian Abyaneh, L. Gregoratti, Dynamic high pressure: a novel approach toward near ambient pressure photoemission spectroscopy and spectromicroscopy, J. Instrum. (2013) 8. Available from: https://doi.org/10.1088/1748-0221/ 8/05/T05001. [13] S. Oswald, X-Ray Photoelectron Spectroscopy in Analysis of Surfaces, John Wiley & Sons, Ltd., 2013. Available from: https://doi.org/10.1002/9780470027318.a2517.pub2. [14] P. Willmott, An Introduction to Synchrotron Radiation: Techniques and Applications, John Wiley & Sons, Ltd, 2011. Available from: https://doi.org/ 10.1002/9781119970958. [15] D. Attwood, Soft X-rays and Extreme Ultraviolet Radiation, Cambridge University Press, 1999. Available from: https://doi.org/10.1017/cbo9781139164429. [16] M. Amati, A. Barinov, L. Gregoratti, H. Sezen, M. Kiskonova, Scanning photoelectron microscopy: past, present and future. Springer Handb. Surf. Sci., Springer; n.d. [17] B. Bozzini, E. Tondo, M. Prasciolu, M. Amati, In situ X-Ray spectromicroscopy investigation of the material stability of SOFC metal interconnects in operating electrochemical cells, ChemSusChem 4 (2011) 10991103. Available from: https://doi. org/10.1002/cssc.201100140. [18] B. Bozzini, M. Amati, L. Gregoratti, M.K. Abyaneh, M. Prasciolu, A.L. Trygub, et al., Microscale evolution of surface chemistry and morphology of the key components in operating hydrocarbon-fuelled SOFCs, J. Phys. Chem. C 116 (2012) 2318823193. Available from: https://doi.org/10.1021/jp3040105. [19] B. Bozzini, M. Amati, L. Gregoratti, M. Kiskinova, In-situ photoelectron microspectroscopy and imaging of electrochemical processes at the electrodes of a self-driven cell, Sci. Rep. 3 (2013) 15. Available from: https://doi.org/10.1038/srep02848. [20] B. Bozzini, M. Amati, L. Gregoratti, C. Mele, M. Kazemian, In-situ photoelectron microspectroscopy during the operation of a single-chamber SOFC, Electrochem. Commun. 24 (2012) 104107. Available from: https://doi.org/ 10.1016/j.elecom.2012.09.001. [21] B. Bozzini, D. Kuscer, S. Drnovˇsek, M. Al-Hada, M. Amati, H. Sezen, et al., Spatially resolved photoemission and electrochemical characterization of a singlechamber solid oxide fuel cell, Top. Catal. 61 (2018) 21852194. Available from: https://doi.org/10.1007/s11244-018-1064-5.

CHAPTER 4

Protonic-based ceramics for fuel cells and electrolyzers Kawther Thabet, Annie Le Gal La Salle, Eric Quarez and Olivier Joubert

Institut des Matériaux Jean Rouxel (IMN), CNRS-Université de Nantes, 44322 Nantes Cedex 3, France

Contents 4.1 Mechanism of proton conduction 4.1.1 Proton defect formation 4.1.2 Proton transport 4.2 Electrolyte materials 4.2.1 BaCeO3 perovskite-based materials 4.2.2 BaZrO3 4.2.3 BaCeO3BaZrO3 mixed systems 4.2.4 SrZrO3 4.2.5 Other proton-conductive materials 4.3 Electrode materials 4.3.1 Fuel electrode material 4.3.2 Air electrode material References

91 91 93 94 94 97 98 99 100 104 104 110 115

4.1 Mechanism of proton conduction 4.1.1 Proton defect formation The incorporation and the transport of proton within oxide materials structure require mainly the presence of oxygen vacancies. These latter can be induced by intrinsic defects (structure defects) related to a lack of an atom or an extrinsic defects related to impurities and substitutions with an acceptor type dopant. Under a humid atmosphere, protonic defects are created through the reaction of water with a vacant oxygen site and an oxygen ion, resulting in the formation of two hydroxyl entities (4.1). One is formed through a creation of a bond between a proton with oxygen from the structure,

Solid Oxide-Based Electrochemical Devices DOI: https://doi.org/10.1016/B978-0-12-818285-7.00004-6

© 2020 Elsevier Inc. All rights reserved.

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whereas the other is due to the filling of a neighboring oxygen vacancy to form the second protonic defect [1]. The dissociation of water in contact with a protonic conductor can be described according to the following reaction based on the KrögerVink notation [2]: H2 O 1 Vvo 1 Oxo -2 OHo

(4.1)

where Vvo is oxygen vacancy; Oxo is the oxygen ion in the normal lattice position, and OHo is the proton defect. This reaction concerns the majority of the proton-conducting phases such as perovskite materials with oxygen vacancies as main default. The creation of oxygen vacancies in perovskite structure occurs through the introduction of acceptor type dopant. As illustrated in Fig. 4.1, a typical perovskite structure is formed with 14 oxidation state cation in B-site and 12 oxidation state cation in A-site. The introduction of a trivalent cation M in the B-site generates oxygen vacancies according to the following equation [3,4]: x 0 2BX B 1 Oo 1 M2 O3 -2MB 1 Vo 1 2BO2

(4.2)

This mechanism is the one mainly observed for materials used as electrolyte in proton ceramic fuel cell or electrolyzer. The proton defect can be also produced by another mechanism of proton incorporation without oxygen-defect participation under hydrogen-rich atmosphere when the compound exhibits a reducible element according to the following reaction:  2 H2 1 2 OX o -2 OHo 1 2 e

(4.3)

As described in the above equation, the creation of proton defects can also involve the electronic defects as compensating charges, leading to electronic conductivity. Accordingly, these types of materials are not used as electrolyte.

Figure 4.1 Ideal cubic perovskite structure.

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The enthalpy of water dissolution reaction (4.2) is negative indicating that the proton conductivity dominates at low temperature, while at high temperature, the reverse reaction takes place and the conductivity is controlled by the O2-vacancy mechanism [1]. One of the properties to be taken into consideration to promote the reactivity with water is the material basicity, which is related to the electronegativity of the element. It has been reported that compounds with lower electronegativity exhibit higher hydration equilibrium constant leading to a more stable proton defects [1,5]. Thus the perovskite basicity must be important enough to promote the dissociation of water but sufficiently low to avoid parasite reactions with acid gases such as CO2, which can affect electrolyte performance due to the decomposition of the material by carbonation [6].

4.1.2 Proton transport The proton-conduction mechanism has long been debated, and several researches have been carried out to study proton position and transport. Due to its tiny ionic radius and its strong polarization power, the proton H1 cannot be isolated in equilibrium conditions. It reacts with its environment by creating covalent bonds. The two main mechanisms that can be considered to date for the proton transport are vehicle mechanism [5] and Grotthuss mechanism [6,7]. The first considers that the proton remains bounded with a mobile ion such as O22 to form hydroxyl group, or a mobile molecule such as H3O1. In these two cases the proton transport is ensured by the migration of the mobile group in the structure. This type of mechanism is mainly observed in aqueous solutions, ionic liquids, and small molecular compounds with a low-binding energy. For Grotthuss mechanism the proton is free and moves by hopping from an oxygen ion to another by rotational diffusion of the hydroxyl group and a prior breakage of hydrogen bound as seen in Fig. 4.2. The proton migration is thus facilitated by a weak OH bond. In this case the proton transport depends on interoxygen distance, and it is promoted in symmetrical perovskite structure where the OO distance is less than 0.25 nm [7]. To elucidate the proton transport mechanism an isotope effect (H1/D1) analysis was performed and demonstrated that the conduction process is ensured by proton jumping from one oxygen ion to the adjacent one [8]. Quantum MD simulation was also realized and demonstrated that the determining mechanism is based on proton rotational diffusion and hopping between adjacent oxygen ions, which confirms the Grotthuss mechanism [1].

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Figure 4.2 Trace of a proton (orange) diffusion in BaCeO3 showing the two main features of proton transport: rotational motion and proton transfer [7].

4.2 Electrolyte materials 4.2.1 BaCeO3 perovskite-based materials Compounds, derived from barium cerate (BaCeO3), have been intensively studied for more than 30 years and are still considered as one of the most attractive and promising proton-conducting ceramics. Using acceptor dopant process as mentioned above, a large number of oxygen deficient compounds with BaCe12xMxO32δ general formula have reported. According to the operating temperature, these perovskite BaCeO3 can react with water vapor to form hydrated compounds BaCe12xMxO3-yOHz (z # y). At high temperature the BaCeO3-based materials show predominant anionic conductivity, while they are proton conductors at low temperature [9]. They present the highest proton conductivity among the other materials (10221023 s cm21 at 600°C with an H1 transport number close to one). This high conductivity level is due to a combination of the basicity of the Cerium element and the presence of oxygen vacancies within the material crystal lattice. Barium cerate structure was initially studied by Jacobson et al. [10]. At room temperature, BaCeO3 crystallizes in an orthorhombic Pmcm space group [11,12]. Three main structural phase transitions have been reported from ambient temperature to 1000°C. The first allotropic transformation is observed at 290°C and is associated with a small structure change from Pmcm to Incn space group. At approximately 400°C the transition consists on orthorhombic to rhombohedral changes. Finally at 900°C, a transformation to a face-centered cubic structure with Pm-3m space group (Fig. 4.3) is observed. The influence of the nature of the dopant element on the conductivity was intensively investigated. The most studied systems are doped with

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Figure 4.3 Structural phase transition of BaCeO3 as a function of temperature [13].

trivalent acceptors elements. Iwahara et al. investigated electrochemical properties of substituted perovskite BaCe0.9M0.1O32δ by various elements (M 5 Nd, Sm, Gd, Dy, Yb, Y, . . .). Results showed that doping with Y leads to the best H1 conductivity associated with the highest proton transport number compared to other dopants. The decrease of dopant ionic radius promotes higher proton transport number. Indeed, the substitution by a larger ionic radius dopant induce an enlargement of the spacing along a-axis, leading to a crystalline structure change from orthorhombic symmetry and affects the ions movements. The structure parameters have an effect on the ionic conductivity, and, in general, the more important the distortion, the less the ionic conductivity. The distortion is given by the Goldschmidt tolerance factor (t) as described in the following equation [14]: ra 1 ro T 5 pffiffiffi 2ðrb 1 ro Þ where ra and rb are the ionic radii of cations in A- and B-sites, respectively, while ro is the ionic radii of oxygen. It was confirmed through several studies that the highest value of the total conductivity is reached with

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yttrium and samarium-doped material under partial pressure of H2 of 1 atm [3,15,16]. The corresponding total conductivities at 873K were 1.75 3 1022 and 2.5 3 1022 S cm21, respectively. The influence of the dopant element concentration was also well studied. It was demonstrated that if the variation of dopant quantity (x) does not affect the material structure, the increase of x promotes a better ionic conductivity which reaches a maximum for x 5 0.10.25, depending on the nature of lanthanide [17,18]. This can be explained by the formation of oxygen vacancies due to the dissolution of the lanthanide in the perovskite structure. A further increase of the lanthanide concentration is followed by a decrease of free oxygen vacancies and consequently a decrease of ionic conductivity (Fig. 4.4) [20,21]. The electrochemical properties are of a great importance to enable a final practical application; however, other parameters must be taken into consideration such as the chemical and mechanical stability. Indeed the major drawback of BaCeO3-based oxides is their chemical instability and reactivity with acid gases such as water or carbon dioxide leading to secondary phases formation, due to their high basicity [22,23]: BaCeO3 1 H2 O-BaðOHÞ2 1 CeO2 BaCeO3 1 CO2 -BaCO3 1 CeO2 BaCeO3 1 H2 S-BaS 1 CeO2 1 H2 O Many attempts were made to overcome the low thermodynamic stability and maintain a high conductivity level by the codoping of BaCeO3. However, this strategy to stabilize the material against atmospheres induces a decrease in conductivity which can be related to a decrease in

20

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(B) Ln-Gd Ln-Gd Ln-Sm

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(A)

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Figure 4.4 Electrical conductivity of BaCe12xLnxO32δ materials at 600°C in wet air (A) and wet hydrogen (B) [19].

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the structure volume and consequently a decrease in migration channels size, and an increase of OH bond strength [24].

4.2.2 BaZrO3 Barium zirconatebased materials as well as barium cerates have been widely studied as proton-conductive electrolyte. BaZrO3 displays a cubic structure with Pm-3m space group [11]. Such a symmetrical structure exhibits an excellent stability and favors the mobility of proton defects. It was shown that the substitution of the cation present on the site B with an aliovalent cation increases the density of proton defects and improves the ionic conductivity due to the formation of oxygen vacancies. The total conductivity increases with the decrease of dopant ionic radii. The most common dopant is yttrium, leading to a chemically stable compound BaZr12xYxO32δ, which has generally the highest conductivity level [25]. Kreuer et al. studied a number of alkaline dopant and found that, despite its higher ionic radius, yttrium is the most promising acceptor-dopant for BaZrO3, leading to the highest proton mobility and the lowest activation energy [26]. The stability of the protonic defect depends on the basicity of O-cation bonds, which is not affected when the dopant element is the yttrium. The optimal concentration is fixed around 15%20% [26]. The oxide system based on zirconate has both anionic and cationic conductivities under different atmospheres between 423K and 1273K. At low temperature and under wet atmosphere the protonic conductivity dominates, in contrast at high temperature and under a dry atmosphere, the oxide ion diffusion is the predominant conduction mechanism. The major drawback of doped BaZrO3 is the high sintering temperature, exceeding 1600°C, and the extended annealing times required to achieve fully dense and pure phase [27,28]. Such a temperature induces the evaporation of barium oxide BaO and the formation of Y2O3 secondary phase at the grain boundaries resulting in a high grain boundary resistivity [29,30]. Moreover, it was demonstrated that after sintering process, the obtained material is characterized by a small grain size lower than 1 μm [31]. Consequently, the performance of BZY, in term of conductivity, influenced by the microstructure, is lower than that of BCY. Another problem caused by high sintering temperature is the difficulty to obtain a thin layer electrolyte when forming a complete cell, which affects also the cell performance.

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Different solutions were proposed to promote the sinterability of barium zirconatebased material. One way to decrease the sintering temperature consists of adding a small amount of sintering aids composed of a transition metal oxide (CuO [32], ZnO [33], NiO [34,35], CaO [36], In2O3, LiNO3 [37], and TiO2 [38]). It was shown that the introduction of 4 mol.% ZnO in BaZr0.85Y0.15O32α allows to reduce the sintering temperature down to 1350°C. However, the conductivity is lower than that of BaZr0.9Y0.1O32δ by two orders of magnitude [33]. Another possible way to lower sintering temperature is the synthesis of nanometric powder by wet chemistry methods such as solgel method or citratenitrate combustion synthesis. It was shown that a density of about 95% can be achieved after sintering at 1173K using nanopowders prepared by solgel method. Thin film technology is another possibility. For example, for BZY thin film prepared by pulsed laser deposition, a protonconductivity value of 0.11 S cm21 at 500°C [39] has been reported.

4.2.3 BaCeO3BaZrO3 mixed systems A new approach to overcome the limitation of BaCeO3 and BaZrO3based material is to develop a novel electrolyte compound that combined both good chemical stability and high conductivity level. Several studies have proposed BCZY material (Ba(Ce, Zr, Y)O32δ), as a good compromise between the two Ba(Ce, Y)O3 and Ba(Zr, Y)O3 compounds [4052]. As mentioned in the previous sections, the structure of barium cerate and barium zirconate at room temperature is not the same. It was reported that BCZY material structure undergoes an evolution depending on Zr amount. Neutron and synchrotron XRD analysis was performed to study the structural evolution of BaCe0.852xZrxY0.15O32δ (0.1 , x , 0.4) with the temperature [53]. At room temperature, it was found that the symmetry increases with Zr content, leading to a high chemical stability in the presence of CO2 and H2O, while maintaining good conductivity properties of BaCeO3. For low amount of dopant (x 5 0.10.2), three successive phase transitions were observed, from monoclinic I2/m to orthorhombic Imma (Imcn) to rhombohedral R-3c and to the cubic Pm3m structure. The temperature of these phase transitions reduces as the Zr content increases: at x 5 0.30.4, only one phase transition from rhombohedral to cubic is observed. In the same way, Katharia et al. studied BaCe0.92xZrxY0.1O3 system and showed a structure evolution depending on Zr amount. For 0 , x , 0.3 the structure is orthorhombic and

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becomes cubic for content between 0.3 and 0.9. This structural modification is induced by the difference of ionic radii between Ce41 (0.87 Å) and Zr41 (0.72 Å). The chemical stability was also investigated under CO2 atmosphere. At 900°C for 2 h the stability against CO2 increases with x value. For x 5 0.1, BaCe0.8Zr0.1Y0.1O3 reacts slightly with CO2 leading to the formation of CeO2 and BaCO3. The latter disappears with x 5 0.4 [54]. According to several researchers, the most advantageous cerium to zirconium ratio in term of stability was found to be in the range of 1050 mol.%. Several studies have been carried out using different dopant elements such as erbium [55], scandium [56], neodymium [57], indium [56], and gadolinium [58]. Lv et al. [59] investigated BaCe0.45Zr0.45Ln0.1O3 (Ln 5 Y, In, Gd, Sm) system after sintering at 1600°C. The total conductivity was found to increase from 0.5 to 10 s cm21 in the order Y . Gd . Sm . In. Although yttrium is known to be the most promising dopant element, a novel strategy to further increase the conductivity and improve the stability was developed by codoping the B-site with Y31 and Yb31. Yang et al. investigated BaZr0.1Ce0.7Y0.1Yb0.1O32δ (BZCYYb) electrolyte material and the obtained results indicated an enhancement of ionic conductivity, which reaches a value of 1022 S cm21 at 550°C, while maintaining a good chemical stability in the presence of carbon dioxide (50% CO2/H2%) and dihydrogen sulfide (50 ppm) for several hours at 750°C. Similar studies have been conducted on BCZYYb material [6063]. Wang et al. showed a conductivity improvement after sintering at 1350 and 1400°C, which can be explained by an increase of grain size and a decrease in grain boundary contribution [64]. Shi et al. also studied cosubstitution for BaZr0.3Ce0.5Y0.22xYbxO32δ material by varying the Yb content (x 5 0, 0.05, 0.1, 0.15, 0.2) (Fig. 4.5A). Contrary to the solid solution BaZr0.1Ce0.7Y0.22xYbxO32δ that reaches a maximum of conductivity for x 5 0.1 (Fig. 4.5B), the conductivity decreases with the increase of the amount of ytterbium under a humidified reducing atmosphere [66].

4.2.4 SrZrO3 Perovskite strontium zirconatebased materials undergo two different structure phase transitions. From room temperature to 1023K, SrZrO3 crystallizes under orthorhombic structure with a Pnma (62) space group. Over the range of 1023K1113K, a little change of the symmetry from Pnma to Imma can be seen. Then from 1113K to 1343K, a phase

100 (A)

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(B)

0.1

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x=0 x=0.05 x=0.10 x=0.15 x=0.20

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0.003

1E-3 0.00

0.05 0.10 0.15 0.20 Concentration of Yb

0.25

1.2

1.3 1000/T (K–1)

1.4

1.5

Figure 4.5 (A) Conductivity of BaZr0.1Ce0.7Y0.22xYbxO32δ in humidified air with 0 , x , 0.2 at different temperatures [65]. (B) Total conductivity of BaZr0.3Ce0.5Y0.22xYbxO32δ under hydrogen (2% H2O) [66].

transition from orthorhombic system to quadratic one with a space group of I4/mcm is observed. It should be noted that the crystalline system is an important parameter for the proton conduction of zirconates. A decrease of the ionic radius of the cation A in ABO3 is associated with a system change from cubic to orthorhombic, resulting in an increase of the activation energy relative to proton transport. It has been shown that the proton conductivity of strontium zirconatebased materials increases with the substitution of Zr by doping elements such as Yb, Y, In, Al, and Ga. The optimal conductivities are obtained after the substitution by Yb and Y, with a value of approximately 100 times higher than that of undoped SrZrO3. The proton conductivity increases with the ionic radius of the doping elements but decreases for radii higher than that of Yb31.

4.2.5 Other proton-conductive materials 4.2.5.1 Perovskite-related material Besides simple perovskites, more complex perovskite structures with formula of A2B0 BvO6 and A3B0 B2vO9 have been considered as potential proton conductors. For both types the A and the Bv ions are divalent and pentavalent, respectively, the B0 of the first formula is trivalent whereas that of the second formula is divalent. For these kinds of materials the incorporation of proton defects can be ensured without the need of doping. The oxygen vacancies are introduced by modifying the ratio B0 /Bv, resulting in the formula of A2(B0 11xBv12x)O62δ and A3(B0 11xBv22x) O92δ types. The decrease of Bv amount in favor to that of B0 increases

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the proton defects concentration, after exposure to water vapor [67,68]. These perovskite materials were initially developed by Nowick et al., then different complex perovskite structure materials such as complex perovskite structure materials Ba3Ca12xNb22xO92d, Sr3Ca12xNb22xO92d, Ba2YSnO5.5 [69,70] were developed. It was reported that complex perovskites Ba3(CaNb2)O9 and Sr2(ScNb)O6 exhibit the same protonconductivity levels compared to that of BaCeO3 at low temperature ,400°C. Despite a good compromise between the proton conductivity and the chemical stability in the presence of CO2, the Ba2YSnO5.5 perovskite material suffers from a structural deterioration in wet atmosphere. In fact, the high concentration of O2 vacancies in the crystal lattice causes structural degradation and the presence of microcracks [71]. At present, one of the best candidate that attracts the interest of many researches is Ba3Ca1.18Nb1.82O8.73, also known as BCN18, mainly due to its good chemical stability in the presence of CO2 and H2O [72,73]. It was shown that BCN18 can incorporate up to 0.18 protons per ABO3 perovskite unit, which is comparable with that of doped barium cerate and zirconate [74,75]. Nevertheless, with a conductivity of 1023 S cm21 at 600°C in humid air, it does not seem to be the best candidate as a high-temperature proton-conductive electrolyte [76]. 4.2.5.2 Brownmillerite A2B2O5-based materials Brownmillerite-based materials are other perovskite-related materials with oxygen vacancies of formula A2B2O5 or A2BB0 O5. The brownmillerite structure can incorporate one-sixth oxygen vacancies ordered in alternating layers along the [77] direction. One of the most studied brownmillerite material is BaIn2O5, which was initially proposed as a good anionic conductor, with a conductivity comparable and even higher than that of zirconia at temperature beyond 925°C. A few years ago, brownmilleritebased material has also been studied as protonic conductor when exposed to a wet atmosphere near 300°C. The good oxide conductivity is observed at high temperature, above a phase transformation, from an ordered oxygen vacancies structure to a disordered tetragonal and cubic phase. BaIn2O5 react with H2O at low temperature to form Ba2In2O5  H2O. Around 400°C the hydrated phase starts to dehydrate. Above this temperature the brownmillerite material becomes purely anionic conductor. In the literature, several attempts have been made to stabilize the quadratic and cubic forms of barium indate at lower temperature.

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Partial cationic substitution of Ba and/or In was performed in order to enhance oxide ion and proton conductivities. For example, the substitution of Ba by La (Ba12xLax)In2O51x showed an increase of the proton conduction with the increase of La amount. The optimal conductivity, obtained with x 5 0.1, is equal to 1.12 3 1025 S cm21 at 400°C. Investigation of Ba2(In12xTix)O51x system has shown that the conductivity is decreasing, while the substitution ratio is increasing. This can be explained by the reduction of hydration process which strongly depends on the compound basicity. In fact, the increase of substitution amount induces a higher electronegativity difference between Ti41 and In31, which lowers the system basicity and consequently implies lower conductivity level. The highest proton-conductivity value, obtained with x 5 0.2 at temperature between 400°C and 600°C, is equal to 1.1 3 1023 S cm21. Above 600°C a decrease of proton conductivity is observed and can be explained by a decrease of proton transport number. We should note here, that at 600° C, the conductivity level is 10 times lower than for most protonconducting electrolytes. However, their interest consists in their great stability as proton conductors at lower temperature between 450°C and 550°C. 4.2.5.3 Phosphates, niobates, and tantalates New types of complex oxides were investigated in trying to achieve both high proton conduction and great chemical stability in operating atmosphere. The nonstoichiometry of these compounds leads to the creation of oxygen vacancies, which induce a proton conductivity. Many studies have been focusing on materials including phosphate, such as lanthanum phosphate LaPO4, which was first proposed by Norby in the 1990s. It was reported that doping LaPO4 with 5% of Sr leads to a conductivity of 3.1024 S cm21 under wet atmosphere [78]. Other studies focused in metaphosphate such LaP3O9 [7981] and La7P3O18 [82] and showed that the highest conductivity level of 5 3 1024 S cm21 is obtained with Srdoped metaphosphate [8083]. These materials have a good chemical stability in carbon rich atmosphere since the rare earth materials exhibit a lower basicity compared to that of conventional proton conductors perovskite materials. The main drawback of this compound consists in its monoclinic structure characterized by an oxygen ion distance varying from 2.43 to 3 Å [84], which can affect proton transport from a tetrahedron to another, limiting the proton conductivity.

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A new family of acceptor-doped rare earth materials were investigated by Norby as proton conductor material, with the formula RE12X AX MO4, where RE designs rare earth elements (La, Gd, Nd, Er, or Y), A indicates the dopant element (Ca, Sr, or Ba), and M is Nb or Ta, and x can vary from 1% to 5%. It was shown that niobates or tantalates undergo different polymorphic transformations depending on temperature [85]. At low temperature, they are described as a monoclinic phase corresponding to Fergusonite structure, whereas, at high temperature, they are described as a tetragonal phase corresponding to Scheelite structure. The phase transformation temperature was found to increase with the decrease of rare earth radius, and it is generally in the temperature range of 500°C820°C for the niobates [86], and between 1300°C and 1450°C for the tantalates. As illustrated in Fig. 4.6, the two different structures correspond to new structural types of proton-conducting oxides. It is important here to note that, contrary to orthotantalate, the main inconvenient of orthoniobate structure is its phase transition from monoclinic to tetragonal at 500°C, which is coupled with a volume change leading to a decrease in thermomechanical and conduction performance. These materials exhibit both ionic and electronic conduction depending on operating condition. They showed dominant proton conductivity at temperature up to 700°C. Then the proton conduction decreases with the increase of temperature and the oxygen vacancies become the dominant mobile species [4043]. (A)

(B) MO4

RE O2– c b c

a

b

a

Figure 4.6 Structures of orthoniobates and orthotantalates REMO4 (where RE 5 rare earth and M 5 Nb or Ta): (A) monoclinic and (B) tetragonal [46].

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For this kind of system a small amount of dopant element is sufficient to achieve a good conductivity level. In fact, in contrast to the perovskite material, which necessarily requires an acceptor doping to promote proton conduction, the niobate and tantalate materials yield the highest conductivity for an extremely low amount of dopant element, of only a few mole percent. It was reported that the best conductivity, of 1023 S cm21, is achieved with 1 mol.% Ca-doped LaNbO4 at 800°C. Generally, and based on lattice volume, the orthoniobate material has higher proton conductivity compared to orthotantalate one, which reaches a maximum conductivity level of about 2 3 1024 S cm21 under the same condition [42,44,45].

4.3 Electrode materials 4.3.1 Fuel electrode material The hydrogen electrode is an essential component of fuel cell or electrolyzer where, respectively, the oxidation or reduction reaction takes place. To perform this function the material must conform certain requirements and properties related to the electronic conductivity and the electrocatalytic activity. The fuel electrode must be stable under reducing atmosphere, must exhibit a good electronic and ionic conductivity, and must be porous to ensure gas diffusion. In general, the anode material used in anionic conduction fuel cells can be adopted in proton conduction ones. Two main families were studied: metals (or alloys) and ceramicmetal composites. 4.3.1.1 Metals and alloys Metals have long been considered as anode materials for fuel cells due to their good electronic conductivity as well as their excellent catalytic activity. The choice of anode material was initially oriented to certain precious metals such as platinum and palladium [4650]. The major drawback of these materials was their high cost. Thus transition metals such as nickel and cobalt were proposed as alternative materials, but the latter remains expensive. Apart from their high cost, they generate grain growth and agglomeration during sintering process, which can affect electrode performance [52,87,88]. Other materials consisting on nickel-based alloys such as NiAl and NiAg were considered as protonic ceramic fuel cell (PCFC) anode. Yamaguchi et al. measured a current density of 20 mA cm22 at 0.5 V (640°C) on a cell Pd0.6Ag0.4 (anode)/ BaCe0.9Y0.1O32δ/Ag (cathode) [89]. The obtained performances are still quite modest.

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Figure 4.7 Reaction using a metal or an O22/e2 mixed conductor.

In general, these materials are good electronic conductors but poor protonic conductors. The electrode reaction can then occur only in zones called triple points (TPB: triple phase boundary) (Fig. 4.7), namely the contact zones between the gas (arrival of H2), the metal (transport of electrons), and the electrolyte (diffusion of H1). This configuration limits the number of reaction sites and restricts the active volume of the electrode. A controlled electrode microstructure is thus required to perform the gas diffusion [87]. 4.3.1.2 Ceramic/metal composites To increase the active surface of the anode the metal electronic conductivity can be associated with a ceramic proton conductivity. When the electrode is a mixed proton and electron-conducting material, the reaction can occur in the whole contact surface between the cermet and the gas (Fig. 4.8). In the fuel cell mode the hydrogen is, thus, directly oxidized at the anode, and the proton diffuses through the anode to join the electrolyte. Several composite cermet anodes with different metallic phase (Ni, Cu, Pt, Ag, Co, and Fe) were investigated in solid oxide fuel cell (SOFC). The most commonly studied material is Nickel-electrolyte cermet. The Ni has the advantage to exhibit both good electrical conductivity and an excellent catalytic activity of hydrogen oxidation and methane steam reforming. It also presents a significant thermal expansion and a high melting point that allows the cosintering of the cermet at high temperature without cracks and constraints formation at the anode electrolyte interface. The Ni is also relatively inexpensive compared to previous mentioned metals. The use of electrolyte material as a ceramic phase in the PCFC cermet anode has shown promising results as it ensures the proton

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Figure 4.8 Anodic fuel cell reaction using a metal or an O22/e2 mixed conductor.

conductivity, extends the triple-point zone, and preserves a good dispersion of the metal phase. A range of electrolyte materials has been employed as a ceramic phase. It was reported that the BaCeO3-based composite is an unsuitable material for anodes when using hydrocarbon fuels, due to its instability in the presence of steam and CO2. However, BaZrO3-based materials have shown to be more promising as anode material owing to its good chemical stability in operating condition. It is important here to note that the relative amount of the two phases is an essential parameter to optimize the cell performance. It was determined that the nickel content to create a percolating network of Ni phase must be higher than 40 vol.%. Below this percolation threshold the cermet conductivity is purely ionic. Besides composition, many other factors related to the porosity, the grain size, and nickelceramic distribution have a strong effect on cell performance. Lee has demonstrated that the interconnectivity of porosity and the uniform distribution between conducting and porous phases is essential for an optimal electron and gas transport [90]. Typically, an oxide ionconducting anode requires high porosity volume of about 50% to maximize the three-phase boundary region and to facilitate the diffusivity of oxygen in metal phase, which is known to be negligible. On contrary, in anode for PCFC, besides being the only diffusing ion, the proton exhibits a high mobility through the two conducting phases; thus the three-phase boundary is no more necessarily required, and the porosity can be limited and produced only through the reduction of NiO phase. The microstructure of cermet anode for PCFC was extensively studied, Coors et al. demonstrated that 68 wt.% NiBCZY can be used as anode material without the need of pore former. The reduction of NiO to Ni yield to 26% porosity, which is

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sufficient to create an adapted material for operation [91]. These results are in accordance with that obtained with NiBCZYYb demonstrating degradation in PCFC performance with the increase of anode porosity [92]. Nasani et al. have compared 40 vol.% NiBZY anodes sintered at 1400°C. They concluded that cermets prepared using pore former showed higher polarization resistance Rp than these of 34% porosity fabricated without additional porogens. After reduction the NiBZY showed a bimodal pore size distribution. The nanometric size pores are related to the reduced Nimetal particles with a pocketed appearance, whereas the larger pores are attributed to the channels created between the two phases due the volume contraction induced by NiO reduction. Such microstructure is typically seen with anode cermets in PCFC and has been observed in several works [9396]. The effect of Ni amount on the porosity and the electrical conductivity was investigated by studying two anode cermets prepared by mixing BCY powder with 35 and 45 vol.% of Ni. It was reported that the open porosity increases from 22% to 48% with the increase of Ni content. The electrical conductivity was also improved and reaches a value of 500 S cm21 at 25°C with the higher Ni amount. In a symmetrical cell configuration the low area specific resistance of 0.06 cm2 is obtained with the anode containing 45 vol.% of Ni. Furthermore, the conductivity of BCY electrolyte decreases when the Ni content decreases from 45 to 35 vol.%. This could be explained by a lower anode porosity that hinders gas diffusion and consequently affects electrolyte hydration [97]. Zunic et al. studied the composition of NiBCY anode material varying from 40 to 60 wt.% of Ni content. Results have shown a good percolation pathway between the two conducting phases. The lowest polarization resistance was achieved with 40 wt.% nickel anode [98]. To highlight the influence of Ni content on the total electrical conductivity, impedance measurements were performed on NiBZY anode cermet with different volumic ratios of nickel to BZY in wet and dry 10% H2/N2. As shown in the Fig. 4.9, with 20 vol.% of nickel, the conductivity increases in wet atmosphere, suggesting a protonic conductivity contribution to total conductivity. By increasing the Ni content to 30%, a typical metallic behavior is noticed. The percolation threshold is attained at above 40 vol.% as observed in microstructural image in Fig. 4.10 [93]. It was also conclude that the uniform distribution of the two conducting phases leads to a high active surface of the TPB region.

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6

logσ (S cm–1)

3

0

20 vol.% Ni 30 vol.% Ni 40 vol.% Ni 50 vol.% Ni

–3

–6

1

2

3

1000/T (K–1)

Figure 4.9 Arrhenius plots of NiBZY anodes formed by the acetate combustion method under wet (empty symbols) and dry (filled symbols) 10% H2/N2 [93].

Figure 4.10 Scanning electron micrographs of 40% NiBZY (A) before reduction and (B) after reduction [93].

The strategy adopted by different groups to optimize cermet architecture consists of developing a multilayer anode system with different morphologies. The first layer is an electrochemical active layer, close to the electrolyte, where the hydrogen oxidation reaction takes place. It consists of small, dispersed particles of both metal and electrolyte phases to maximize the triple-point zone density and reduce the polarization activity. The second layer is a transition zone that links the active layer with the outside layer. The latter acts as a mechanical support and is characterized by higher particles and pores size, which facilitate electron collection and gas transport.

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Despite being the most widely used material in PCFC, nickel-based anode suffers from several problems. One of the major problems is the nickel agglomeration. Nickel particles tend to grow and agglomerate upon prolonged operation at high temperature. This can lead to a decrease of the active surface area and an insufficient catalytic activity for fuel reforming [99]. Another drawback that can affect anode performance is its sensibility to sulfur species, which commonly exist in the fuel [100]. H2S reacts strongly with Ni surface, lowering the active sites for fuel oxidation reaction and leading to a possible increase of anodic polarization. It has been reported that even a small concentration of H2S in fuel, lower than 20 ppm, can easily poison the nickel-based anode. Sulfur poising of NiBCZY anode was investigated by Fang and results have showed that the increase of H2S concentration in the gas environment induces to a decrease of hydrogen permeation flux through NiBCZY, which can be explained by the formation of BaS, CeO2, Ni3S2, and Ce2O2S compounds [101]. A few studies have demonstrated that proton conductingbased anode material can tolerate sulfur-containing atmosphere. An enhanced sulfur tolerance was observed with the NiBaCe0.7Zr0.1Y0.1Yb0.1O32δ (BCZYYb) anodes in comparison to NiBCZY one. This stability is related to the codoping with Y and Yb. The two dopants on the B-site work in a cooperative fashion to improve the catalytic activity for reforming or hydrocarbons oxidation as well as conversion of H2S to SO2 [65,77]. The sulfur poisoning can occur through two different stages depending on the temperature. At low temperature and with H2S flux removal the degradation is reversible and the electrocatalytic activity of the anode can be completely or partially recovered. At high temperature the poisoning is irreversible even with low poison concentration. The nickel-based cermet suffers also from a susceptibility to carbon deposition. In fact, when using hydrocarbon as a fuel, the Ni cermet electrode shows a high catalytic activity of hydrocarbon cracking, which induce the formation of graphitic filaments and carbon dissolution into the bulk Ni that blocks electrochemical reactions and deteriorates anode performance [102]. To overcome this problem the hydrocarbon can be converted to hydrogen by adding a sufficient amount of steam [103106]. It was found that a steam-to-carbon (S/C) ratio higher than 2 avoids carbon formation and deposition [107]. However, this approach depends strongly on operating temperature and may present its own disadvantages. At low temperature the steam-reforming activity is not efficient enough to suppress carbon deposition; it is then necessary to use a high steam concentration

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leading to high concentration polarization, Ni-agglomeration, and fuel dilution. Ni cermet anodes suffer also from a sensibility to oxidation when exposed to air. In fact, in real fuel cell system, an interruption of the fuel supply can accidently take place leading to Ni reoxidation [108]. Nasni et al. studied the in-situ redox cycling behavior of NiBZY and showed a microstructure degradation upon reoxidation of Ni to NiO. This can be explained by an extended growth of NiO that leads to the formation of cracks in BZY matrix and delamination of anode/electrolyte interface. These microstructure changes in anode cermet lead to a decrease of electrochemical performance. After redox cycle an increase of polarization and ohmic resistances was observed that is in agreement with microstructure damage [96]. Similar phenomena were observed with oxide ion fuel cell upon reoxidation [109]. To avoid this problem, alternative anode materials with a better oxidation resistance, such as composite alloy, were developed for oxide ionconducting SOFC [110113]. However, they are found to be less catalytically effective compared to Ni anode and microstructurally unstable [111,112]. 4.3.1.3 Mixed conductive oxides Mixed conductive oxides represent a new path for the development of PCFC anode materials. The hydrogen is directly oxidized in contact with the anode, which ensures then the transport of protons and electrons. This double property makes it possible to extend the reaction zone not only to the entire volume of the porous anode but also to the external gas/anode interface, which could favor the kinetics of the electrode reactions. Shimura et al. have shown that the Sr2TiO4 oxide (of K2NiF4 structure-type), after substitution of titanium by indium, becomes a mixed conductor (protonic and electronic) in reducing atmosphere [106]. However, the maximum conductivity obtained with the composition Sr2Ti0.93In0.07O42δ is less than 1024 S cm21 at 600°C. However, a specific surface resistance of 2.97 Ω cm2 at 900°C was measured under humidified hydrogen on the perovskite La2Sr4Ti6O192δ. Mixed conductors are an interesting way in the search for PCFC anode materials. Unfortunately, their use is rare and few works are reported in the literature.

4.3.2 Air electrode material The air electrode is the electrode where the electrochemical reaction occurs. This electrode plays an important role in cell performance, and a number of specific features are required to perform this function. In a fuel

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cell mode, it is obvious to note that a porous microstructure is essential to allow gas transport through the electrode surface and to ensure water evacuation formed during the reaction. The electrode reaction can theoretically occur only at the three-zone boundary, where electrons (metal), protons (electrolyte), and oxygen gas are present. A PCFC cathode should offer also a high stability against CO2 which can be present in air. In this part the different types of materials identified in the literature as cathode materials for PCFC will be presented: mixed oxide ion electronic conductors, mixed protonelectronproton conducting oxides, and composite proton ion and electron-conducting materials. 4.3.2.1 Mixed O22/e2 conductor It has been demonstrated that the use of mixed oxygen ion and electronic conducting material as a cathode provided better performance by extending the reaction zone to the entire contact area between the electrode and the gas [114,115] (Fig. 4.11). The most studied cathode material for oxide ion fuel cell, which was also proposed as cathode material for PCFC, is La12xSrxMnO32d. The latter was found to have a satisfactory electronic conductivity of 130 S cm21 at 700°C but suffers from a poor ionic conductivity. Its performance as cathode for PC-SOFC remains modest [76]. Cobaltite-based cathode material of formula La12xSrxCoO32d (LSC) exhibits a high electronic conductivity of 1000 S cm21 at 600°C; however, oxygen-diffusion properties for this material are still poor. A better performance was obtained by substituting a part of cobalt with iron. The best compromise is obtained with the composition La0.6Sr0.4Fe0.8Co0.2O32d (LSFC). However, this material is rarely used for PCFC due to its low oxygen substoichiometry [116]. Iwahara et al. proposed a number of mixed oxygen ionic and electronic conducting cathode materials for

Figure 4.11 Reaction using a metal or an O22/e2 mixed conductor.

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BaCe0.9Sm0.1O3 electrolyte-based fuel cell such as La0.6Ba0.4CoO3, Ca0.85Ce0.15MnO3, and La0.6Ba0.4MnO3. Among these, La0.6Ba0.4CoO3 showed the best performance in terms of stability. The maximum short-circuit current density was about 900 mA cm22 at 1273K, and the polarization resistance was low [3]. More promising cathode for BCY electrolyte, obtained by replacing La with Pr, was proposed by Hibino et al. The overpotential of Ba0.5Pr0.5CoO3 cathode at 600°C was 53 mV at 200 mA cm22 [117]. Cathodes material analogous to that used for oxide ion fuel cell SOFC, such as La12xSrxMnO3 (LSM) or Sm0.5Sr0.5CoO3 (SSC), may not be adapted for PCFC since the active zone for oxygen reduction is limited to the interface between the electrolyte and the cathode. Indeed, the oxygen reduction occurs at the electrode surface; then oxide ions diffuse through the electrode. At the internal interface, between the electrolyte and the electrode, problems of produced water evacuation can take place, causing layer delamination. The electrode performances are thus less effective in comparison to those of oxygen ion fuel cell SOFC [110,118,119]. Moreover, some cathode materials based on barium, such as BSCF, extensively used in oxide ion fuel cell, were tested in BaCe0.9Y0.1O2.95 electrolyte-based fuel cell and found to be incompatible as cathode, due to the inter diffusion of Ba from the electrolyte to the cathode leading to an increase of the cell ohmic resistance. The highest peak power density is only equal to 550 and 100 mW cm22 at 700°C and 400°C, respectively [118121]. 4.3.2.1 Composite ceramic/mixed conductor (O22/e2) One of the considered solutions to improve the electrolyte/cathode interface is to introduce a proton-conductive ceramic to a mixed oxygen ionic and electronic conducting cathode. In this case the water formation reaction takes place over the entire surface of contact between the protonconducting ceramic and the mixed conducting material (Fig. 4.12). Several studies have been carried out using composite material as cathode for PCFC [122,123]. Ma et al. studied the performance of a cathode for PCFC formed with La0.5Sr0.5CoO32δ as mixed oxide ion and electronic conducting material and BaCe0.8Gd0.2O2.9 as a proton-conducting material. The maximal power density obtained at 700°C is about 355 MW cm22 [124]. A similar power density was reported by Pang et al. with a composite of formula Ba0.5Sr0.5CoO0.8Fr0.2O32δBaCe0.8Sm0.2O2.9. Wu et al. studied BaCe0.8Sm0.2O3/Sm0.5Sr0.5CoO3 as composite cathode material. The ceramic/mixed conductor ratio was investigated and results demonstrated that a proton-conducting material (BaCe0.8Sm0.2O3) content of 40 wt.%

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Figure 4.12 Reaction using composite cathode made of a proton conductor phase and an O22/e2 mixed conductor phase.

offers the best electrode performance with an interfacial polarization resistance of about 0.67 Ω cm2 at 600°C. For higher contents, this resistance increased, whereas the bulk resistance remains constant. The composite fired at 1050°C exhibits the highest performance, with the lowest interfacial polarization of 0.21 Ω cm2 and the greatest power density of 0.24 W cm22 at 700°C. Improved cell performance was achieved using a composite made from the mixed conductor phase Sm0.5Sr0.5CoO3 and a novel proton conducting material of composition Ba(Zr0.1Ce0.7Y0.2)O3. Firing the composite at 1000° C generates a higher number of active sites and facilities electrochemical reactions. Results showed the appearance of two additional phases resulting from the interaction between the conducting materials: a good proton-conducting phase (Sm2Zr2O7) and a high mixed electronic and oxygen ionconducting phase (BaCoO32δ). The maximum power densities are about 725, 598, 445, and 272 mW cm22 at 700°C, 650°C, 600°C, and 550°C, respectively [118]. A new composite material formed with both O22/e2 La0.6Sr0.4Co0.2Fe0.8O3 and H1/e2 BaZr0.5Pr0.3Y0.2O3 (BZPY30) was developed by Fabbri et al. and showed improved performance compared to the one prepared with a proton conductor BaZr0.7Pr0.1Y0.2O3 (BZPY10). The polarization resistance was found to be smaller due to an extended active area created with the mixed conductor BZPY30 material [125]. 4.3.2.3 Single-phase mixed triple conducting electrode material As shown previously, composite cathode materials for PCFC system limit the electrochemically active sites to the interface between the cathode and the proton-conducting electrolyte. To avoid this limitation and enhance cell performance an alternative approach for cathode material has been developed. The use of a mixed protonelectron conducting material has

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been suggested to perform the electrode reaction on the entire gas/cathode interface. In this case, protons cross the membrane to reach the cathode where the electrons also circulate: the water is then formed at the gas/cathode interface, which would favor its evacuation a priori (Fig. 4.13). The first studies were performed with BaCeO3-based cathode material. Initially, Mukundan et al. investigated the electrochemical properties of Pr-doped barium gadolinium cerate. For a Pr-concentration higher than 40 mol.% an increase of the total conductivity is observed due to an enhancement of the p-type electronic conductivity. The highest total conductivity and the lowest overpotential are equal to 0.75 S cm21 and 0.47 V at 800°C in dry air, respectively, and they are obtained with Ba (Pr0.8Gd0.2)O2 [126]. The same material was also studied by Magrasó et al. [127] and showed mainly electronic conduction and a minor proton conduction even in wet atmosphere. Zaho et al. investigated the performance of a cathode based on BaCeO3 matrix but doped with bismuth. Results showed a chemical stability improvement under wet atmosphere compared to BaCeO3 and a total conductivity increase. The highest total conductivity obtained with BaCe0.5Bi0.5O3 is 0.1 S cm21 in air at 600°C and the overpotential is about 70 mV at 800°C in air at a current density of 100 mA cm22. However, a decrease in proton conductivity was observed with the increase of Bi content due the decrease of oxygen vacancies concentration [128]. An enhancement in power density was obtained with BaCe0.5Fe0.5O32δ compared to BaCe0.5Bi0.5O3. However, both values (192 and 125 mW cm22 at 600°C, respectively) remain low.

Figure 4.13 Reaction using a single-phase mixed triple conducting cathode.

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Fabbri et al. tested different dopant elements such as Sm, Eu, and Er for barium cerate proton conductor cathode. BaCe0.9Yb0.1O3 was selected as the best candidate with the highest conductivity under both dry and wet atmospheres. However, the electron conductivity decreases in the presence of water vapor, which corresponds to cathode’s operating condition, leading to a large area specific resistance (ASR) [122]. A new mixed triple conducting cathode material BaPr0.8In0.2O3 has been recently developed by Wang et al. and used in Ce0.7Y0.1Yb0.1O32δ (BZCYYb) electrolytebased fuel cells. The study has demonstrated a satisfactory tolerance to CO2 and H2O and great electrochemical performances with a maximum power density of 688 mW cm22 at 750°C and a power output at a cell voltage of 0.7 V at 600°C for 100 h [129]. Another promising cathode material, NdBa0.5Sr0.5Co1.5Fe0.5O5, has recently been reported and showed high power densities of 1.71, 1.37, 1.05, and 0.69 W cm22 at 1023K, 973K, 923K, and 873K, respectively [130]. A further recent cathode material, BaCo0.4Fe0.4Zr0.1Y0.1O32d (BCFZY0.1), was reported by Duan et al. Cell performances have been investigated at intermediate to low temperature and have found to be the greatest so far. Power density reaches high values of 455 and 142 mW cm2 at 500°C under H2 and CH4, respectively. The operation was possible even at 350°C, and high performances were maintained for 1400 h without degradation [131].

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[103] A.M. Sukeshini, B. Habibzadeh, B.P. Becker, C.A. Stoltz, B.W. Eichhorn, G.S. Jackson, et al., Electrochemical oxidation of H2, CO, and CO/H2 mixtures on patterned Ni anodes on YSZ electrolytes, J. Electrochem. Soc. 153 (4) (2006) A705A715. [104] E.S. Hecht, et al., Methane reforming kinetics within a NiYSZ SOFC anode support, Appl. Catal. A: Gen. 295 (1) (2005) 4051. [105] H. Zhu, R.J. Kee, V.M. Janardhanan, O. Deutschmann, D.G. Goodwin, et al., Modeling elementary heterogeneous chemistry and electrochemistry in solid-oxide fuel cells, J. Electrochem. Soc. 152 (12) (2005) A2427A2440. [106] H. Zhu, R.J. Kee, et al., Modeling distributed charge-transfer processes in SOFC membrane electrode assemblies, J. Electrochem. Soc. 155 (7) (2008) B715B729. [107] A. Kromp, S. Dierickx, A. Leonide, A. Weber, E. Ivers-Tiffée, et al., Electrochemical analysis of sulphur-poisoning in anode-supported SOFCs under reformate operation, ECS Trans. 41 (33) (2012) 161169. [108] M. Ettler, H. Timmermann, J. Malzbender, A. Weber, N.H. Menzler, et al., Durability of Ni anodes during reoxidation cycles, J. Power Sources 195 (17) (2010) 54525467. [109] T. Klemensø, C. Chung, P.H. Larsen, M. Mogensen, et al., The mechanism behind redox instability of anodes in high-temperature SOFCs, J. Electrochem. Soc. 152 (11) (2005) A2186A2192. [110] E. Fabbri, D. Pergolesi, E. Traversa, et al., Electrode materials: a challenge for the exploitation of protonic solid oxide fuel cells, Sci. Technol. Adv. Mater. 11 (4) (2010) 044301. [111] A. Atkinson, et al., Advanced anodes for high-temperature fuel cells, Nat. Mater. 3 (1) (2004) 1727. [112] X.-M. Ge, S.-H. Chan, Q.-L. Liu, Q. Sun, et al., Solid oxide fuel cell anode materials for direct hydrocarbon utilization, Adv. Energy Mater. 2 (10) (2012) 11561181. [113] A. Mohammed Hussain, J.V.T. Høgh, T. Jacobsen, N. Bonanos, et al., Nickel-ceria infiltrated Nb-doped SrTiO3 for low temperature SOFC anodes and analysis on gas diffusion impedance, Int. J. Hydrogen Energy 37 (5) (2012) 43094318. [114] F. Mauvy, et al., Electrode properties of Ln2NiO41δ (Ln 5 La, Nd, Pr) AC impedance and DC polarization studies, J. Electrochem. Soc. 153 (8) (2006) A1547A1553. [115] A. Tarancón, M. Burriel, J. Santiso, S.J. Skinner, J.A. Kilner, et al., Advances in layered oxide cathodes for intermediate temperature solid oxide fuel cells, J. Mater. Chem. 20 (19) (2010) 37993813. [116] J. Dailly, S. Fourcade, A. Largeteau, F. Mauvy, J.C. Grenier, M. Marrony, et al., Perovskite and A2MO4-type oxides as new cathode materials for protonic solid oxide fuel cells, Electrochim. Acta 55 (20) (2010) 58475853. [117] T. Hibino, A. Hashimoto, M. Suzuki, M. Sano, et al., A solid oxide fuel cell using Y-doped BaCeO3 with Pd-loaded FeO anode and Ba0.5Pr0.5CoO3 cathode at low temperatures, J. Electrochem. Soc. 149 (11) (2002) A1503A1508. [118] L. Yang, C. Zuo, S. Wang, Z. Cheng, M. Liu, et al., A novel composite cathode for low-temperature SOFCs based on oxide proton conductors, Adv. Mater. 20 (17) (2008) 32803283. [119] P. Holtappels, U. Vogt, T. Graule, et al., Ceramic materials for advanced solid oxide fuel cells, Adv. Eng. Mater. 7 (5) (2005) 292302. [120] P. Batocchi, F. Mauvy, S. Fourcade, M. Parco, et al., Electrical and electrochemical properties of architectured electrodes based on perovskite and A2MO4-type oxides for protonic ceramic fuel cell, Electrochim. Acta 145 (2014) 110.

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[121] R. Peng, T. Wu, W. Liu, X. Liu, G. Meng, et al., Cathode processes and materials for solid oxide fuel cells with proton conductors as electrolytes, J. Mater. Chem. 20 (30) (2010) 62186225. [122] E. Fabbri, T. Oh, S. Licoccia, E. Traversa, E.D. Wachsman, et al., Mixed protonic/ electronic conductor cathodes for intermediate temperature SOFCs based on proton conducting electrolytes, J. Electrochem. Soc. 156 (1) (2009) B38B45. [123] T. Wu, R. Peng, C. Xia, et al., Sm0.5Sr0.5CoO32δBaCe0.8Sm0.2O32δ composite cathodes for proton-conducting solid oxide fuel cells, Solid State Ionics 179 (27) (2008) 15051508. [124] Q. Ma, R. Peng, Y. Lin, J. Gao, G. Meng, et al., A high-performance ammoniafueled solid oxide fuel cell, J. Power Sources 161 (1) (2006) 9598. [125] E. Fabbri, L. Bi, D. Pergolesi, E. Traversa, et al., High-performance composite cathodes with tailored mixed conductivity for intermediate temperature solid oxide fuel cells using proton conducting electrolytes, Energy Environ. Sci. 4 (12) (2011) 49844993. [126] R. Mukundan, P.K. Davies, W.L. Worrell, et al., Electrochemical characterization of mixed conducting Ba(Ce0.82yPryGd0.2)O2.9 cathodes, J. Electrochem. Soc. 148 (1) (2001) A82A86. [127] A. Magrasó, R. Haugsrud, M. Segarra, T. Norby, et al., Defects and transport in Gd-doped BaPrO3, J Electroceram. 23 (1) (2009) 8088. [128] Z. Hui, P. Michèle, et al., Preparation, chemical stability, and electrical properties of Ba(Ce12xBix)O3 (x 5 0.00.5), J. Mater. Chem. 12 (12) (2002) 37873791. [129] Z. Wang, M. Liu, W. Sun, D. Ding, Z. Lü, M. Liu, et al., A mixed-conducting BaPr0.8In0.2O32δ cathode for proton-conducting solid oxide fuel cells, Electrochem. Commun. 27 (2013) 1921. [130] J. Kim, et al., Triple-conducting layered perovskites as cathode materials for proton-conducting solid oxide fuel cells, ChemSusChem 7 (10) (2014) 28112815. [131] C. Duan, et al., Readily processed protonic ceramic fuel cells with high performance at low temperatures, Science 349 (6254) (2015) 13211326.

CHAPTER 5

Multilevel modeling of solid oxide electrolysis Jakub Kupecki1,2, Luca Mastropasqua3, Konrad Motylinski1,4 and Domenico Ferrero5 1

Department of High Temperature Electrochemical Processes (HiTEP), Institute of Power Engineering, Warsaw, Poland National Fuel Cell Research Center (NFCRC), University of California, Irvine, Irvine, CA, United States 3 Advanced Power and Energy Program, University of California, Irvine, Irvine, CA, United States 4 Institute of Heat Engineering, Warsaw University of Technology, Warsaw, Poland 5 Department of Energy, Polytechnic University of Turin, Torino, Italy 2

Contents 5.1 Introduction 5.2 Theoretical background 5.2.1 Key performance indicators 5.3 Materials and micro-electrochemistry 5.3.1 Kinetic models 5.3.2 Global kinetics 5.3.3 Elementary mass-action kinetics 5.3.4 Equivalent circuit kinetics 5.4 Multidimensional approaches to cell/stack modeling 5.4.1 Zero-dimensional models 5.4.2 One- and two-dimensional models 5.4.3 Three-dimensional models 5.5 Typical operating conditions 5.6 Thermal management of solid oxide electrolyzer stacks 5.7 Thermal management of solid oxide electrolyzer through the use of heat pipes 5.8 System analysis and applications 5.8.1 Operation of solid oxide electrolyzer as a part 5.8.2 Solid oxide electrolyzer integration with thermal and electric sources Acknowledgment References

123 125 125 128 128 129 130 131 132 133 137 138 139 143 149 154 154 156 159 159

5.1 Introduction The sustainable deep decarbonization of the power and industrial sectors hinges on the widespread deployment of low-carbon and renewable Solid Oxide-Based Electrochemical Devices DOI: https://doi.org/10.1016/B978-0-12-818285-7.00005-8

© 2020 Elsevier Inc. All rights reserved.

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technologies—mainly solar and wind. However, the well-known mismatch between production and demand—due to the naturally intermittent nature of the energy resource—calls for massive deployment of large-scale and longterm energy storage. A sustainable option could be found through the production of easy-to-store gaseous (e.g., hydrogen and synthetic fuels) or liquid (e.g., methanol, dimethyl ether—DME, or other synthetic hydrocarbons) energy vectors. One of the enabling technologies in the search for ways to decouple the production of renewable electricity and the consumption of renewable-based products is electrolysis. In most cases, fuel cell technology may be used in reverse mode to operate an electrolysis system. Therefore renewable electricity can be used as an input energy source to produce valuable chemicals, using mainly water and CO2 as input streams. High-temperature electrolysis based upon solid fast ion-conducting oxides specifically offers numerous advantages related to system integration with the gas and electricity network, the energy storage, and transportation market and ultimately with the industrial and manufacturing sector. In fact, the possibility of operating at high temperature broadens the applicability range of these systems to electrochemically split both water and biogenic or fossil CO2 in order to produce a carbonaceous feedstock. This characteristic is particularly interesting, as it could produce a carbonbased syngas (from renewable energy vectors) for use in a chemical postprocessing island (e.g., FisherTropsch for synthetic diesel and HaberBosh ammonia process) with a view to producing renewable gaseous or liquid chemicals for the industrial, transport, and power sectors. Due to the wide range of possible products, this production paradigm is often referred to as power-to-X. The specific operating conditions for solid oxide electrolyzers (SOEs) require a raft of analyses ranging from electrochemistry kinetics, material selection and degradation, and cell and stack testing and modeling, to system integration and cross-sectoral coupling analyses. This chapter summarizes the theoretical background needed for a basic understanding of SOE operation, sets out the main modeling requirements, and defines key performance indicators (KPIs). Subsequently, the literature state-of-the-art related to modeling methodologies from microelectrochemistry and kinetic models up to system-level analyses are reviewed and discussed. In particular, the research challenges are

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highlighted and accompanied by a discussion of modeling strategies to address them.

5.2 Theoretical background 5.2.1 Key performance indicators In order to establish a common ground for solid oxide electrolyzer cell (SOEC) systems, for the purpose of comparing them with other competitive technologies for hydrogen or syngas production, a general set of KPIs must be created. Table 5.1 summarizes three categories of KPIs evaluating in turn thermodynamic, electrochemical, and economic performances. The definitions are introduced in general form in order to be agnostic with respect to the specific system configuration considered. A set of KPIs for SOEs is relevant when modeling components and systems given their intrinsic thermodynamic, multienergy nature, that is, a thermodynamic system, which uses and produces multiple types of energy sources (e.g., heat, electricity, and hydrogen). Eq. (5.1) states the general first law of efficiency for an SOE system, focusing on the chemical power content of the product stream— m _ X LHVX —(i.e., hydrogen and syngas) divided by the power required from the different feedstocks employed (i.e., heat and electricity) for the electrolysis reaction. Eq. (5.2) reflects the same concept but applied only to _ th;tot and W _ el;tot take into account the consumption an SOE stack. In fact, Q of thermal and electric power of the whole system, hence considering auxiliary electric loads or other external sources of high-temperature heat [e.g., _ th;red concentrated solar power (CSP) and nuclear]. On the other hand, Q _ el;red only refer to the thermal and electric power needed for the and W _ th;red is defined in the steam reduction reactions within the SOEC stack. Q following equation: _ th;red 5 Q

j j ðΔHR 2 ΔG Þ 5 jðVtn 2 EN Þ T ΔS 5 ze F ze F

(5.9)

Eq. (5.3) is particularly useful as a comparative term with other technologies for the production of electro fuels—such as polymer electrolyte membrane (PEM) electrolysis coupled with photovoltaic (PV)—as it evaluates the electric energy consumption specific to the primary energy of fuel produced. However, for high-temperature electrolysis the comparison must be performed while keeping in mind that electricity is not the only input energy stream to the system—as explained in Eq. (5.1).

Table 5.1 Key performance indicators for thermodynamic, electrochemical, and economic solid oxide electrolyzer (SOE) performance evaluation. Thermodynamic KPIs

ηI 5

m_ X LHVX _ th;tot 1 W _ el;tot Q

ηSOEC 5 πX 5

m_ X LHVX _ th;red 1 W _ el;red Q

1 ηel;SOEC

5

_ el W m _ X LHVX

System first law efficiency/%

(5.1)

SOE stack first law efficiency/%

(5.2)

SOE stackspecific electric energy consumption/kWh kgX21

(5.3)

Voltage efficiency/%

(5.4)

Cell voltage degradation rate/% 1000 h21

(5.5)

Levelized cost of hydrogen equivalent/h MWh21

(5.6)

Specific stack area per unit mass of X produced/m2 (kg s)21

(5.7)

Year-long capacity factor/%

(5.8)

Electrochemical KPIs

  1=2 i     h 1=2 2 ΔG=ze F 1 RT =ze F ln xH2 xO2 =xH2 O 3 p=p0 EN ηV 5 5 Vcell Vcell δV 5

Vcell ðt 5 1khÞ 2 Vcell ðt 5 0Þ Vcell ðt 5 0Þ

Economic KPIs

LCOHeq 5

KPI, Key performance indicator.

ðCinv 1 CO&M 1 Ctax Þ ΠH2 eq aX 5

A m_ out X

CF 5

Heq 8760

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Electrochemical KPIs provide insight into the performance of the single cell or stack in design conditions or during long-term operation. In particular, the voltage efficiency reported in Eq. (5.4) evaluates the magnitude of electrochemical losses compared to reversible operation. In addition, cell voltage degradation (reported in Eq. 5.5) is of great importance, as its minimization has a profound effect on the lifetime of the stack and thus on the overall economics of the system. Levelized cost of hydrogen equivalent (Eq. 5.6) is used to provide a unique KPI to compare the economic performance of various hydrogen (or synthetic fuels) production technologies. The discounted present value of investment, O&M, and tax costs along the plant lifetime is calculated specific to the discounted value of primary energy contained in the fuel produced. In addition, it should be borne in mind that SOE systems are characterized by a predominantly capital-intensive economic function. In other words, the cost associated with the purchase and installation of physical components (SOE stack, inverters, gas purification sections, and hydrogen storage) outweighs all others, such as O&M costs [This might change depending on the size of the system. The smaller the system, the bigger the contribution of O&M costs will be compared to the total levelised cost of hydrogen (LCOH.)]. Moreover, the lion’s share of the capital cost derives from the stack itself, as depicted in Fig. 5.1. Eq. (5.7) introduces the concept of specific active area of the SOE stack per unit mass of fuel product. As per many electrochemical systems, the common reference is per unit of stack area; this becomes an effective parameter to compare the power densities and overall utilization of the SOE with respect to other electrolyzers. Eq. (5.8) reports the capacity factor (CF) of the system. SOEs may be operated in conjunction with renewable energy source (RES) plants— such as solar or wind—and serviced in such a way as to provide electric grid support at a specific time of day or year (for seasonal energy storage). Therefore the specific type of operation may considerably reduce the operating hours during the year, thus increasing overall cost due to stranded assets. In order to maximize the CF of the system, appropriate control strategies and optimized dynamic coupling with RES are needed (see Section 5.8.2).

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Figure 5.1 Cost breakdown of SOE hot box. SOE, Solid oxide electrolyzers. Adapted from B.D. James, A.B. Spisak, W.G. Colella, Manufacturing cost analysis of stationary fuel cell systems,2016.,https://www.sainc.com/assets/site_18/files/publications/sa% 202015%20manufacturing%20cost%20and%20installed%20price%20of%20stationary %20fuel%20cell%20systems_rev3.pdf.. [1].

5.3 Materials and micro-electrochemistry 5.3.1 Kinetic models In SOECs, electrochemical reactions occur at electrode level and are governed by reaction kinetics, which depend on complex and interconnected phenomena, such as adsorption/desorption of gas molecules on electrode surfaces, dissociation/transport of adsorbed species, charge-transfer reactions, and heterogeneous reactions. Several approaches for modeling the kinetic mechanisms of electrochemical reactions have been developed for solid oxide fuel cell (SOFC) technology, but they are also applied in respect of electrolysis operation of solid oxide cells (SOCs). In fact, from the angle of reaction kinetics, the main difference between SOFC and SOEC consists of the different reaction mechanisms, while the modeling approaches adopted in the literature are identical. Several different and discordant mechanisms for water and carbon dioxide splitting were reported in the literature and readers are referred to Kleiminger [2] for a recent review on the topic.

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This section summarizes the main approaches followed for modeling electrochemical reaction kinetics in SOCs, with reference to literature examples for SOECs. Modeling examples reported in the literature can be divided into three main approaches: by global kinetics rate laws, elementary mass-action kinetics, and equivalent circuits.

5.3.2 Global kinetics In the first approach the electrode reaction mechanism is assumed to be controlled by a single charge-transfer reaction, a condition that enables global rate laws to be applied to describe the electrochemical kinetics at the electrode. Typically, the ButlerVolmer equation is the equation used as the global rate law, relating to current density and electrode activation overpotential [3]:      ne Fηact ne Fηact i 5 i0 exp αf 2 exp 2αb (5.10) RT RT In this formulation the faradic current density is a function of exchange current density—i0—and activation overpotential—ηact—of the electrode reaction through exponential terms, including symmetry parameters of forward/backward reactions—αf and αb—and the number of electrons transferred—ne—in the limiting charge-transfer step. The exchange current density is the parameter that depends on the charge-transfer kinetics and electrode microstructure, usually expressed (see Eq. 5.11) as the product of an Arrhenius term and a pressure term, the latter usually expressed as the product of partial pressures pk of reactants, normalized to a reference pressure and raised to a dimensionless exponent nk.     Eact pk nk i0 5 γUexp 2 (5.11) L RT k pk;ref Eq. (5.11) is a semiempirical relation for the exchange current density, which shows its dependency on the activation energy of the electrode reaction, Eact, and on a preexponential parameter γ, which has been reported to be dependent on materials, microstructural parameters, and also on the temperature, and is usually determined by fitting experimental data. An even simpler approach to kinetic modeling by global rate laws is to assume a linear equation relating activation overpotential and current

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density, including all the reaction information in an exchange current density term [4]. Most of the SOEC models are based on global rate laws and apply a ButlerVolmer (or linear) formulation for the activation overpotential combined with a polarization equation that determines the cell voltage as the sum of equilibrium cell potential with all the overpotentials (i.e., activation, ohmic, and concentration). Examples of this application to H2O electrolysis, CO2 electrolysis reversible SOC (rSOC) operation, and coelectrolysis are given in Refs. [47]. Studies of Grondin et al. [8,9] demonstrated that the assumption of a one rate-limiting step in the reaction mechanism described by a ButlerVolmer equation fails to predict water reduction overpotential on Nicermet for low water content. The authors showed that a two rate-limiting steps mechanism, also considering the adsorption of water, implemented in a continuum model provided a better fitting of experimental data.

5.3.3 Elementary mass-action kinetics In order to overcome the limitations of the global rate law approach, elementary kinetics models have been developed. This approach, first developed for SOFCs [10,11], is based on the description of all the electrochemical (and also chemical) processes occurring in the cell by elementary reactions and in the formulation of fundamental mass-action kinetics for the rates of the reactions. The faradic current density produced by the charge-transfer reactions is calculated as the difference between the rates of the electrochemical reactions occurring at the electrodes [12]:    ! X β a FEa β c FEc i5F ka ðT Þ L ai exp 2 kc ðT Þ L ai exp 2 RT RT i;a i;c i (5.12) where ka,c are the anodic/cathodic rate constants, usually expressed in the Arrhenius form, ai are the activities of the reactants/products, β a,c are symmetry coefficients, and Ea,c is the electrode/electrolyte potential difference at the electrode interfaces. This modeling approach allows calculating the current density without needing to directly evaluate equilibrium potential and activation overpotential. In the models the elementary electrochemical kinetics are usually coupled with elementary kinetics of heterogeneous chemical reactions and surface transport of species. Zhu et al. [13] developed a SOFC model based on elementary kinetics, reduced to a modified

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ButlerVolmer formulation by deriving theoretical expressions of the exchange current density from the reaction mechanism. This simplified approach has been widely applied in SOFC models and has been adopted several times for SOECs. In particular, the modified ButlerVolmer formulation has been applied for H2O electrolysis [14], CO2 electrolysis [15], and coelectrolysis [16,17], while a pure elementary kinetics approach was adopted in [18] for CO2 reduction and in [19] for coelectrolysis, the latter work applying a modified ButlerVolmer only at the anode. In most SOE models, however, the calculation of the electrochemical active thickness (EAT) is usually not performed and all the electrochemical reactions are assumed to take place at the zero-dimensional (0D) interphase between the electrode and electrolyte. Distributed charge-transfer models is an area of active research for SOFCs [2022], while it has still to be appropriately addressed for SOECs. A clear understanding of the EAT and electrokinetic mechanism would in fact be a valuable contribution, especially with regard to the applications of coelectrolysis and the competitive thermal and chemical effects of CO2 reduction and reverse watergasshift (WGS) reactions.

5.3.4 Equivalent circuit kinetics Another modeling approach reported in the literature for the study of SOEC kinetics is by equivalent circuits. This approach is strongly related to electrochemical impedance spectroscopy (EIS) measurements on cells and electrodes and is intended as a tool for the interpretation of experimental EIS spectra for diagnosis applications. On the other hand, the other kinetics approaches are applied in models that globally simulate the performance of SOCs through currentvoltage characteristics, thus relating to performance measurements by polarization. The EIS technique is based on providing a voltage/current perturbation signal as input to an SOC and analyzing the frequency response of the SOC (graphically represented in Nyquist or Bode diagrams), which corresponds to the impedance of the cell determined by all the electrochemical and transport process within the cell. An equivalent circuit model describes the SOC with a series and/or parallels of impedance elements, each related to a particular phenomenon occurring in the cell, such as ohmic losses due charge transport, gas diffusion, charge transfer, species adsorption/desorption, and stray impedances due to measurement devices. Two types of elements are usually used in equivalent circuit

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modeling: lumped elements—such as resistance, capacitance, and inductance—and frequency-dependent elements, such as constant phase and Gerischer and Warburg elements. It is outside the scope of this chapter to provide deep insight into equivalent circuit modeling techniques. A complete review on equivalent circuit modeling and validation methods can be found in the work by Huang et al. [23] for SOFCs, while the following paragraph contains some relevant examples of equivalent circuit models applied for the analysis SOEC electrochemical reaction kinetics analysis. Dasari et al. [24] and Pan et al. [25] investigated the NiYSZ electrode performance by EIS and equivalent circuits in both SOFC and SOEC operation (H2/H2O mixtures), obtaining similar results. The works reported the predominance of high-frequency impedance in fuel cell mode, related to charge-transfer kinetics, and of low-frequency phenomena due to gassolid interaction (i.e., adsorption/desorption and species dissociation) in electrolysis. The reaction pathway identified for water electrolysis is thus different from a simply “reversed” hydrogen oxidation mechanism, with charge-transfer kinetics being more limiting for the hydrogen oxidation path, while water reduction is limited by species transport in the reacting interface. Shin et al. [26] modeled an NiYSZ/ YSZ/LSM cell (steam electrolysis) by equivalent circuits with Gerischer elements, identifying the separated contribution of ohmic losses, chargetransfer impedance at the NiYSZ electrode, surface diffusion and reaction impedance at the LSM electrode, and gas-phase transport impedance at the NiYSZ electrode. The study showed opposite and compensating polarization behaviors of cathode and anode in electrolysis. The cathodic charge-transfer losses increased with the current due to combined diffusionreaction limiting processes related to gas density decrease with hydrogen production, while the anodic losses decreased due to increased oxygen activity. Several studies also modeled SOECs by equivalent circuits for analysis of degradation phenomena [2729].

5.4 Multidimensional approaches to cell/stack modeling Numerical models used for prediction of SOE cell operation are crucial tools in understanding and analyzing the influence of various parameters (e.g., geometrical, thermodynamic, and kinetic) on the electrochemical performance and overall development of SOE technology. Models currently used simulate with high precision the operation of SOCs from

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mesoscale processes, capturing phenomena occurring at the level of separate layers of the cell, to macroscale processes, where the performance of a complete power systems based on SOC technology is analyzed. However, each of the available modeling methodologies involves some approximations and/or limitations, which might result in various types of errors and inaccuracies in the results they generate. Therefore depending on the assumptions, details, and type of expected results, the appropriate modeling method must be chosen [30,31]. In addition, proper calibration and validation of a given numerical platform is crucial in order to guarantee high convergence of results from computational simulations compared to real experimental data. Commonly used models of single cells and complete SOE stacks are based on mass and energy balances, with particular regard to electrochemical reactions, ionic and electronic conductivities of cell layer materials, and gas diffusion. Depending on the problem analyzed, 0D to threedimensional (3D) models are used, with each method being characterized by advantages and disadvantages [32].

5.4.1 Zero-dimensional models In cases where numerical activities focus on SOE performance and its optimization, discrete 0D models are used [33,34]. In this methodology, separate modules are treated as black boxes, where the key elements are inlet and outlet parameters. Usage of 0D numerical tools is usually correlated with implementation into methodology empiric and semiempiric equations in order to enhance the accuracy of the results generated for specific cases. 0D or black-box models are usually sufficient when the aim of the analysis is the study of thermodynamic performance of complex systems, especially during operation in off-design or in dynamic conditions. However, such models often neglect spatial configuration and some of the processes in order to achieve low-computational cost with slightly higher prediction errors for off-design analysis. Despite all the research on SOE since last 50 years, few articles are available in the open literature concerning its modeling. SOE numerical tools are strongly correlated with SOFC-based mathematical methodologies, due to the comparable gas diffusion mechanisms and reversible but similar electrochemical behavior. A number of models used in the studies of SOE were originally developed to investigate SOFCs. Njodzefon et al. [35] proposed a 0D, isothermal, and stationary model for predicting currentvoltage characteristics of

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anode-supported SOFC, which was modified and calibrated to perform calculations in electrolysis mode. The model was validated on a reversible Ni/YSZYSZGDCLSCF square button cell. Petipas et al. [33] proposed a numerical tool to simulate an SOE-based system operated at different power loads for compressed hydrogen production without an external heat source. They presented a 0D model composed of SOE unit and balance of plant, operating close to the thermoneutral point with system efficiency of 91% (HHV). Iora and Chiesa [36] designed a 0D model of a system where pure oxygen was generated, based on the integration of an SOFC and SOE. In the proposed methodology, electricity, heat, and steam from the SOFC module were delivered to the SOE part. Aspen ONE is software that is commonly used to design and create 0D models of SOFC and SOE modules. Hauck et al. [37] and Mottaghizadeh et al. [38] proposed models of power systems based on rSOCs using Aspen Plus software with various levels of detail. Numerical activities focused on optimization of specific system designs, and the model validation was done using data from the literature. Based on detailed knowledge of the modeled processes, mathematical apparatus can be created that does not rely on fitting coefficients or nonphysical assumptions that are impossible to be verified experimentally. In recent years a new approach was proposed for studies of SOFC [39]. The behavior of SOFC under varied operating conditions was simulated using an equivalent electric circuit, which is shown in Fig. 5.2. In this

Figure 5.2 Electric circuit equivalent of solid oxide fuel cell (A) and solid oxide electrolyzer (B).

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methodology, no empirical efficiencies are used, thus every parameter has a physical representation. This method was used to predict performance of SOFC cells and stacks both in steady state [40] and in transient modes [41]. The model was verified in the course of several studies, which indicated that the relative prediction error for voltage would not exceed 5% even during transitional modes of operation. In a similar manner the model can be applied to represent SOE. It is therefore possible to extend the proposed methodology to simulate interchangeable operation between fuel cell and electrolysis mode. In this methodology the modeled stack can be operated as either a fuel cell or an electrolyzer, where the electrochemical module is represented as a proper equivalent of the electric circuits shown in Fig. 5.2. The main processes occurring during operation of the SOE mode can be described by the flow of ions and electrons, which give an adequate equivalent electric circuit of the electrochemical cell. With SOE, current flow I3 represents the current delivered to the SOE from the current source, which is divided into currents I1 and I2 . I2 is delivered to the circuit representing electronic conductivity, while I1 is the total flow of electrons used in the electrolysis reaction. From the electric circuit the formula defining the SOE cell voltage can be determined: Emax 1imax r1 ηs  ESOEC 5  11 r1 =r2 ð1 2 ηs Þ

(5.13)

where, Emax is the maximum voltage defined by the maximum work of an isothermal process; ηf and ηs are the fuel and steam utilization factors, respectively, defined by the current working conditions of the cell; imax is the maximum current density defined by quantity of delivered fuel, steam, or oxidant; and r1 is the area-specific internal ionic resistance defined by permeability of electrolyte for oxygen ions, and r2 is the area-specific internal electronic resistance defined by electric conductance of the solid electrolyte. The formula maximum voltage of the SOE cell is determined from Nernst equation: Emax 5

RUT PO2;anode ln 4F PO2;cathode

(5.14)

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Solid Oxide-Based Electrochemical Devices

where T is the absolute temperature; R is the universal gas constant; F is the Faraday constant; PO2;anode is the oxygen partial pressure at the oxidant electrode outlet; and PO2;cathode is the oxygen partial pressure at the fuel electrode outlet. The maximum cell current depends on the gas flow and Faraday’s constant. In general, characterization of a cell is done with respect to the unit area; hence, current density becomes the main parameter instead of current. In this case the equation describing maximum current can be normalized to the area of 1 cm2 as follows: imax 5

2FUnsteam Acell

(5.15)

where Acell is the active area of a single SOC. A generic SOC is made of an electrolyte and neighboring electrodes—the fuel electrode and the oxidant electrode. Each of the layers can be made of different materials with different structures and physical properties. The total areaspecific ionic resistance of an SOC can be determined using the following equation: σ1;electrolyte σ1;anode σ1;cathode r1 5 1 1 (5.16) δelectrolyte δanode δcathode σ1 5 σ0 e2ðEa =RT Þ

(5.17)

where σ1 is total ionic conductivity, and factors σ0 and Ea depend on the electrochemical characteristics of the materials. Solid oxide electrolytes are often assumed to exhibit only ionic conductivity, but electronic conductivity is present as well. The temperature effect on the internal electrical resistance is not well understood and described. In general, a decrease of the electrolyte thickness reduces the ionic resistance and at the same time reduces electronic resistance. At high steam utilization factors the effects of electronic resistance are minor, but larger differences are observed at low current densities. The presence of r2 can be used to explain the difference between the open-circuit voltage (OCV) and maximum cell voltage calculated using a theoretical formula. Electrical resistance of a cell depends on the thickness and total electronic conductivity of a cell, defined by the following equation:

Multilevel modeling of solid oxide electrolysis

r2 5

δ σ2

137

(5.18)

where δ 5 δelectrolyte 1 δanode 1 δcathode is the total thickness, and σ2 5 σ2electrode 1 σ2anode 1 σ2cathode is the total electronic conductivity of an SOC. Typically, a set of experimental data is required to compute the value of electronic resistance.

5.4.2 One- and two-dimensional models One- and two-dimensional (1D and 2D) models in the case of SOC cells are designed in the form of separate layers that influence each other, representing electrodes, electrolyte, and fuel and oxidizer channels. They are used in situations where boundary conditions in the form of geometry need to be taken into account. It is a simplified approach that reduces one or two additional dimensions. The simplification is compensated by appropriate assumptions, such as heat transfer and direction of electron flows occurs only along the stack, but at the expense of the number of results generated by the model [18,42]. These types of numerical tools are typically used to reduce the time needed to generate results while taking into account the geometry. This is done mainly in situations where the discretization of differential equations does not compromise the accuracy of the model, even when the geometry is simplified to a given extent. Moreover, this approach can be used to determine the concentrations of individual chemical compounds and temperature profiles along or between individual cell layers of gas channels. The 0D approach shown by Iora and Chiesa [36] was expanded, resulting in the creation of a finite difference 1D model of a single-unit SOFCSOEC stack [43]. The improved 1D model focused mainly on determining the influence of various system configurations and operating parameters on pure oxygen production processes. Ni [6] presented a 1D model simulating the operation of SOE cells for the electrolysis of carbon dioxide. In 2012 Ni developed a 2D SOE stack dynamic model for the production of syngas by coelectrolysis of steam and carbon dioxide [44]. Grondin et al. [8] presented a 1D model for simulating the behavior of a fuel electrode based on nickel ceramicmetal composite, analyzing balance equations, taking into account the kinetics of electrochemical reactions. Narasimhaiah et al. [15] created a modified ButlerVolmer model to simulate carbon dioxide reduction, including multistage reactions of single electron transfer. Jin and Xue [45] proposed a 2D model of a planar

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SOC operating in both SOFC and SOE modes. The results generated during experimental activities on NiOYSZ/YSZ/LSM cell were used to validate the model. Stempien et al. [31,4649] in a number of publications proposed a new model covering the effects of the electrolyzer at the extreme difference of oxygen chemical potentials. The model was used to analyze several energy conversion systems, that is, lowering of carbon dioxide emissions, reduction of instability of RESs, electric grid balancing, and production of synthetic fuels.

5.4.3 Three-dimensional models The most complicated methods used for simulating SOC operation are complete 3D models. 3D models simulate variable parameters within the cell, taking into account gas and temperature distribution as well as electrochemical reactions, after prior determination of the appropriate computational methodology and boundary conditions. In addition, this approach can be used to design separate elements of the SOC module, to determine correlations between them and to optimize their performance. The possibility of using 3D models is practically limitless, but it does lead to difficulties in terms of the form of costs and the time required to conduct calculations. Depending on the complexity of the issues analyzed, the generation of individual case results may take anywhere between a few hours and a few days. For this reason the 3D approach is used for detailed examination of key problems, and the results generated are further used as input data for simplified models. Finite element method is the most commonly used solution to simplify calculations in this type of approach [50,51]. Hawkes et al. [52] prepared a 3D model of a high-temperature SOEC stack composed of 60 planar cells. The technical specification and performance data of the stack used in the simulations were based on physical stack data delivered from Ceramatec, Inc. and tested at the Idaho National Laboratory. The numerical tool was created in Ansys Fluent workbench. The electrochemical calculations were included in the user-defined functions as own computational codes. The changes in current density, temperature, and gas compositions along the stack, for different cell voltages, were shown. Duhn et al. [53] proposed a novel method for simulating gas distribution in SOC stacks. The designed model reproduced with very high accuracy of the gas channel dimensions and location from the physical stack. For the numerical optimization processes of channels parameters, the Monte

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139

Carlo methodology was selected, which is commonly used for advanced mathematical problems (integrals, statistical process chains), so that their results can be predicted using an analytical approach. In 2013 Grondin et al. [54] created a 3D model of an SOE single repeating unit (SRU), where gas flow velocity, species concentrations, current density, and temperature distributions through the SRU were calculated. In this work an artificial neural network (ANN) was used to predict the operation of the SOE unit, focusing mainly on the porous cathode electrode. Data for training and validating the ANN simulator was extracted from the previously validated electrochemical model. Navasa et al. [55] designed a 3D cathode-supported SOEC computational fluid dynamics (CFD) model, where the impact of various cell voltages on overall module performance was analyzed. The configurations of both cross-flow and counter-flow gas channels were taken into consideration during the numerical investigation. The simulations performed resulted in a series of temperature and gas distribution profiles in the cell, depending on the current voltage for endothermic, thermoneutral, and exothermic modes during electrolysis operation. In addition, depending on the operational parameters and configuration of the unit, the rate of hydrogen generated was also determined. In 2018 Navasa et al. [56] proposed a new 3D multiphysics model of an SOC, which precisely determines local partial pressure distributions in the cell. This methodology underwent a detailed validation process based on in-house experiments performed in various operating conditions. The main goal in this work was to analyze and determine the ways of mitigating SOC cell degradation, thus extending its lifetime. To sum up, every proposed methodology has several advantages and disadvantages. Depending on the preferred aspects of numerical activities, that is, simulation time and cost, number and type of results generated and acceptable accuracy, the model has to be chosen taking into account its overall limitations.

5.5 Typical operating conditions SOEs profit from similarities to SOFCs, which are far more widely researched both in terms of electrode manufacturing and optimization of operating conditions. SOEs are usually operated between 700°C (973K) and 950°C (1223K) [14] and at pressures ranging from 1 up to 10 bar [57]. Operation at high temperature entails clear advantages compared to

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SOE’s low-temperature counterparts (i.e., polymer electrolyte membrane electrolyzers), as the chemical and electrochemical kinetics are favored. Furthermore, operation at higher pressure can be beneficial. Bernadet et al. [57] studied the effect of pressure on the performance of SOEs from experimental and modeling viewpoints. The tests, carried out at 800°C, on two cathode-supported button cells with 20 mm diameter anodes, show that pressurization raises performance compared to atmospheric operation if the cell works at high current densities, that is, the effect of electrochemical losses is more relevant—see, for example, Fig. 5.3. On the other hand, when the cell is operated closer to the OCV, atmospheric operation leads to higher efficiencies, mainly due to the lower OCV attainable in these conditions. This characteristic is also observed by Sun et al. [58] in polarization curves at 1 and 3 bar, with a gas ratio of 50/50 vol.% H2O/H2. The modeling analysis of this effect confirms that the improved performance at high current density relates to the increase in the cell limiting current density (i0—see Eq. 5.11) and therefore to the reduction in concentration overpotentials. This is explained by looking at the mass transport mechanism and its dependency on pressure; the dusty gas model (DGM) is widely used for the modeling of mass transport in porous media (see Eq. 5.19), which is a modification of the more general StefanMaxwell model [59]. Steam conversion (%) 100

90

80

70

60

50

40

30

20

10

0

1.5 1 bar 10 bar 1 bar model 10 bar model

1.4

Voltage (V)

1.3 1.2 1.1 1 0.9 0.8 –1.6

–1.2

–0.8

–0.4

0

Current density (A cm–2)

Figure 5.3 Experimental and simulated polarization curves at 1 and 10 bar (T1/4 800°C, 35/58.5/6.5 vol.% of N2/H2O/H2 at the cathode side, air at the anode side) [57].

Multilevel modeling of solid oxide electrolysis

  Xn cj ji 2 ci jj ci @μi;T ji 2 1 eff ði 5 1; 2; . . . ; nÞ 5 j51 eff RT @z cDij DKn;i j 6¼ i

141

(5.19)

where, ci and ji are, respectively, the concentration and the molar flux of the species i, and μi;T is the chemical potential at a fixed temperature. The DGM combines gas molecular diffusion with Knudsen diffusion. Therefore both effective diffusivity coefficients for molecular and eff eff Knudsen diffusion are included, respectively, in Dij and DKn;i . The former is a function of pressure, as reported by Fuller’s method in Eq. (5.20). In particular, molecular diffusivity decreases with increasing pressure [60]. On the other hand, the latter only depends on the microstructural properties of the porous media (i.e., pore radii) and on the operating temperature (see Eq. 5.21).   E 1:43 3 1023 T 1:75 1 1 21 eff Dij 5 1 (5.20) h i with Mij 5 2 1=3 1=3 2 τ Mi Mj pMij0:5 ν i 1ν j

eff DKn;i

E2 rpore 5 τ3

rffiffiffiffiffiffiffiffiffiffi 8RT πMi

(5.21)

where, Mi denotes the molecular weight for the gas species i, and ν i is Fuller’s diffusion volume. Therefore the positive impact that a higher pressure has on the concentration of the gas species generally outweighs the limitations of molecular diffusion, entailing an increase in cell limiting current, that is, a reduction in concentration overpotentials. The same study provides insight into the effect of cathode microstructure (i.e., porosity, tortuosity, and average pore radius) on performance of the cell when operated at high pressure. The results show that the effect of improved microstructure characteristics diminishes as pressure increases, as the already reduced overpotentials due to higher pressure lead to sufficiently high improved performances. Consequently, it is suggested that for operation at the thermoneutral voltage and above 5 bar, it would be possible to operate with stronger finer microstructure produced with cheaper manufacturing processes. Extensive work has been done at the DTU and Risø National Laboratory on SOE testing and modeling. Fig. 5.4 sets out the polarization curves of their cells. Their typical operating conditions range from 23.6 A cm22 at 1.48 V, 950°C and 70/30 vol.% H2O/H2 ratio (i.e.,

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Solid Oxide-Based Electrochemical Devices

Cell voltage V (V)

950 950

°C,

°C,

1.6

70%

70%

CO

1.4

H2 O

1.2

2

SOFC

1 0.8

C, 5



0.6

SOEC

850°

75

C,

0.4

50

%

0% H

2O

H

2O

0.2 –4

–3

–1

0

0

Current density (A cm–2)

1

2

3

Figure 5.4 IV curves obtained on the tested SOC working as an SOEC (negative current densities) and as an SOFC (positive current densities) at various temperatures and inlet gas compositions [61]. SOC, Solid oxide cells; SOEC, solid oxide electrolyzer cell; SOFC, solid oxide fuel cell.

average internal resistance of 0.17 Ω cm2) to 0.55 Ω cm2 at 750°C with 50/50 vol.% H2O/H2 ratio [61]. The cells are characterized by conventional materials typical of SOFCs: 300 μm thick NiO/YSZ porous support and 10 μm thick YSZ hydrogen electrode; 10 μm thick LSM/YSZ oxygen electrode and 10 μm thick YSZ electrolyte. Therefore the electrochemical modeling of such materials hinges on extensive experience of SOFC modeling. Menon et al. [14] used such experimental data to develop and validate an SOE finite volume model, which couples microscale phenomena—such as elementary kinetics and adsorption of reacting species—with a macroscale perspective. From an operational standpoint the work highlights the trade-off between hydrogen production efficiency and hydrogen throughput with cell voltage. In fact, the former (Eq. 5.1) increases with reducing voltage and steam utilization factor (see Eq. 5.22). ηs accounts for the steam conversion, and correspondingly for the hydrogen production, at the fuel electrode, with respect to the amount of steam molar flow rate at the cathode inlet; ηs is a central parameter for the SOEC operation, since it has an influence on cell voltage and efficiency. Furthermore, when introducing an SOEC into a plant, amount of steam is fundamental for optimizing overall system efficiency. ηs 5

n_ H2 ;prod jAactive =2F 5 n_ H2 O;in n_ H2 O;in

(5.22)

Conversely, the hydrogen production rate—which is directly related to current density—increases at increasing voltage. From a system design

Multilevel modeling of solid oxide electrolysis

143

perspective the choice of steam utilization factor ought to take into account the efficiency consideration and economic aspects related to the additional investment costs needed to accommodate the higher cathode stream flow rate at low Us [62]. Typical values of Us range between 40% and 80%.

5.6 Thermal management of solid oxide electrolyzer stacks As discussed previously in this chapter, the thermal behavior of an SOEC depends on the operating point of the cell. The thermal balance between the sinks represented by endothermic electrochemical reactions and the sources due to irreversible losses (see Eq. 5.23) determines three different thermal regimes: endothermic, thermoneutral, and exothermic. X j _ _ _ Q net 5 Q th;red 1 Q loss 5 2 ηk T ΔS 1 jU ze F k (5.23) X 5 2 jðVtn 2 EN Þ 1 jU ηk 5 jðV 2 Vtn Þ k

The thermoneutral voltage of the cell identifies the operating point at which thermal sinks and sources are balanced, and thus it is possible to identify which of the three thermal conditions is occurring in the cell _ net is zero from its operating voltage (see Eq. 5.23 and Fig. 5.5). In fact, Q if V 5 Vtn, while it is negative if V , Vtn and positive if V . Vtn. 870 Ucell = 1500 mV

860

Temperature (°C)

850 840

Ucell = 1400 mV

830 820

Ucell = 1300 mV

Ucell = 1000 mV

810

Ucell = 1100 mV

Thermoneutral operating mode

800 790 780

Ucell = 1200 mV

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Current density (A cm–2)

Figure 5.5 SOEC temperature (middle of the cell at the cathode/electrolyte interface, electrolyte-supported cell) simulated at different cell voltages (Vtn at 1300 mV) [63]. SOEC, Solid oxide electrolyzer cell.

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When an SOE stack is considered in which cells are connected in series by interconnect plates, additional thermal sources arise due to the ohmic losses related to the contact resistance between cells and plates and to the resistance of the plates themselves. From the modeling point of view, the thermoneutral voltage criterion is applicable also to a stack unit [i.e., cell 1 plate, known as stack single repeating unit (SRU)] for identification of the thermal regime, if the cell model includes contact and plate resistances for determination of the SRU voltage. Another possible type of thermal source/sink that may occur in cells and stacks is represented by the reaction heat of homogeneous/heterogeneous chemical reactions between chemical species in the anodic/cathodic streams. It is uncommon to have this type of sources/sinks in SOE cells operating in steam electrolysis, in which only H2/H2O mixtures are present at the cathode (and usually N2/O2 at the air-fed anode). Nevertheless, it may occur in coelectrolysis operation at the cathodes, where mixtures of carbon- and hydrogen-containing molecules can react (e.g., WGS and reverse reactions, methanation) due to the high temperature and presence of catalysts (e.g., nickel). Li et al. [64] assessed by elementary reaction modeling the local distribution of heterogeneous chemical/electrochemical reactions in a cell during coelectrolysis. The thermal balance is usually implemented in cell and stack models in the form of energy conservation equations in different domains: fluid (anodic/cathodic streams), porous (electrodes), and solid (electrolyte and interconnects) [65]. Applying the thermal balance in solid and fluid domains, one can calculate the temperature of the solid/fluid at each point of the domains (or a single global value for 0D models). In the porous domains, fluid and solid coexist, which in principle can assume different values of temperature at the same point. In SOC models the local thermal equilibrium (LTE) approximation is usually applied for the porous domains, which locally assumes the same temperature for solid and fluid, which opens the way to using a single energy conservation Eq. (5.24).    @T _ (5.24) 1 ρg Cpg uUrT 5 rU keff rT 1 Q eff @t _ is a term that includes all thermal sinks/sources (i.e., In Eq. (5.24), Q _ net and the additional chemical sinks/sources), u is the fluid sum of Q   velocity, and ρCp eff and keff are effective properties of the solidgas domain given by volume averages of the properties of gas and solid: 

ρCp

Multilevel modeling of solid oxide electrolysis

145

  ρCp eff 5 ερg Cpg 1 ð1 2 εÞρs Cps

(5.25)

keff 5 εkg 1 ð1 2 εÞks

(5.26)

where, ε is the electrode porosity, ρ is the density, Cp the specific heat, and k the thermal conductivity. The LTE approach was discussed and validated for SOFC models in Ref. [66]. It is worth noting that Eq. (5.25) corresponds to the energy conservation equation of fluids for ε 5 1 (i.e., 100% porosity) and solids for ε 5 0 (i.e., 0% porosity). In the global thermal balance of a stack, besides thermal sinks and sources, cells and plates exchange heat with anodic and cathodic streams (convective heat exchange), between themselves (radiative heat exchange and conductive heat exchange in contact points) and with the external environment. In fact a realistic SOE stack is not adiabatic but has a thermal exchange toward the external environment through nonideal thermal insulation layers. Hence, the complete thermal balance of a nonideal SOE stack entails different sources, sinks, and heat exchange boundaries with ambient and fluids, all contributing to determination of the stack temperature profile. The thermal interaction of the stack with entering/exiting fluids and the external environment is implemented in the models by boundary conditions. The thermal balance on the SOE stack/SRU is used to determine the temperature distribution along 1D (1D models) or on a plane (2D models) or volume (3D models), which reduces to a single value in the case of 0D models [33]. In the literature the majority of SOEC thermal models were developed on 1D/2D and investigate the temperature profile along flow direction or in a cross-section of the cell/stack SRU [9,62,67,68]. Very few models address the thermal simulations of SOECs with a 3D approach, one of the most relevant being the work of Hawks et al., which modeled the temperature distribution in a 60-cell SOE stack [52]. Thermal models of SOE stacks/SRUs are powerful instruments to address the local temperature conditions leading to degradation of materials and loss of performance. In fact the temperature affects the performance of the SOEC, impacting mostly on reaction kinetics, ionic conductivity of the electrolyte, and reversible cell voltage. In SOEC the temperature decrease has a negative effect on the three abovementioned parameters, generating an increase in activation losses, ohmic losses, and reversible cell voltage. Besides

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Solid Oxide-Based Electrochemical Devices

performance, the temperature can be a source of degradation for cell and stack components. Absolute limits and thermal gradient limits exist on stack temperature. The first type of limits consists in the extremes of the operating temperature range allowed for the stack. Lower temperature limits are related to the high overpotentials that lead to excessive voltage for a cell, while the higher limits are related to the chemical and thermomechanical properties of stack materials, particularly of electrode catalysts (risk of sintering) and cell sealants (loss of adhesion of glassceramic sealing). Moreover, as the SOC stack is a composite of different materials (ceramic, metallic, and glass), there is only a limited temperature window in which the thermal expansion coefficients of materials are compatible. Usually the operating temperature range for SOECs is 700°C900°C, with lower temperatures—down to 500°C—for cells of protonconductive oxides. The second type of limits is the thermal gradients in the cells, which induce thermomechanical stresses that can cause cracks/ delamination of materials interfaces. From the SOFC literature, thermal gradients from 10°C mm21 to 1°C mm21 are reported as limits [69,70]. Compared to SOFCs, in which all thermal sources are exothermic, the thermal balance of SOECs is characterized by a smaller net heat balance at the same current density values, due to the self-balance of sources/sinks. This leads to smaller temperature gradients in SOECs compared to SOFCs, if symmetrical conditions are considered. Nevertheless, the SOEC operating conditions require a careful assessment of the temperature profiles, especially when the stack is coupled to variable renewable sources due to thermal transients related to cyclical operation. The local distribution of the temperature in a cell/stack is extremely hard to investigate experimentally and might even prove impossible without special measurement configurations. In practical applications, the monitoring of stack temperature is generally performed by measuring the temperature difference on inlet/outlet flows and by placing thermocouples in various positions next to the stack, without catching the local gradients within the cells. For this reason the thermal models are of paramount importance when assessing local conditions leading to degradation and when simulating the response to thermal control strategies. In principle, the control strategies for the thermal management of SOC stacks involve actions to modify all sources, sinks, and heat exchange boundary terms of the thermal balance of a stack. In the case of SOEC, three types of thermal management strategies could be implemented: 1. stack fluids: control through cathodic/anodic flows

Multilevel modeling of solid oxide electrolysis

147

Figure 5.6 Simulated temperature distribution along SOE stack (in cathode steam) for an average current density of 5000 A m22 (A) and 15,000 A m22 (B), at fixed steam utilization—80%—and fluids inlet temperature—800°C—for air ratios of 0.4, 7, and 14 [68]. SOE, Solid oxide electrolyzer.

2. reactions: exploit exothermic/endothermic chemical reactions 3. stack coupling with external thermal sinks/sources: use of special interconnects to exchange heat through stack insulation The most common strategy is SOEC thermal control realized by adapting the anodic flow entering the stack, which is also commonly applied for SOFCs with cathodic (i.e., air) flow. Even though an oxygenfree gas would be the best anodic feed option for SOEC performance—as it ensures a low O2 partial pressure at the electrode while balancing the pressure difference through the two sides of the cell—air is commonly used in SOECs too, for economic and technical reasons. In fact, air has a perfect compatibility with the anodic materials and avoids the need for separating oxygen from sweep gas, where sweep gas is used and recirculated. From the point of view of SOE modeling, several studies assessed the use of anodic air flow for thermal management in SOEC cells/stacks [62,68,7173]. Cai et al. [68] compared by modeling the effect of different parameters on SOEC stack performance, including the effect of varying air ratio (i.e., ratio of anodic/cathodic flows) from 0.4 to 14 Fig. 5.6. The study showed that 80% of the temperature gradient reduction in the cell is realized with an air ratio of up to 7, selected by the authors as the value that balances the advantages of more uniform temperature distribution against the increase of auxiliary ventilation energy required to increase the air flow rate [73]. The study assessed the effect of steam utilization and steam molar fraction variation on temperature gradients at fixed current density, showing a markedly lower impact compared to the air ratio. This result suggests that regulating the cathodic flow is not suitable for temperature control

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Solid Oxide-Based Electrochemical Devices

purposes, a view reinforced by the fact that varying cathodic flow rate and its composition—and consequently of steam utilization in water electrolysis at fixed current—has a huge impact on cell performance. In fact, to the authors’ knowledge, the use of cathodic flow for thermal management is not reported in SOEC literature. Another possible thermal control strategy is to exploit chemical reactions on the cathode side in coelectrolysis as thermal sources/sinks. The main chemical reactions that occur with coelectrolysis compositions (CO/ CO2/H2O/H2 mixtures) are WGS—or reverse—and methanation (i.e., Sabatier reaction), the latter being the most interesting because it is highly exothermic and could potentially provide the heat absorbed by the cell in under thermoneutral condition. This synergy between exothermic methanation and endothermic SOEC operation is presented in the literature as a great advantage at system level for power-to-gas systems, increasing the energy and exergy efficiency of the overall process [7476]. However, direct integration within the cells of coelectrolysis and methanation is difficult, because methanation requires high pressure, while current SOEC technology operates at ambient pressure and at lower temperatures than SOECs (200° C550°C) [77]. Recently, some studies investigated the direct coupling of methanation and coelectrolysis in tubular [78] and button cells [79,80], focusing on methane production without addressing the thermal control option. Hence, this thermal management option could be of interest for future SOEC stacks operating in conditions that are more favorable to methanation. Another SOE thermal management strategy at stack level consists in coupling the stack with external sources through interconnects, which act as distributed thermal source/sink in contact with the cell—or block of cells—and enable temperature conditioning without modifying the operating conditions of the cells. This strategy requires modification of the interconnect design in order to couple it with an external source for heating/cooling the plate. The most common solution is to integrate hightemperature heat pipes within interconnects. A detailed description of this solution and the modeling approach adopted for SOEC-heat pipes simulation is provided later in this chapter (see Section 6.1) together with some relevant results from the literature. Finally, an example of SOE thermal management by interconnect modification without using heat pipes has been proposed by Di Giorgio and Desideri [81]. In this work the use of an eutectic metal alloy in interconnect microchannels and of a solid aluminum oxide as thermal storage

Multilevel modeling of solid oxide electrolysis

149

was studied for rSOC operation, with the aim being to store the heat produced in SOFC mode for subsequent SOEC operation.

5.7 Thermal management of solid oxide electrolyzer through the use of heat pipes Among the SOE thermal management strategies at stack level previously described in the chapter, coupling the stack with external sources by integrating high-temperature heat pipes within interconnects is a recently investigated alternative to anodic flow modulation. Heat pipes are heat transport devices that can provide high heattransfer rates by exploiting the evaporation and condensation of a heattransfer fluid, which fills closed tubes/cavities and forms a continuous loop moving from one end of the heat pipe structure to the other. At the endothermic end of the heat pipe, the fluid (liquid state) evaporates and then flows as vapor through the pipe to the condensation end (exothermic), where it is cooled to saturated liquid conditions and returns to the evaporator end through wick structures by capillarity. Heat pipes represent isothermal structures, as the fluid inside the heat pipe—a metal for hightemperature applications, typically sodium—is in phase change conditions in the evaporation/condensation cycle. Heat pipes can be integrated within the SOC stack by special interconnects, which incorporate one end of the heat pipe, while the other is put in contact with an external heat sink/source. This type of integration was successfully demonstrated in the European project Biocellus, where an SOFC stack cooled by heat pipes was created and tested. The presence of heat pipes integrated in the interconnects exerts a “thermostat” effect on the SOC stack, adding a constant temperature structure that reduces the thermal gradients and makes it possible to directly extract/provide heat from/to the stack. In the literature, integration of heat pipes in stacks has been investigated mainly for fuel cell applications with the aim being to increase stack cooling and exploit the recovered heat in thermal integration solutions with fuel cell system components (e.g., preheaters and prereformers) [82]. Most works addressed the use of heat pipes in SOFCs to integrate stack and system with biomass gasifiers, assessing this solution with system models focusing on heat recovery rather than stack thermal gradients. Panopulos et al. [83] used a system model (Aspen) to investigate the heat integration of SOFC and gasification of biomass through liquid sodium heat pipes. Santhanam et al. [84] studied an integrated biomass

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Solid Oxide-Based Electrochemical Devices

gasifierSOFCgas turbine system, proposing to place the heat pipes connecting the SOFC and gasifier in between two stacks thereby avoiding the complexity of integrating heat pipes within interconnects. In this case the control capability of heat pipes on cell temperature profiles is limited, as they are in contact only with the top/bottom of the entire stack. Other studies proposed the integration of SOFC auxiliaries with heat pipes for thermal recovery: Mojaver et al. [85] using sodium heat pipes integrated with an SOFC afterburner to provide heat for the gasification of biomass and Venkataraman [86] for heat recovery from SOFC hot cathode exhausts to supply heat to a desorber. Recently, Zeng et al. experimentally investigated a highly thermal integrated heat pipemicrotubular SOFC [87,88]. Focusing on SOEC, several works by Dillig et al. [89,90] experimentally investigated the integration of planar high-temperature heat pipes in short stacks. Guandalini et al. [91] presented a modeling study on an rSOC integrated with heat pipes, using a 0D model. Very few studies addressed the integration of heat pipes within SOC stacks by modeling their impact on the temperature profile. Marocco et al. [92] investigated with a 1D model the integration of liquid sodium heat pipes into interconnects (every five cells) of a hydrogen-fed SOFC stack, which is the most stringent thermal condition due to the absence of cooling by internal reforming, as methane is not present. In the model the heat pipe is treated as isothermal surface with an equivalent thermal resistance and included in the thermal balance of the stack as a boundary thermal flux at the interconnect. The work showed that heat pipe integration is beneficial for the SOFC, increasing the maximum permissible current density (and power) compatible with temperature gradient limits. Dillig et al. [93] presented a 3D CFD model of an SOFC stack with internal methane reforming integrating planar heat pipes, also in this case modeled with equivalent thermal resistances. The model showed considerable reductions of in-stack temperature gradients thanks to heat pipes (one per 10 cells), up to 50% within one cell. Dillig and Karl [94] developed a quasi-2D thermo-electrochemical model of an SOC with/without heat pipes both in SOEC and SOFC, showing and comparing 1D thermal profiles in the stack. Following immediately below is an example of the modeling results of SOE thermal management by heat pipes, using as reference the approach of Marocco et al. [92] for heat pipe modeling as equivalent resistance and showing the thermal model and results of Dillig and Karl [94].

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151

Figure 5.7 Heat resistances in a heat pipe. Configuration for SOFC operation or exothermal SOEC (i.e., evaporator end in contact with SOC stack). SOC, Solid oxide cell; SOEC, solid oxide electrolyzer cell; SOFC, solid oxide fuel cell. Adapted from P. Marocco, D. Ferrero, A. Lanzini, M. Santarelli, Benefits from heat pipe integration in H2/ H2O fed SOFC systems, Appl. Energy 241 (2019) 472482. doi:10.1016/j. apenergy.2019.03.037.

From the point of view of modeling, a heat pipe can be seen as a thermal conductor, which follows Ohm’s resistance law, thus represented as an equivalent heat resistance that is the sum of the series/parallel of the internal heat resistances of the heat pipe, each connected to a specific heat-transfer phenomenon. Fig. 5.7 depicts the main heat resistances within the cross-section of a heat pipe, along the axial direction of the pipe. The resistances in the wall and capillary structure are conductive in nature, thus derived from Fourier’s law, and depend on the geometry (planar/cylindrical) and thermal properties of the heat pipe in the following equation. Rw;c=planar 5

s ln ðdout =din Þ Rw;c=cylindrical 5 Aλ 2πLλ

(5.27)

In Eq. (5.27), s is the thickness of wall/capillary layer, A and L are the surface area and length of the condenser/evaporator zone, dout/din are the external/internal diameters, and λ is the thermal conductivity of the layer. For the capillary structure—a solid matrix saturated with liquid—an effective thermal conductivity is used, which is obtained as an average of the conductivities of solid structure and liquid, weighted with geometrical parameters. The heat resistances in the vapor core of the heat pipe are distinguished in radial resistances at the liquidvapor interface, describing the molecular interaction at the interface, and axial resistance along the vapor flow, proportional to the temperature drop (very small) along the vapor

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flow. It is worth noting that the radial conduction resistances in the wall and capillary structure are dominant, thus the overall thermal resistance of the heat pipe can be approximated by a series of four resistances: RHP 5 Rw;evap 1 Rc;evap 1 Rw;cond 1 Rc;cond

(5.28)

The total resistance of the integrated interconnect-heat pipe is the sum of the interconnect conductive resistance and the heat pipe equivalent resistance. In thermal models of SOCs, heat pipes are usually considered isothermal surfaces/volumes, with a fixed temperature not affected by the value of heat flux exchanged with the SOC. However, heat pipes are not an ideal thermostat, which can exchange infinite heat flux, but are subjected to heat transport limits: capillary, viscous, sonic, entrainment, and boiling limits. These limits are connected to pressure drops, fluid velocity, and nucleation of vapor bubbles in the capillary structure and contribute—the capillary being the most relevant—to determine the maximum heat flow that the heat pipe can deliver without compromising the motion of fluid inside the heat pipe. Thus in SOE thermal models, a heat pipe can be implemented as an isothermal structure with characteristic thermal resistance and heat transport limit. In the quasi-2D thermo-electrochemical SOC model developed by Dillig and Karl [94], high-temperature heat pipes are modeled using this Plane of symmetry R_solid R_contact

R_rad_ channel

2 q_trans

R_int

Qtrans,2

R_contact

Hout

1 cell unit

Rth,cell Cell 3

R_int

qs

q_trans

R_int_steg

Heat pipe

CV

Cell 4

R_rad_ channel

Cell 2

3 q_trans Cell 1

R_int_steg 4 q_trans R_solid

Qtrans,1

Heat pipe

(A)

(B)

(C)

Figure 5.8 Thermal management of high-temperature solid oxide electrolyzer cell/ fuel cell systems: (A) heat transfers within heat pipe integrated solid oxide cell stacks; (B) thermal resistance circuit diagram for a single-cell layer; (C) schematic approach to equivalent heat-transfer coefficient [94].

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approach. In the work a steady-state, finite volume thermoelectrochemical model of a planar SRU of an SOC stack has been developed, applying an equivalent thermal circuit for the simulation of the heat flux transferred between the stack SRUs and heat pipes. In the control volume of the SRU (see Fig. 5.8) the energy balance in steady-state conditions is implemented. The balance includes the heat sources/sinks term (qs in the figure) due to electrochemical reactions and cell overpotentials, the heat transferred by anodic and cathodic fluids entering/exiting the volume and the transverse heat transfer (Qtrans) between SRUs and the heat pipe. The heat flux Qtrans has been calculated as dependent on the local temperature in the cell, the heat pipe temperature (isothermal), and an equivalent heat-transfer coefficient that describes the heat-transfer regimes through the layers of the stack (10 cells for each heat pipe), which is obtained from the equivalent circuit model of stack resistances shown in Fig. 5.8. 1 i Rth;i

Qtrans 5 ktrans UðT ðxÞ 2 THP Þ; with :ktrans 5 P

(5.29)

The simulations were performed for operation in both fuel cell and electrolysis, with and without heat pipes. The temperature profiles along the flow parallel cell direction for endothermic, exothermic, and thermoneutral SOEC conditions and SOFC operation are shown in Fig. 5.9. Fig. 5.9A depicts the profile without heat pipes (inlet temperature of the fluids of 800°C), showing a total temperature gradient within the cell of up to 180K in SOFC, with 100K (negative) gradient in SOEC endothermal mode. The positive impact of heat pipes is shown in Fig. 5.9B, depicting for each mode the temperature profile on the five cells thermally influenced on one side of the heat pipe. The figure clearly shows how the stationary thermal gradients shrink. It is worth noting that in the case of transient operation, the thermal gradients are even smaller than the stationary solution, which is reached after the complete evolution of the transient; thus in the case of reversible, dynamic operation (e.g., powerto-power applications) the presence of a constant temperature heat pipe can be used to stabilize temperature profiles in safe operating regions.

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(A) 1000 SOFC operation λ = 7.5

Cell temperature (°C)

950 900

Exothermal SOEC 850 800 Thermoneutral SOEC

750 700

Endothermal SOEC

650 0.1

0

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Dimensionless flow parallel position [–]

(B)

1000

Cell temperature (°C)

950 SOFC operation λ = 7.5

900 Thermoneutral SOEC

850

Exothermal SOEC

800 Endothermal SOEC

750 700 650

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Dimensionless flow parallel position [–]

Figure 5.9 (A) Temperature profile of a cell without heat pipes; (B) temperature profiles on five cells with heat pipes. Adapted from M. Dillig, J. Karl, Thermal management of high temperature solid oxide electrolyser cell/fuel cell systems, Energy Procedia 28 (2012) 3747. doi:10.1016/j.egypro.2012.08.038.

5.8 System analysis and applications 5.8.1 Operation of solid oxide electrolyzer as a part When designing an SOE stack placed within a more complex system, the predicted most common operating condition should be considered. Depending on the operating point on the cell characteristic curve the

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Figure 5.10 (A) Cathode stream temperature along the cell for average current densities of 5000 and 7000 A m22; (B) thermal energy (per mole of H2) consumed by the reaction (TΔS) and that produced by the irreversible losses (2Fηtotal) as a function of current density at 1023K [62].

thermal behavior of the stack will be different. This constitutes one of the main differences compared to SOFC stacks and greatly influences the design of the rest of the system and its coupling with the SOE. As reported by Udagawa et al. [62] the operational curve of the cell at different current densities is characterized by a thermoneutral point in which the thermal energy consumed by the endothermic electrochemical reactions is equal to that produced by the irreversibility losses, as schematized in Fig. 5.10. Therefore when the chosen design point is below the thermoneutral point, the cell will be endothermic and heat will need to be supplied to the cell by either the internal energy of the reactant streams or via external heat sources; examples of the latter will be discussed in the following section. If the cell or stack is operated in exothermic condition (above the thermoneutral point), heat is available for thermal recovery at the cell outlet. As already mentioned, operation above the thermoneutral condition has pros and cons and should be evaluated accordingly. The cell in fact does not exploit external heat to—at least partially—supply the required energy for the electrochemical reduction of water; this represents a disadvantage of exothermic operation and an energy inefficiency source, as external electric energy is first converted into heat due to irreversibility losses and then used to power the electrochemical reactions. On the other hand, from a plant perspective, operation above the thermoneutral voltage point might be advantageous for two reasons:

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1. It allows for operation at higher current density, thus achieving higher power density per unit of cell active area and therefore a cheaper SOE module per unit of hydrogen produced. 2. Depending on the external thermal source considered, it might be more advantageous from an economic—and sometimes thermodynamic—perspective to reduce the thermal power input (i.e., working at higher current densities) as it will reduce the overall first law efficiency of the system. In other words, the increase of consumed electric power at higher current densities is more than outweighed by the reduction in thermal power.

5.8.2 Solid oxide electrolyzer integration with thermal and electric sources The thermal management challenges associated to high-temperature electrolysis constitute an advantage in terms of process integration with other technologies. In fact, different studies have proposed using the thermal power available as a waste product from various sources (such as nuclear [95,96], biomass and solid waste [97], geothermal [98], concentrated solar thermal [99], or thermo-PV solar [100]) to supply the required energy to the electrochemical reactions in an SOE. Note that in many cases where the external thermal source is not enough to supply the overall thermal energy for electrochemical reactions, additional primary energy must be provided either via electric heating or by burning a fuel source. One important example is the FCH-JU European Union funded project SOPHIA, which has studied various solar technologies to be integrated into pressurized SOE modules. In particular, the use of a CSP plant delivers the combined production of electricity and heat from a renewable source which could then be used to produce low-carbon renewable hydrogen. The project considered all four main CSP technologies—solar tower, parabolic trough, linear Fresnel, and solar dishes—with and without thermal storage and with various heat-transfer fluids (e.g., water, molten salts, and ambient air). The study concluded that for MW-scale hydrogen production (i.e., 400 kg day21) for transport applications the configuration of a solar tower integrated with an SOE combines the required characteristics of hightemperature steam production with the scalability of a solar field. Other solar technologies can provide both heat and electricity for an electrolyzer, but are either impeded by maximum thermal limitations of materials (i.e., parabolic trough and Fresnel solar receiver temperature is currently limited at 450°C) or by restricted scalability at bigger sizes of the solar plant (i.e., solar dishes).

1 4

2 3

Feed CO2/H2/CO 1

Heliostat

Y M2 Feed H2O

Y M1

2 3

1 4

Heat exchanger (HE)

CP2

H2O/H2/CO2/CO

H2O/H2/CO2/CO

Pump H2O

Mixer (M) Separator (SEP) Electrical heater (EH) Compressor (CP)

HE1 Condenser H2/CO/CO2

2

Y

EH1 Heliostat

SEP Rankine cycle

3

CO2 H2/CO

HE2 Air/O

Air

2

EH2

Electrolyzer

H2/CO

Solar receiver (SR)

System (1) :

Air Circulation H2O

System (2) : CP1

4 MPPT PV arrays

DC–DC

Air

Two-stage compressor System (3) : Syngas storage

Figure 5.11 Flowchart of the three systems, constructed with five different subcomponents: electrolyzer and auxiliaries (red block), concentrated solar heating system (purple block), fluid connection system (green block), CSP system (black block), and PV system (blue block). System 1 represents the thermal-only system using concentrated solar technology to provide both heat and electricity. System 2 represents the electricity-only system using PV technology as the only source for both heat and electricity. System 3 represents the hybrid heat-electricity system using concentrated solar technologies and PV providing solar heat and electricity, respectively. The black arrows indicate mass flow and energy streams, the blue lines indicate electricity streams, and the blue colored components are electricity consuming devices connected to the CSP or PV systems [101]. CSP, Concentrated solar power.

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The solution of an SOE integrated with a solar tower receiver is studied from a thermodynamic and economic perspective by Lin and Haussener [101]. The authors propose three solar-driven high-temperature electrolysis systems: (1) a thermal approach using a concentrated solar tower system to provide heat and generate electricity through a thermodynamic cycle; (2) an all-electric approach using PV technologies to produce electricity and generate heat via electric heaters; and (3) hybrid approach, using concentrated solar and PV technologies to produce thermal and electric energy, respectively. The three system configurations are depicted in Fig. 5.11. The authors reported a maximum solar-to-fuel efficiency of 10.6% of the purely thermal solar tower system; while the lowest cost of hydrogen production (i.e., $4.9/kg) is associated to a hybrid configuration in which the solar tower provides for the thermal demand of the electrolyzer and the electric one is covered by a PV plant. Other studies developed various configurations of coupled CSP with SOEs. Sanz-Bermejo et al. [102] proposed an SOE coupled with a Fresnel solar field using thermal oil as heat-transfer fluid and aiming to produce 400600 kg day21 of hydrogen. The plant makes extensive use of thermal energy storage (TES) of thermal oil in order to increase the operating hours of the electrolyzer, which can then act as an additional load on the electric grid during night hours in order to minimize the reduction load gradient. The same authors also studied the integration of an SOE with a direct steam generator solar power plant [103]. Guandalini et al. [91] studied the integration of a rSOC for long-term energy storage, where the required thermal power to the rSOC stack is provided by a direct steam Fresnel collector. An interesting characteristic of the proposed system is the coupling of the rSOC stack with external high-temperature molten salt thermal storage via two layers of heat pipes. Therefore the operating strategy is to exploit the exothermic nature of the fuel cell operation to heat up the thermal storage; the heat will then be employed—together with the solar thermal energy coming from the Fresnel collector—to supply high-temperature heat when the stack operates in electrolysis mode. The authors suggest that it is possible to reach hydrogen production efficiencies of about 80% and ideal round trip efficiencies of approximately 60%. Moreover, seasonal shifting of electric generation was also possible, proving the potentialities for rSOC systems to perform season-long energy storage. Seitz et al. [104] suggested the integration of an SOE with parabolic trough plant to perform long-term energy storage of intermittent

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renewable energy, such as wind and solar. The proposed configuration features a phase change material TES to provide an extension of the operational hours during nighttime. The study reported a minimum LCOH achieved with the adoption of a TES with a capacity of 11 h at 0.11 h kWh21. The adoption of TES is beneficial both in terms of LCOH reduction and year-long hydrogen production capacity. Very few researchers have explored the coupling of SOEs with dish collectors. Mohammadi et al. [105] recently presented a study proposing a compressed air energy storage system coupled with a dish collector to produce the electricity required by the SOE stack, and an additional dish collector to produce high-temperature heat. The work presented a technicaleconomic analysis concluding that with a daily capacity of 41 kg day21 of hydrogen, the efficiency of the power cycle and of the electrolyzer result is 72.69% and 61.70%, respectively, with an LCOH of $9.1/kg.

Acknowledgment Authors acknowledge financial support from the National Science Centre of the Republic of Poland (project ID 2018/31/D/ST8/00123).

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CHAPTER 6

Sensors based on solid oxide electrolytes A. Demin1,2, E. Gorbova1,2,3, A. Brouzgou3, A. Volkov1,2 and P. Tsiakaras1,2,3 1

Laboratory of Electrochemical Devices Based on Solid Oxide Proton Electrolytes, Institute of High Temperature Electrochemistry, RAS, Yekaterinburg, Russia Laboratory of Materials and Devices for Clean Energy, Ural Federal University, Yekaterinburg, Russia 3 Laboratory of Alternative Energy Conversion Systems, Department of Mechanical Engineering, School of Engineering, University of Thessaly, Volos, Greece 2

Contents 6.1 Introduction 6.2 Brief history 6.3 Materials for sensors 6.3.1 Electrolytes 6.3.2 Electrodes 6.3.3 Sealants 6.4 Types of sensors 6.4.1 Potentiometric sensors 6.4.2 Amperometric sensors 6.4.3 Coulometric sensors 6.5 Combined sensors 6.6 Concluding remarks References

167 168 169 170 172 173 177 177 189 201 203 205 205

6.1 Introduction Solid oxide electrochemical sensors are increasingly used in many applications, such as laboratory analysis, metallurgy, chemical processing, and environmental control (air, industrial wastes, combustion monitoring, etc.). Such sensors are attractive because the measured chemical quantities are directly transformed into electrical signals. Most of the different electrochemical gas sensing devices have the same phenomenology and working principles. Two types of sensors can be distinguished: (1) the active sensors in which the measured signal is voltage [potentiometric: equilibrium potentiometric Solid Oxide-Based Electrochemical Devices DOI: https://doi.org/10.1016/B978-0-12-818285-7.00006-X

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sensors (EPSs), mixed potential sensors (MPSs)] and (2) the passive sensors, that requires the application of an electrical source, the signal of which is analyzed afterward (amperometric and coulometric sensors). We will limit the description of those sensors, using a solid oxide material with ionic conductivity (solid electrolytes), which plays a major role in the detection mechanism. Herein, the main emphasis is given on the sensors based on oxygen or proton ion-conducting electrolytes. The main goals of this chapter are (1) to explain the working principles of solid oxide electrochemical sensors, emphasizing on the advantages and limits of their use and (2) to discuss the latest research activity in the field.

6.2 Brief history At the end of the 19th century the German scientist W. Nernst, with a great contribution to the development of electrochemistry, discovered that at high temperatures, a ceramic material, made of zirconia-calcia solid oxides, was able to conduct electrical current. He invented an electrical lamp (later named “Nernst glower lamp”), in which the working body was a rod made of the abovementioned ceramic material. The lamp gave perfect daylight spectrum but was not convenient in use: it was necessary to heat the rod before the lamp began to work, and for ordinary use, the Nernst lamp was displaced by Edison lamp at the beginning of the 20th century. However, the Nernst glower lamp was important for use in the medical field in infrared spectroscopy until the 1980s [1]. The nature of the current in the Nernst ceramic was not discovered until the 1930s of the past century when it was stated that the current in that and in similar ceramic materials was due to ions transport. Such materials were called “solid oxide electrolytes.” The first solid state cells in the 1950s were based on ceramics of zirconia stabilized by calcia or yttria. These materials are oxygen ion conductors (electrolytes) at high temperatures. Kiukkola and Wagner [2,3] first have used ceramic cells for thermodynamic measurements in 1957. Peters and Möebius [4] have used zirconia-based cells for the investigation of carbon dioxide dissociation and Boudouard equilibrium. Ceramic cells were first used in 1960 for oxygen analysis in molten salts [5]. In 1961 ceramic cells were also used for gas analysis [6], while similar cells, named “oxygen gauges,” were also patented [7]. In the middle of 1960, Alcock and Belford [8,9] used solid-electrolyte cells for

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measuring the solubility of oxygen in liquid metals. In 1969 the utilization of solid-electrolyte sensor for a wide range of applications, in particular, controlling oxygen content in refining of copper, measuring CO/CO2 ratios in furnaces was proposed [10]. In the same year, Förster and Richter [11] suggested the use of Cr/Cr2O3 as an oxygen reference potential. In 1971 Sandler used a zirconia-based galvanic cell with two electrodes: active platinum and inactive silver ones, for the analysis of airmethane mixtures [12]. In 1972 Ruka and Parson [13] patented “Method for polarographic measurement of oxygen partial pressure.” In fact, they first proposed a principle of novel type of sensors, which later were called “gas-diffusion-controlled solid-electrolyte oxygen sensors” [14], “limiting current sensor” [15], “gas polarographic sensor” [16], and “electrochemical pumping sensor” [17]. In 1973 Fleming et al. [18] first described a sensor for on-vehicle detection of engine exhaust gas composition. Agrawal et al. [19] first used ceramic cells for controlling the oxygen activities in argonoxygen mixtures by “coulometric titration.” In 1975 Hagen et al. [20] used a solidelectrolyte cell based on MgO stabilized ZrO2 for determining Al content in liquid steels. In 1976 Sandler [21] patented “Electrochemical sensor for reactive gas mixtures,” the first MPS (called also “non-Nernstian”) [22]. In 1977 Haaland [23] first described a combined sensor made with two cells sealed into a small unit with an inner chamber. One cell was used as a pumping cell and the other for measuring the electromotive force (EMF). In the same year, Hamann et al. [24] described “lambda sensor” for application in automotive emission control systems. In 1980 Takahashi and Iwahara [25] first reported on proton conduction in perovskite-type oxide solid solution. Two years later, such material was used in a steam concentration cell [26]. In 1984 Yamaguchi et al. [27] described a limiting current type sensor for the measurement of O2 and H2O concentrations in their mixtures with N2. Later, this type of sensors was called “multifunctional sensors” [28]. In 1993 Somov proposed the principle of the so-called multielectrode amperometric sensor for the analysis of multicomponent gas mixtures [29].

6.3 Materials for sensors The simplest solid oxide electrochemical sensor consists (1) of an electrolyte, (2) of at least of two electrodes, (3) of wires connecting the electrodes with a measuring device, and, in many cases, (4) of a sealant.

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6.3.1 Electrolytes The main functional part of an electrochemical sensor is a solid oxide ion-conducting material (solid electrolyte), which should meet a set of properties, including transport, mechanical and thermal characteristics, as well as thermodynamic stability under working conditions and longterm stability. The first solid oxide electrolyte was zirconia stabilized with calcia. Later, many various oxides were used as zirconia stabilizing agents: magnesia and ceria [30], yttria [31], and scandia [32]. Due to substitution of Zr41 cations by lower valence cations, a vacancy is formed in an oxygen sublattice. At elevated temperature an oxygen ion can jump from its normal position to the as-formed vacancy. Under a chemical or an electrical potential difference, oxygen anions move in a definite direction, thus providing electrical current of oxygen anions inside the electrolyte. Thoria-based electrolytes were also investigated and considered as a base for oxygen sensors for the analysis of gases with very low oxygen content [33], and for the analysis of melts [34,35]. Liaw and Weppner [36,37] reported on the utilization of the so-called yttria-doped tetragonal zirconia (having low content of yttria stabilizer) for the limiting current oxygen sensor. In some applications, when oxygen concentration is not less than ppm level, it is possible to use ceria-based electrolytes [38]; an electronic conductivity in these electrolytes appears at lower oxygen concentrations. Currently, yttria-stabilized zirconia (YSZ) is practically the only oxygen ion-conducting electrolyte commercially utilized, not only in sensors but also in other solid oxide electrochemical devices such as fuel cells, electrolyzers, oxygen pumps, and reactors. It is interesting to note that calcium zirconate was proposed in 1976 as prospect electrolyte for oxygen sensors operating at temperatures at around 1600°C [39]; later it was discovered that this material exhibited protonic conduction at significantly lower temperatures. The fact is that at the abovementioned high temperature, zirconates present oxygen ion conductivity; proton conductivity is negligible and their partial electronic conductivity is lower than that of stabilized zirconia. In the beginning of 1980s, Takahashi and Iwahara [25] have reported the appearance of a noticeable high-temperature proton transport in complex oxides with perovskite structure, particularly in SrCeO3. Protons are not the structural element of such oxides; however, due to the presence of vacancies in perovskites, they can interact

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with water vapor at elevated temperatures, according to the following reaction: H2 O 1 Vo 1 Oo3 5 2OHo

(6.1)

where Vo is the oxygen vacancy created in the crystal structure due to acceptor doping, OHo is the oxygen ion in the normal lattice site, and OHo is the proton localized on the oxygen ion (proton defect). The connection of a proton with an oxygen ion is weak, and at elevated temperatures, the proton can jump to another oxygen ion. Under a chemical or an electrical potential difference, protons move in a definite direction, thus providing electrical current of protons inside the electrolyte. Due to existence of vacancies in perovskites, they exhibit also oxygen ion conductivity. However, oxygen ions mobility is very low at moderate temperatures (,600°C) and such oxides have practically pure protonic conductivity, at these temperatures in reducing atmospheres. Under oxidizing conditions a hole conductivity appears in such oxides that limits their application for sensors. Since 1980, many oxide materials having proton conductivity were found. At the first stage, mainly alkali earth metal cerates MCeO3 (M 5 Sr, Ca, and Ba) were studied. In the beginning of 1990s, proton conduction was found in zirconates [40]. In 1993 Liang and Nowick [41] reported on protonic conduction in both stoichiometric and nonstoichiometric mixed perovskite ceramics with the general formula A2(B0 11xBv12x)O62δ (A 5 Sr21, Ba21; B0 5 Ga31, Gd31, Nd31; Bv 5 Nb51, Ta51; x 5 00.2). Later, in 1996, the proton conducting Ba3Ca1.18Nb1.82O92δ complex oxide electrolyte was investigated, which exhibited a proton conductivity σH . 1022 S cm21 with a transport number tH . 0.98 at 600°C [42]. This material did not demonstrate degradation in CO/CO2 atmosphere for more than 100 h. However, according to our knowledge, there is no information on the application of these materials in sensors in the past years. A comprehensive review on BaCeO3-based ceramic electrolytes was presented by Medvedev et al. [43]. Recent activity on the development of proton-conducting oxides, including perovskite-based materials such as BaCeO3, BaZrO3, BaCeO3BaZrO3, SrCeO3, and LaScO3; and other classes of materials such as doped Ba2In2O5, CeO2, and LaNbO4 was overviewed by Kochetova et al. [44]. A wide range of protonic ceramic materials was recently reviewed [45], where the main attention was made on BaCeO3 and BaZrO3 as

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these electrolyte materials were in the focus of research during the past two decades due to their considerable proton conductivity and stability. The latest achievements in the field of proton-conducting oxides can be found in a review on recent progress in low-temperature protonconducting ceramics published in 2019 [46]. In 1991 the so-called H/D isotope effect was first detected in protonconducting cerate ceramics [47]. Proton and deuteron conductivities were stated to be different in that protonic. Later, the isotope H/D effect was discovered in zirconates [48], in nonstoichiometric mixed perovskite ceramics with the general formula A2(B0 11xBv12x)O62δ (A 5 Sr, Ba, B0 5 Ga, Gd, Nd; Bv 5 Nb, Ta; x 5 00.2) [41]. In 1995 Kreuer et al. [49] first proposed the theory of the isotope effect. It should be noted that all solid oxide electrolytes exhibit, in addition to ionic conductivity, some parts of electron (hole) conductivity. The presence of nonionic conductivity can negatively affect the performance of the sensors due to the so-called oxygen (or hydrogen) electrochemical permeability [11,50,51]. In commonly used ionic oxygen electrolytes, the electronic conductivity is very low and becomes significant only at extremely low oxygen partial pressures [39,52]. However, the oxygen permeability limits, to some extent, the application of solid electrolytesbased oxygen potentiometric sensors [5357]. The conductivity of holes in protonics, in oxidizing atmospheres and elevated temperatures, can be significant [40,58]. Therefore the application of protonics in the potentiometric sensors, especially in oxidizing media, is seriously limited.

6.3.2 Electrodes In the sensors the main requirement of the electrodes is their high sensitivity to the analyzed gas component. Moreover, they also must have stable porous structure, chemical and long-term stability under the working conditions. Especially for the amperometric sensors the electrodes must be electrochemically active in order to minimize polarization resistance impact to the total sensor resistance. Taking into account that solid oxide sensors have a small size, noble metals can be employed as electrodes. In a sensor the reference electrode (RE) must be in contact with an atmosphere with a known concentration of electrochemically active gas component. In an oxygen EPS, ambient air as a rule is used as a reference gas. In some cases, oxygen is used as a reference gas; generally, oxygen in the

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atmosphere is generated by electrochemical pumping of oxygen to the sensor’s RE [59]. In the case of hydrogen or steam sensors based on a protonconducting electrolyte, the reference gas is hydrogen; the hydrogen atmosphere is supplied to the RE by electrochemical pumping [60,61]. Various materials can be used for REs: at the first stages, platinum was utilized for this purpose, sometimes silver (see, e.g., Ref. [62]), and then many oxides: manganites, cobaltites, nickelates, and ferrites. Up to date, platinum is the most often used material as RE. Some metal/metal oxide mixtures such as Ni/NiO or Cr/Cr2O3 [11] are characterized by a strong dependence of oxygen partial pressure on temperature and can be used as the reference oxygen potential if the sensor’s temperature is maintained constant. There is a great variety of sensing electrodes (SEs) (called also working electrodes or measuring electrodes) in the MPSs. At the first stage, various metals or alloys were used as SEs: Au [63], Pt [6466], Mo or binary alloys of Pt with one of the following elements: Ag, Au, Ni, Cu, and Rh [67]. Later, simple or complex metal oxides were used as the SEs: ZnO or CuO/ZnO [62,6871], CdMn2O4 [73,74], Nd2CuO4 [75], a combination of CdO and SnO2 [76,77], CdCr2O4 [7880], WO3 [81,82], NiCr2O4 [72], ZnCr2O4 [83,84], La0.6Sr0.4Fe0.8Co0.2O3 [85], La0.8Sr0.2CrO3 and La0.6Sr0.4MnO3 [62], La0.6Ca0.4A12xBxO3 (A 5 Mn or Cr, B 5 Ni or Fe) [86], MNb2O6 (M: Co, Ni, Zn, Ni) [87], CuCrFeO4 [88], La0.8Sr0.2CoO3 [89], La0.8Sr0.2MnO3 [90], CoMoO3 [91], Fe0.7Cr1.3O3, ZnCr2O4, Fe2NiO4, La0.8Sr0.2CrO32δ [84], MgO-doped (0, 1, 3, 5, and 8 at.%) BiVO4 [92], SnO/Zn2SnO4 [93], CoTiO3 [94], (Ni, Co, Fe) oxide/tin oxide [95], and NiFe2O4 [96,97]. Metal oxides composed with noble metals were also used as SEs: Nb2O5, Ga2O3 and In2O3 (all composed with gold) [63], NiO 1 3 wt.% Rh [98], Pt/YSZ modified with TiO2 [99], Co3V2O8 1 3 wt.% Rh [100], and NiO 1 5 wt.% Au [84].

6.3.3 Sealants In all types of sensors excluding MPSs with gas-symmetric arrangement, sealant materials are used in order to provide mechanical strength and hopeful separation of the sensors’ spaces. At the early stage, Pyrex seal was used in a coulometric sensor [101]. Haaland [23] utilized platinumzirconia seal for sealing two electrochemical cells into a small sensing unit.

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Maskell and Steele [102] used a gold seal for constructing an amperometric sensor. With the development of solid oxide electrochemical devices, many sealants were discovered, investigated, and elaborated. The main requirements to these sealants are (1) low electrical conductivity, (2) acceptable mechanical robustness, and (3) a long-term stability as they may be exposed either to oxidizing or reducing conditions. For these reasons, today the development of glass or glassceramic sealants is dominated. The glassy-based sealants offer the opportunity to use the optimal glass chemical composition, including also another material (e.g., ceramic) modifying in that way their characteristics. In solid oxide fuel cells (SOFCs)’ literature, two main categories of glassy sealants appeared: (1) the glassceramics and (2) the pure amorphous glass. Practically all sealants suitable for SOFCs can be successfully applied to sensors fabrication. 6.3.3.1 Glassy sealants The glassy sealants should present (1) high thermal stability, (2) good adherence with the rest components that comes into contact with, (3) thermal expansion coefficient (TEC) in the range of 8.512.0 3 1026K21, (4) chemical compatibility with the other materials of the sensor, and (5) good stability under oxidizing, reducing, and wet atmospheres [103]. The networks of glassy sealants are consisted of various oxide components (intermediates, modifiers, etc.), which present high field strength, polyhedral units, and low coordination number. The SiO2 and B2O3 are the most common networks used for the glassy sealants manufacturing. Then, in order to modify these networks, other substances (modifiers) are used, which can establish nonbridging oxygen species resulting in nonlinked polyhedral units [104]. Today, in literature alkali, alkaline earth oxides and especially Al2O3 are the most prevalent glass network modifiers. In order, the glassy-sealant properties to be tailored, rare earth and transition metal oxides should be added (the additives) [105]. The main disadvantages of the glassy sealants stem from (1) the known “combined ion effect,” which causes deviation from the “additive rule” [104,106], (2) “boron anomaly” (borozyl groups are converted to borate groups), and (3) lack of knowledge of glass composition, structure, and property relations. The glassy-sealant properties are defined by the cations coordination number, the length and the angle of the cationoxygen bond, the degree of network connectivity, and local ordering in the network structure [105].

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In literature, SiO2BaO-based glass systems such as SiO2BaOCaO Al2O3, SiO2BaOAl2O3, and SiO2BaOB2O3 have been studied. Da Silva et al. [107] replaced part of the SiO2 into BaOSiO2Al2O3 ternary glassy system by B2O3 in order to reduce its melting temperature below 1500°C. The as-fabricated glassy systems, being used as sealant between anode and electrolyte, show good chemical compatibility with YSZ and high characteristic bond strength. Lee et al. [108] reported that when the content of BaO into SiO2B2O3BaO ternary glassy system was up to 55 mol.%, the glass transition and TEC increased. The role of BaO in those systems was tried to be decoded by Holbrook et al. [109] by replacing BaO with Na2O. They observed that there were three elastic phases of the BaO, whose presence depends on the BaO content. These elastic phases form the glass transition temperature. Due to those disadvantages, the relative works are very restricted, since the majority of the scientists have turned into glassyceramic sealants. 6.3.3.2 Glassy-ceramic sealants The glass that is used in this category of sealants has a physical compact crystallize structure and it is much harder than other glasses. Due to this characteristic, this kind of glass is not modified when the coefficient of thermal expansion remains stable over time. Usually, a glassceramic sealant is placed between the electrolyte [110] (the most common is yttriazirconia). The all joint materials must achieve a good and homogeneous thermomechanical and thermochemical compatibility among them. Specifically, the sealants have to remain the same value of TEC with the surrounding materials. Today, most of the researchers focus on the BaO-based ceramic-glass systems [111], since it has been proved that the BaO inclusion has as result the reduction of glass transition temperature as well as glasssoftening temperature and the TEC increment. The BaAl2Si2O8 monocelsian phase is the ideal one and can take a TEC value equal to 23 3 1026K21 [112]; nevertheless, the common problem is the participation of BaO into reactions at the steel interface that lead to the formation of BaCrO4, which in turn has a TEC value 20 3 1026K21, causing sealants division and spallation. Eichler et al. [113] studied the (BaO  Al2O3  SiO2)-glass and found that the crystallization rate can be regulated within wide limits by means of MgO addition. Some reviews on sealants for SOFC application was

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published last time (see, e.g., Refs [114,115]). One of the latest reviews on material selection for SOFC technology including sealants was published in 2015 [116]. According to Qi et al. [117] the BaO  Al2O3  SiO2  MgO glassy-ceramic sealant, in comparison to the amorphous SiO2  Al2O3  ZrO2  CaO  Na2O glassy sealant, presented better characteristics when was used in electrochemical oxygen sensors More specifically, the average temperature coefficients of the linear extension were calculated 10.0 3 1026°C 21 and 9.5 3 10 26°C21, for 45% SiO2  15%Al2O3  25%BaO  15%MgO and 60%SiO2  10%Al2O3  10% ZrO2  5%CaO  15%Na2O, respectively. Many works appeared in literature, in which different compositions and additives to the BaO  Al2O3  SiO2  MgO  X (X 5 Li2O [118], 5 B2O3SrO [119], 5 CaO [119121]) system were examined. Usually, according to the glassceramic sealants manufacturing methods, the preceramic polymer is totally burnt-out, and it is the sacrificial binder [122]. On the contrary, Elsayed et al. [123] proposed recently a novel-fabricating procedure, using silicones as preceramic polymer. When silicones are burnt at about 500600°C, it leaves behind a ceramic residue, which contains amorphous silica or silicon oxycarbide—a fact that makes silicons to keep glass particles together, even after firing [124]. It is referred that their glassceramic sealant based on CaO  MgO  Al2O3  SiO2 system for solid oxide cells presents a TEC value of 9.5 3 1026K21. The inclusion of aluminum nitride (AIN) dopant into borosilicate glasses and glassceramics was recently reported by Li et al. [125], aiming at modifying their characteristics to the optimum values. Specifically, it is shown that the AIN addition enhances thermal stability and chemical compatibility with Y2O3ZrO2 electrolyte. Moreover, in comparison to the undoped sealant, it presents lower conductivity and significantly reduced electrical conductivity. Oxynitride glasses enhance the network glass structure, due to the fact that two-coordinated oxygen is replaced by a three-coordinated nitrogen [126]. The addition of nitrogen significantly improves Young’s modulus, the electrical resistance, and glass-transition temperature [127]. By doping the boron-based glassceramic sealant with nitrogen oxide, Ren et al. [128] managed the volatility of boron and the consequent poisoning of the La0.6Sr0.4Co0.2Fe0.8O3 (LSCF) cathode in a SOFC. The NiO dopant increases the SiOB linkages and suppress the reaction between the cathode and the sealant.

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The addition of alkali oxides as modifiers into a glass network structure, is another novel method, recently adopted by many researchers [129,130], in order to increase the TEC values of the glass matrix and to tailor the thermomechanical properties of the glassceramic sealants. Very recently Sato et al. [131] deposited a patent reporting a glass composition substantially free of alkali metal oxides, containing 1225 mass% SiO2, 1020 mass% B2O3, 1830 mass% CaO, 1530 mass% MgO, and 10.527 mass% BaO, wherein the glass composition, when fired in the form of glass powder at a temperature of 850°C1050°C, forms a crystallized glass that exhibits a TEC of at least 130 3 1027°C21 in the range of 50°C800°C.

6.4 Types of sensors 6.4.1 Potentiometric sensors A sensor consists of an electrolyte and at least two electrodes. The sensing signal in potentiometric sensor is the potential difference between the two electrodes attached to the electrolyte. The electrodes can be placed onto the opposite sides of the electrolyte wall (in EPSs, and in some configurations of MPSs) or at the same side (as a rule used in MPSs). EPSs are utilized for analysis of equilibrium gas mixtures, whereas MPSs are used for the analysis of nonequilibrium gas mixtures, where oxygen coexists with H2, CO, NOx, NH3, hydrocarbons (HC), and volatile organic compounds (VOCs). In an EPS, both electrodes must have an equilibrium potential in the corresponding gas atmospheres. In an MPS, only one of the electrodes must be in equilibrium with surrounding atmosphere. 6.4.1.1 Equilibrium potentiometric sensors 6.4.1.1.1 Operation principle The operation principle of the potentiometric sensors is based on the open circuit voltage (OCV) measurements (in the past the term “EMF,” was more popular), where the electrolyte with reversible electrodes represents a concentration cell subjected to a gradient of chemical potentials of the ionic species i. μ1 ð

E52 μ2

t dμ nF i

(6.2)

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where μ1 and μ2 are the chemical potentials of species i, ti is the ionic transport number for species i, n is the number of electrons involved, and F is the Faraday constant. Considering that μi 5 μoi 1 RT lnpι

(6.3)

the following equation can be obtained: pð2

E 5 2RT

ti dlnpi nF

(6.4)

p1

where R is the universal gas constant, T the absolute temperature, p1 and p2 are the partial pressure potential-determined gas on the opposite sides of the concentration cell. The integrating procedure results in E 5 2ti

RT p2 ln nF p1

(6.5)

Eq. (6.5) can be transformed to Eq. (6.6) for oxygen-ion (O22) conductors: 0

RT p O2 E 5 tO ln 5 tO EO 4F p00 O2

(6.6)

where EO is the thermodynamic OCV values of an oxygen concentration cell under oxygen partial pressure difference (p0 O2 , p00 O2 ) and tO is the oxygen ions transport number. As a rule, solid oxide electrolytes with a negligible part of electronic conductivity are used for the oxygen sensors, so in Eq. (6.5), tO 5 1. Oxygen sensors can be applied not only for measuring an oxygen concentration in its mixture with other gases without interacting with oxygen (inert gases, N2, CO2, H2O) but also for measuring the H2/H2O or CO/CO2 ratio in corresponding mixtures. From the following reactions: 1 H2 O#H2 1 O2 and 2

(6.7a)

1 CO2 $CO 1 O2 2

(6.7b)

Sensors based on solid oxide electrolytes

one can express oxygen partial pressure in the following forms:   pH2 O 2 pO2 5 K1 and pH2 

pCO2 pO2 5 K2 pCO

179

(6.8a)

2 (6.8b)

where K1 and K2 are the equilibrium constants of the chemical reactions (6.7a) and (6.7b), respectively. Substituting pO2 from Eqs. (6.8a) and (6.8b) in Eq. (6.6) and assuming tO 5 1, one can obtain     RT pH2 0:5 EH2 =H2 O 5 ln pO2 3 (6.9a) 2F K1 pH2 O     RT pCO 0:5 ln pO2 3 ECO=CO2 5 2F K1 pCO2

(6.9b)

When oxygen is used as a reference gas, the EMF can be calculated by the following equations [132]:     13008 pH2 O EH2 =H2 O 5 0:0992 2:947 2 T (6.10a) 1 log T pH2    14700 pCO2 1 log T ECO=CO2 5 0:0992 4:505 T pCO

(6.10b)

Eq. (6.5) can be transformed to Eq. (6.11) for a protonic (H1) conductor and to Eq. (6.12) for coionic (O22, H1) conductors: 00

E 5 tH 0

RT p H2 ln 5 t H EH 2F p0 H2

(6.11)

00

RT p O2 RT p H2 E 5 tO 1 tH 5 tO EO 1 tH EH ln 00 ln 4F p O2 2F p0 H2

(6.12)

where EH is the thermodynamic OCV values of a hydrogen concentration cell under partial pressure differences of hydrogen (p0 H2 , p00 H2 ) and tH is the protons transport numbers. Expressing the hydrogen partial

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pressure with Eq. (6.8a) and substituting it in Eq. (6.12), the following equation can be obtained: 0

00

RT p O2 RT p H2 O E 5 ti 1 tH ln 00 ln 5 ti EO 1 tH EH2 O 4F p O2 2F p0 H2 O

(6.13)

where EH2 O represents the thermodynamic OCV value of water vapor concentration cell under the created difference of water vapor pressures (p0 H2 O, p00 H2 O) and ti 5 tO 1 tH is the ions transport number. Therefore considering certain conditions and knowing the experimental OCV value and the gas composition in the reference atmosphere, it is possible to analyze the composition of the second gas atmosphere. This simple principle led to the basic operation for most of the EPSs. 6.4.1.1.2 Reference electrodes In the first designs of EPSs an RE was supplied by air where the oxygen partial pressure was known and equaled to 0.201 atm in average. In some cases, oxygen was used as the reference gas. In the initial stages of EPSs based on proton-conducting electrolytes investigation, hydrogen or mixtures of hydrogen and inert gases with fixed hydrogen content were used as the reference gas. A scheme of this sensor design is shown in Fig. 6.1A. The main inconvenience in the first EPSs’ exploitation was the necessity to supply the RE with the gas with of the known concentration of the electroactive components. The problem was solved by the application of a Me/MeOx system as RE (called also “solid standard”), for instance, Cr/Cr2O3 [11,133]. Me/MeOx powder is placed in the hermetically closed sensor chamber (Fig. 6.1B), thus providing the known pO2 value at a definite temperature. (A)

V

(B)

V

(C)

V

(D)

V

Reference gas

S

S

1 2 3 4 5

Figure 6.1 Schematic illustrations of EPSs: with reference gas supply from outside (A), with solid standard (B), with reference gas supply by electrochemical pumping in tubular design (C), and in planar design (D). 1 is solid electrolyte, 2 is solid standard powder, 3 is electrodes, 4 is inert material, and 5 is sealant. V stands for voltmeter and S for current source. Thick arrows show the flow direction of the analyzed gas. EPSs, Equilibrium potentiometric sensors.

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In this case the sensor does not need a reference gas and its design is simpler. Temperature dependences of pO2, in the case of different Me/MeOx RE (and hence the potential of such electrode against pure oxygen electrode), can be calculated on the basis of temperature dependences of standard free energy of MOx formation, which was first reported by Ellingham [134]. Yajima et al. [135] used an AlPO4  xH2O:La0.4Sr0.6CoO32δ (1:9 in weight) as a solid standard electrode in SrCeO3-based hydrogen and steam sensors. Schwandt and Fray [136] demonstrated that a mixture of solid solutions of hydrogen in α-titanium and β-titanium may be applied as a solid-state hydrogen RE in high-temperature, proton conductingbased hydrogen sensors. A new solid-state hydrogen RE based on a two-component two-phase mixture of b-zirconium and d-zirconium hydride was developed few years ago [137]. It was demonstrated that this electrode is suitable for use in conjunction with the high-temperature proton-conducting CaZr0.9In0.1O32δ solid electrolyte. Another way to avoid supplying the RE with a standard gas is using an electrochemical pumping cell (externally apply an electric potentials) in addition to the measuring cell in order to create the required atmosphere inside the sensor chamber. The electrodes of the cells can be placed on the same tube (Fig. 6.1C), or the cells can be the separate plates glued to each other in such a way that the chamber is formed between them (Fig. 6.1D) [60,61]. 6.4.1.1.3 Isotope sensors Matsumoto et al. [138142] in a series of works proposed the principle operation and experimental model of an electrochemical H/D isotope sensor. They developed three different cells: H2, Pt|electrolyte|Pt, D2, H2, Pt|electrolyte|Pt, D2 1 H2; H2 1 D2, Pt|electrolyte|Pt, D2 1 H2 [electrolyte 5 CaZr0.9In0.1O32δ (CZI) and SrCe0.95Yb0.05O3 (SCY)]. They explained the EMF value by the following two factors: (1) the mobilities difference between proton and deuterium in the electrolyte and (2) the electrode reactions of H2 and D2 gases. Moreover, they discovered that the EMF of the sensor based on CZI electrolyte exhibited linear dependence on temperature, though the measured EMF was much lower than theoretical one.

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6.4.1.1.4 Humidity sensors In 1983 Iwahara et al. [143] reported the application of SrCeO3 protonic electrolyte as the base for the humidity sensor. The sensor was tested in air atmosphere in the range of 300°C400°C. The value of water vapor partial pressure at the one side of the electrolyte membrane was kept at a constant level (p00 H2 O 5 0:006 atm), whereas at the other side, it was widely changed (p0 H2 O 5 0:0080:135 atm). The sensor showed close to linear response of the measured EMF depending on p0 H2 O. Nagata et al. [144] proposed a humidity sensor with SrCe0.95Yb0.05O3 solid electrolyte. It was a sensing system operated at 205.6 3 103 Pa PH2 O with both O2 and H2 gases at 873K1273K. The system was Pt, gas 1 H2O/SrCe0.95Yb0.05O3/air 1 H2O (RE), Pt. The EMF of the sensor exhibited good reversibility and rapidly responding to the changes of humidity and temperature. 6.4.1.1.5 Hydrogen sensors Iwahara et al. [145] for the first time developed a hydrogen sensor based on proton-conducting ceramic materials. They used a material with BaCe0.9Nd0.1O32δ (BCN) composition in a concentration cell of H2, Pt| SCY|Pt, H2 1 Ar type. The measured EMF values were close to theoretical ones; however, they differed from cell to cell. More appropriate results were obtained in the same group when the authors used AlPO4  xH2OLa0.4Sr0.6CoO3 (APLSC) as RE and CaZr0.9In0.1O32δ as electrolyte [146]. They developed and characterized the properties of the H2 1 Ar, Pt|CZI|Pt, and APLSC cell. The as-fabricated sensor demonstrated high accuracy for hydrogen concentration analysis. Recently, Okuyama et al. [147] developed a galvanic cell based on Mn-doped CaZrO3 (CZM). Such galvanic cell operated as a hydrogen sensor, using wet air as a reference atmosphere and wet H2/Ar mixture as the analyzed (working) atmosphere: wet H2 1 Ar, Pt|CZM|Pt, wet air. The obtained data shown that the experimental results satisfy Eq. (6.11) in the hydrogen rich atmosphere, where tH 5 1. 6.4.1.1.6 Sensors for melts’ analysis As it was mentioned earlier, solid-electrolyte cells were used for measuring solubility of oxygen in liquid metals (lead and tin) in the middle of 1960s [8,9]. In 1966 Littlewood [148] published the first review of EMF methods for oxygen determination in molten metals where particular attention was given to the measurement of oxygen in molten steel. Since that,

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many works have been appeared on sensors for oxygen determination in molten iron or steel [11,34,39,149155]. In 1968 Wrench and Inman [156] reported the results of potentiometric studies of oxygen ions concentration in molten salts, namely, in lithium chloridepotassium chloride eutectic. In 1988 Iwase [157] reported on determination of silicon activities in molten FeCSi alloy. At the first stages the sensors’ design was similar to the one shown in Fig. 6.1A, and the reference gas was air. In order to suppress the electronic conductivity in zirconia-based electrolytes due to great difference in pO2 in molten steel and in a reference gas when air is fed to the RE, it was proposed to use Cr/Cr2O3 as oxygen reference potential [11,133]. An alternative to zirconia-based electrolyte for application in the sensors for liquid metals analysis, is thoria-based electrolytes [158] or zirconates [39], which have lower part of electronic conductivity at high temperatures (above 1600°C) compared to zirconia-based electrolytes. The sensors for measuring the content of gases in melts can be fabricated in different designs. Tubular sensor (Fig. 6.2A) represents a thinwalled solid-electrolyte tube, closed at one end (it can be also glued into an alumina tube by the open edge). The sensor of cup-shaped design represents the electrolyte tube, which is glued into the alumina tube by the closed end (Fig. 6.2B). In the plug-type sensor (Fig. 6.2C) a solidelectrolyte plug is glued into an alumina cap. In all the abovementioned type of sensors the reference gas is fed via a metallic tube to the reference Pt electrode. The reference gas is air in the

Figure 6.2 Different designs of potentiometric sensors for measuring gas content in melts: tubular sensor (A), cup-shaped sensor (B), plug-type sensor (C), and needle sensor (D).

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sensors based on an oxygen ion electrolyte and a mixture of Ar 1 1% H2 in the case of sensors based on a protonic electrolyte. As it was abovementioned, the porous Pt in contact with Me/MeOx powder can serve as the RE in the oxygen sensor. The sensor design in this case is similar to that shown in Fig. 6.2D, where a metallic rod is used instead of a tube and the rod is hermetically sealed at the open end of the ceramic closed end tube filled with Me/MeOx powder. The main advantage of this sensor design is that it does not need a reference gas. The further development of the latter design is the so-called needle sensor (Fig. 6.2D). The core of this sensor can be a metallic thin rod covered with porous Me/MeOx layer and with a dense ZrO2- or ThO2-based electrolyte layer over the former. This sensor design was first reported by Janke [34,35] who claimed that promising results were obtained with this sensor in iron melts. Oxygen sensors for steelmaking industry are widely utilized since the beginning of 1970s. It is interesting to mention that in far 1987, more than a half million (518,653) pieces of oxygen sensors were consumed in Japanese steelmaking companies [159]. A single manufacturer (Nippondenso) was reported to having produced nearly 100 million zirconia oxygen sensors per year for different applications, covering 70% of the Japanese market [160]. Problems with sensors for steelmaking were discussed in literature [56]. The authors pointed out the following reasons for distortion of the sensors’ readings: n-type and p-type electronic conduction, oxygen permeability and overvoltage at liquid steel/solid electrolyte interface, overvoltage at solid electrolyte/reference interface, thermal-shock resistance of solid electrolyte. Several methods to minimize errors in measured EMF were suggested by the authors. In 1993 Yajima et al. [161] reported the development of the so-called cup-shaped sensor based on CaZr0.9In0.1O32α protonic electrolyte for the analysis of the hydrogen content in molten aluminum. Using experimental data, they estimated the hydrogen solubility in the nominal pure Al (99.99%), finding good correlation with other literature data. Later, the utilization of such a sensor for measuring hydrogen in molten AlCuZn alloy [50] and for measuring hydrogen in molten copper [162] was reported. In 2008 Kondo et al. [163] reported the utilization of hydrogen sensor based on the CaZr0.95Sc0.05O32α protonic electrolyte in LiFBeF2 molten salt, liquid metal lithium (Li), and lead-17 lithium (Pb17Li).

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6.4.1.1.7 Sensors for automotive application As it is mentioned earlier, the first scientific paper on sensors for automotive application appeared in 1973 [18]. Development of these kinds of sensors was stimulated by legislating in the early 1970s the US Clean Air Act, which required automobile manufacturers to reduce exhaust gases, such as carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NOx), by about 90%. Since then, many laboratories, mainly connected with the industries, developed various sensors for measuring oxygen concentration and detecting harmful components in the exhaust gases. The sensor for measuring oxygen concentration in exhausts is today known as “lambda sensor.” It works as an equilibrium potential sensor. ZrO2 stabilized by Y2O3 or by Y2O3 with MgO is the most important material used for the manufacturing of lambda sensors [160,164]. The first samples of the lambda sensors had no desired properties because of not perfect design and short life-time caused by poisoning electrodes and abrasive corrosion. Step by step, the sensor design has been improving, and by the end of the 1970s, its performance became quite suitable for a long application in cars. In 1980 Gruber and Wiedenmann mentioned 3 years’s field experience on lambda sensors in automotive control systems [165]. The lambda sensor shows a low signal when oxygen is present in the exhaust and a high signal when combustibles are present. At a perfectly balanced air/fuel ratio of 14.7:1, the lambda sensor delivers a signal of 450 mV. In the first versions of the lambda sensors, even a slight deviation from the above ratio caused a sharp decrease or increase in the signal value in the case on lean or rich fuel mixtures, respectively. In the later version of the sensor, so-called wide-band lambda sensor, the signal changes very smoothly with the deviations from the perfect ratio. Moreover, the last models of the sensors are equipped with an internal heater. They can reach the operating temperature of 800°C within 20 s, having a response time less than 0.1 s [166]. It is worth to mention that oxygen sensors based on the above principle are widely used for combustion control in many areas, such as heat-treatment furnaces, glass tank furnaces, ceramic kilns, boilers, oil and gas stoves since the 1970s [160]. The secondary purpose of the gas sensor is measuring the concentration of other exhaust gases, such as CO, NO, and H2. These sensors belong to mixed potential or to amperometric ones and are described in Sections 6.4.1.2 and 6.4.2.

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6.4.1.2 Mixed potential sensors Contrary to EPSs used for the analysis of equilibrium gas mixtures, the MPSs are used for the analysis of nonequilibrium gas mixtures containing apart oxygen combustibles such as H2, CO, HC, or nitric oxides (NOx). MPSs consist of an oxygen electrode (reference) and an SE (working, called also “measuring”), which has a low oxygen sensitivity but a high sensitivity to other gas components. Both electrodes of the MPS can be exposed to the analyzed gas in the so-called gas-symmetric arrangement (Fig. 6.3) [167], or the MPS design can be similar to the one presented in Fig. 6.1, if the SE is the outer one. In the former case the RE, as a rule, is made of Pt or Ag and the working electrode is based on metal oxides. In the latter case the RE is platinum and the SE can be also platinum [64,66], or one of the materials mentioned in Section 6.3.2. Okamoto et al. [6466] found that the EMF of zirconia-based galvanic cells, O2(I) 1 CO, Pt/stabilized ZrO2/Pt, and O2(II) became anomalously higher than the theoretical one calculated from Nernst’s equation, when PCO/PO2 ðIÞ , 2, at lower temperatures such as 350°C. This anomalous EMF is caused by the presence of a mixed-electrode potential. This potential derives from the electrochemical reactions of O22 ions from the solid electrolyte with the CO and the oxygen molecules, both adsorbed on Pt during the CO oxidation on Pt. Miura et al. [73] reported on a new type NOx sensors designed by using stabilized zirconia and an oxide SE. Among the various oxides examined for the SE, CdMn2O4 was found to be the most excellent one. Both planar and tubular devices attached with a sputtered CdMn2O4 layer could respond well to NO2, as well as to NO in air at higher temperature, such as 500°C. Reviews on the mixed potential zirconia-based sensors were presented in literature during the last two decades [168171]. A review of electrochemical NOx sensors was published in 2017 [172]. A detailed description

Figure 6.3 Gas symmetric arrangement of mixed-potential sensor from two sides [167]. H, Heater; ME, measuring electrode; RE, reference electrode.

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of the MPSs including principles and electrode materials sensitive to various gases is recently summarized [167]. The catalytic effects of various electrode materials on nonequilibrium oxygen measurements using solid-electrolyte oxygen sensors have been investigated by Haaland [173]. It was demonstrated that catalytically active electrodes can perturb the measurement of oxygen in nonequilibrium mixtures of oxygen and combustible gases. He stated the development of noncatalytic electrodes for accurate measurement of the free oxygen content in nonequilibrium gas mixtures containing O2 and CH4, C3H6, CO, or H2. The effects of Pt, Au, Ag, Ag deposited on Pt and S- or Pbpoisoned Pt electrodes on the measurement of oxygen in nonequilibrium gas mixtures were determined. The studies were made using solidelectrolyte oxygen sensors of a new internal-reference design as well as with traditional air-reference sensors. Pt electrodes are catalytically active in all of the gas mixtures studied. Both Ag electrodes and Ag vapor deposited on Pt were found to be noncatalytic to CH4 oxidation, while Au electrodes were only slightly catalytically active. MPSs were used for measuring concentrations of CO [62,6466,70, 76,77,88,174,175], H2 [62,69,71], NOx [7173,75,79,80,86,87,98, 100,172,176178], hydrocarbons (HC) [63,84,179], hydrogen sulfide [180], VOCs (acetic acid, methylethylketone, ethanol, benzene, toluene, o- and p-xylene) at sub-ppm levels [99,181,182], offensive odorants (ammonia, trimethylamine, methyl mercaptan, and hydrogen sulfide) [183], and SO2 [184]. A review on trends in electrochemical detection of NH3, H2S, and NOx was published in 2017 [185]. Practically all investigations of MPS are useful for the development of the sensors for automotive application. Among special studies in this field the following works can be mentioned [186188]. Romanitsya et al. [186] studied an application of advanced morphology AuX (X 5 YSZ, ZrO2) composites as SEs for solid state mixed-potential exhaust NOx sensor. The authors showed that the addition of YSZ in the Au electrode decreased the polarization resistance in air, made a shorter response time, and a higher sensitivity to NO2 comparing to Au electrode without additives. Viricelle et al. [187] designed and studied an electrochemical cell consisting of three metallic electrodes placed on YSZ electrolyte operating under polarization between a gold working electrode and a platinum counter electrode. The cell allows selective NO2 detection at 400°C550°C with high sensitivity, and without any significant interference with other gases, such as hydrocarbons,

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Solid Oxide-Based Electrochemical Devices

carbon monoxide, as well to ammonia and nitrogen monoxide. Javed et al. [188] developed a model of an array of four MPSs to identify and quantify gas components in complex mixtures containing NOx/NH3/ C3H8 in diesel engine exhaust. The authors claimed that their approach can be used to decipher contents of complex gas mixtures of unknown composition in numerous industrial, automotive, and national security settings. Among the latest works on the MPSs, it is worth to mention the ones of Liu et al. [91], Tsui et al. [189], Xu et al. [96], Bhardwaj et al. [95], Zheng et al. [82], Wang et al. [94], and Wang et al. [93]. Liu et al. [91] have developed an YSZ-based mixed potential type gas sensor utilizing CoMoO4 SE to realize the effective detection of triethylamine (TEA) at 600°C. The response value of the fabricated sensor displayed the piecewise linear function to logarithm of TEA concentrations and the sensitivities were at 214 mV dec21 (0.15 ppm) and 253 mV dec21 (5200 ppm), respectively. Tsui et al. [189] fabricated an YSZ-based three electrode La0.8Sr0.2CrO3, Au0.5Pd0.5, Pt MPS for NOx/NH3 quantification. The stability of the sensor during a period over 100 days was monitored by electrochemical impedance spectroscopy. Xu et al. [96] described a superior sensitive NiFe2O4 electrode for the mixed-potential NO2 sensor. The sensor exhibited the maximum response (81.3 mV to 100 ppm NO2) at 400°C and an optimal sensitivity of 82.8 mV dec21 at 450°C. Bhardwaj et al. [190] developed the NO2 sensor equipped with Fe2O3SnO2 (Fe:Sn 5 2:1) nanocomposite SEs. The sensor showed the maximum response of about 60 mV toward 100 ppm NO2 with a relatively fast response and recovery dynamics at an operating temperature of 650°C. The sensor also shows a linear dependence of response over the logarithm of NO2 concentration with a sensitivity of 44 mV dec21. Zheng et al. [82] fabricated a NO2 sensor, using mesoporous WO3 with diameter of 7 nm and specific surface area of 209 m2 g21 as the SE deposited onto YSZ substrate. The sensor showed high sensitivity to NO2 over the concentration range of 0.0610 ppm at 500°C and the electric potential difference (ΔV) presented good linear correlation with the logarithm of NO2 concentration. Wang et al. [94] developed a high-response mixed potential type YSZ-based planar NO2 sensor utilizing CoTiO3 SE. The sensor exhibited high responses to NO2 in the concentration range of 500 ppb200 ppm,

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as the value of the response was 130 mV to 100 ppm NO2. A linear relationship was observed between the ΔV of the sensor and the logarithmic scale of the NO2 concentration, the sensitivity of which was 60 mV dec21. Wang et al. [93] fabricated an YSZ-based highly sensitive acetylene sensor based on porous SnO2/Zn2SnO4 as SE. The sensor was able to effectively detect acetylene (C2H2) at 700°C. In terms of the sensing characteristics of the C2H2 gas sensor, the response value toward 100 ppm C2H2 was 282.3 mV, and the detection limit of C2H2 was lowered to 500 ppb. The response of the sensing device varied piecewise linearly with the logarithm of C2H2 concentration range of 0.52 and 51000 ppm, with sensitivities of 212 and 256 mV dec21, respectively.

6.4.2 Amperometric sensors As it was previously reported, Ruka and Parson in 1972 patented the “Method for polarographic measurement of oxygen partial pressure.” It is interesting to point out that this patent was a continuation of the patent application of 1968 entitled “Solid State Polarographic Oxygen Gauge.” Therefore the idea of such sensors appeared in the end of the 1960s. The operating principle of electrochemical sensors with diffusion barrier is well known and it is described in many experimental works that appeared in the international literature [14,16,28,36,37,102,191195]. It consists of an electrochemical cell equipped with a diffusion barrier. There are different types of diffusion barriers, some of which are stated as follows: 1. A porous coating applied onto the sensor cathode or the porous cathode can serve as such a barrier through the pores of which diffusive gas exchange takes place [14,193]. 2. A porous support, for instance, porous alumina, also can serve as diffusion barrier [196]. 3. A mixed ionicelectronic conductor, made of metal oxides (e.g., manganites or cobaltites [197]) or Pt-YSZ dense composite, can be used as diffusion barrier [198]. 4. A channel in the body of a solid electrolyte or of an inert material plate can also act as diffusion barrier [194] (Fig. 6.4A). 5. A thin ceramic or metallic tube (capillary) was used as diffusion barrier [191,199201] (Fig. 6.4B).

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Solid Oxide-Based Electrochemical Devices

Figure 6.4 Schematic illustrations of amperometric sensors with an internal chamber with different types of a diffusion barrier: a hole in an inert material (A), a capillary (B), and surface irregularities on an electrolyte disc and an end of an inert material cup. 1 is solid electrolyte, 2 is sealant, 3 is electrodes, and 4 is inert material.

6. A narrow plane channel between the electrolyte disc and the end of an inert material cup existing due to surface irregularities also can serve as diffusion barrier (Fig. 6.4C) [202]. In the cases 13 the sensor consists of a single plate with two electrodes placed on the opposite sides of the electrolyte plate (cases 1 and 3) or layer (case 2). In the cases 46 the sensor consists of two glued cells, one of which must be an electrolyte and the second can be an inert material. In the case 6 the two parts were joined by using the so-called diffusive welding at which these parts were pressed to each other and subjected the thermal treatment. This procedure provides the mechanical robustness of the sensor and forms a chain of connected pores, which presents a kind of a “narrow plane channel.” The proposed sensor allows measuring the oxygen concentration under conditions of sharp and considerable change of the total gas pressure. An explanation on the operation of the oxygen amperometric sensor with an internal chamber for measuring the oxygen concentration in its mixture with nitrogen (or inert gases) is given later. Upon applying voltage to the sensor electrodes the following reaction occurs at the internal electrode of the sensor: O2 1 4e 2 5 2O22

(6.14)

and oxygen is electrochemically pumped-out from the sensor chamber, due to the transfer of oxygen anions across the electrolyte from the internal electrode to the external one; thus the oxygen concentration inside the chamber decreases. Oxygen, existing in the initial gas mixture, moves into the chamber through the capillary by diffusion and viscous (at high oxygen concentration) flows and simultaneously is pumped out electrochemically (Eq. 6.14). The flow of oxygen evacuated from the chamber and the corresponding sensor current increases with the growing of the voltage applied to the sensor electrodes. Upon reaching a certain voltage

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value, sensor current ceases to increase and remains unchanged even when the voltage continues to rise. This corresponds to an oxygen concentration, inside the sensor chamber, close to zero. In its turn, this corresponds to the maximum oxygen flow rate from the outer space into the sensor chamber at a definite oxygen concentration in the ambient gas atmosphere. Therefore the sensor current reaches the maximum for the definite oxygen concentration in the outer space; this current value is called limiting current. It does not change when the applied voltage grows. Thus on the VI curve, a horizontal part (plateau) is observed (Fig. 6.5A). The relation between the applied voltage and the sensor’s current is given below: U 5 E 1 IR 1 ηa 1 ηc ;

(6.15)

Figure 6.5 Typical VI curves of amperometric sensors with an electrolyte having pure ionic conductivity: (A) for different oxygen partial pressures in a row p1 . p2 . p3 . p4; (B) at different temperatures in a row: t1 . t2 . t3 . t4; (C) in case of the mixture G 1 O2 1 H2O (or CO2), G 5 N2 or inert gases; and (D) typical VI curve in case of an electrolyte having a small component of electronic conductivity.

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Solid Oxide-Based Electrochemical Devices

where E is defined according to Eq. (6.6), I is the current, R the Ohmic resistance, ηa and ηc are the anode and cathode overpotentials, respectively. If the current for the oxygen pumping out comprises the 99% of the current required for the complete oxygen pumping out, the EO value does not exceed 100 mV at the sensor operation temperature below 700°C. When free oxygen disappears from inside the chamber, Oxidized components (Ox 5 H2O or CO2), existing in some quantities in the analyzed gas, are electrochemically decomposed forming Reduced components (Red 5 H2 or CO) and oxygen ions. The oxygen partial pressure is determined by the equilibrium in Ox 1 Red mixture (Eqs. 6.7a and 6.7b) and its partial pressure is calculated according to Eqs. (6.8a) and (6.8b). If 1% of Ox component is decomposed, the EMF of the system O2, (pO2)|O22| Ox(pOx) 1 Red (pRed) is about 1100 mV (at T , 700°C). Therefore the current can visibly be increased if the applied voltage is by B1000 mV higher than that at the plateau beginning; thus the plateau “width” for the oxygen amperometric sensors is about 1000 mV. At higher voltage values the current can further increase if H2O (or CO2) exists in noticeable quantity in the analyzed gas. A similar consideration can be applied to the amperometric sensors based on protonic electrolytes in the case of analysis of H2 1 N2 1 H2O gas mixtures. Under the same conditions (99% of initial hydrogen is pumped out), the EH value is about 200 mV at T , 700°C (compare Eqs. 6.6 and 6.11). If 1% of H2O is decomposed to O2, and protons according to the following reaction H2 O 5 0:5O2 1 2H1 1 2e2

(6.16)

the EMF of the system H2 (pH2)|H 1 |H2O (pH2 O ) 1 O2 (pO2) is about 700 mV, and the “plateau” width for the hydrogen amperometric sensors is about 500 mV at temperatures below 700°C. The following increase of current can be related both with steam decomposition according to Eq. (6.16) and with the appearance of hole conductivity in the protonic conductor due to oxidizing atmosphere apparition. Two types of diffusion control can be distinguished: 1. If the hole (or capillary) diameter is larger than 10 μm, three flows take place in it: a diffusion flow of oxygen into the chamber, a diffusion flow of the second component from the chamber, and a viscous

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193

flow of the ambient gas mixture into the chamber. The limiting current for the oxygen sensor is given by the following equation: Ilim 5 2

 4FDSP  ln 1 2 XO2 RTL

(6.17a)

where D is oxygen diffusion coefficient in nitrogen, S the cross-sectional area of a diffusion channel, L the length of the diffusion channel, P the pressure of the analyzed gas in Pascal, T the temperature of the analyzed gas, and XO2 the molar fraction of oxygen in the analyzed gas. The limiting current for the hydrogen sensor is expressed as follows: Ilim 5 2

 2FDSP  ln 1 2 XH2 RTL

(6.17b)

At lower temperatures the first segment of VI curves can be more complicated (Fig. 6.5B). The very first part of the initial segment has a lower inclination than the rest of the part. This is because at low temperatures, the polarization obeys the Tafel equation: η 5 a 1 b log i

(6.18)

and electrodes’ polarization give predominate impact to the cell voltage at low currents. At higher temperature the electrodes’ polarization linearly depends on the current, thus providing a straight line at the beginning of the VI dependence. The VI curve has two plateaus if the analyzed mixture has a composition G 1 O2 1 Ox, where G 5 N2 or inert gas and Ox 5 H2O or CO2 (Fig. 6.5C). The first plateau corresponds to oxygen and the second one to Ox. Below is a brief explanation of the “two-plateau” VI curve. At definite voltage and current the oxygen concentration inside the chamber becomes zero. As it was discussed earlier, the sensor current increases if the Ox concentration is considerable. With the current increase, the Ox concentration decreases due to the following electrochemical reaction: Ox 1 O22 5 Red 1 2e2

(6.19)

where Red is H2 or CO. When the concentration of Ox component inside the chamber becomes zero, the current cannot increase further

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Solid Oxide-Based Electrochemical Devices

and the second plateau appears with the applied voltage increasing. The Ox concentration is related with the measured limiting currents by the following equation: Ilim2 2 Ilim1 5

2FDSP XOx RTL

(6.20)

If a “plateau” is not horizontal and it is characterized by less inclination than the initial sector, this testifies that the electrolyte has electronic conductivity. In this case an intersection of straight lines interpolated straight parts of the initial sector and “plateau” can be considered as the limiting current as it is shown in Fig. 6.5D. 2. If the hole (pores) diameter is very small (i.e., , about 1 μm), the Knudsen mechanism is prevalent and the limiting current is proportional to the electroactive component pressure [203]. Ilim 5 2zKd Fπd 2 P

(6.21)

where d is the diameter of the hole, P the electroactive component pressure, and z the charge number of Xz2 ions in the electrode reaction: X2 1 2ze2 -2Xz2

(6.22)

Kd is the Knudsen coefficient defined by Kd 5

d pffiffiffiffiffiffiffiffiffiffiffiffiffiffi 3L πMRT

(6.23)

where L is the hole length and M is the molar mass of the electroactive component. An amperometric sensor based on the CaZr0.9In0.1O32α protonic conductor was used for measuring the concentration of H2, C3H8, and CO [196]. Porous alumina was used as the diffusion barrier. A linear relationship was obtained between the limiting current and the partial pressure of these gases. By using the amperometric sensors, based on an oxygen ion electrolyte, it is possible to measure the concentration of such components as H2, CO, and CH4 in their mixture with nitrogen [62]. The sensor equipped with a metallic capillary similar to shown in Fig. 6.3B was used in this work. Traces of oxygen and steam (B10 ppm) always exist in nitrogen. Due to this, it is possible to provide oxygen ions transfer inside the sensor chamber by applying positive potential to the inner sensor

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195

electrode. Combustible gas components are oxidized at the inner electrode according to the following reactions: H2 1 O22 5 H2 O 1 2e2

(6.24)

CO 1 O22 5 CO2 1 2e2

(6.25)

CH4 1 4O22 5 CO2 1 2H2 O 1 8e2

(6.26)

The corresponding limiting current Ik,lim can be calculated by using the following equation: Ik;lim 5 zk Dk Xk

PFS LRT

(6.27)

where zk is the number of electrons participating in reactions (6.24) (6.26) and Xk the mole fraction of the k-component. The amperometric sensor of a similar design was applied for the measurement of ammonia concentration in nitrogen [204]. It was stated that the limiting current dependence on the ammonia concentration is linear in the concentration range from 0.1% to 5% at temperatures below 400°C. Moreover, it was stated that ammonia oxidation occurs according to the following reaction: NH3 1 1:5O22 -0:5N2 1 1:5H2 O 1 3е2

(6.28)

and neither NO nor NO2 are formed. Results on amperometric hydrogen sensors based on La0.95Sr0.05YO3 and CaZr0.90Sс0.10O3 protonic conductors were published in Ref. [205]. In the studied sensors, both the porous solid electrolyte and leaks between the two-linked solid electrolyte discs (Fig. 6.6) served as the diffusion barriers and the transport through the diffusion barriers obeyed the Knudsen mechanism. The limiting current of the sensor based on La0.95Sr0.05YO3 electrolyte was found to be proportional to the hydrogen concentration in nitrogen in a wide range, from 10% up to 98%. As can be seen from Fig. 6.6, in most of VI curves, the plateau exhibits a very slight deviation from horizontality, confirming that the electronic conductivity in the used electrolytes is negligible. Moreover, it was stated that the limiting currents for all gas compositions could be measured at the same applied voltage of about 700 mV (Fig. 6.6). As it is discussed earlier, the plateau length for the

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Solid Oxide-Based Electrochemical Devices

1 2 98% 80% 60% 40% 20% 10%

2.5

I, mA

2.0

3

1.5 1.0

1 2 3 U A

0.5 0.0 0

500 V, mV

1000

Figure 6.6 A schematic representation of the amperometric sensor (left): (1) protonconducting electrolyte, (2) sealant, and (3) electrode. VI dependencies of the amperometric sensor based on the La0.95Sr0.05YO3 electrolyte (right): line 1 gives the slope of the tangent to VI curves at zero point, line 2 gives the “plateau” slope, and line 3 is the horizontal one [205].

sensors based on protonic electrolytes is practically two times shorter than that observed in the sensors based on oxygen ion electrolytes, and, therefore, it is about 500 mV. The limiting current of the sensor based on CaZr0.90Sс0.10O3 electrolyte was also proportional to the hydrogen concentration; however, the VI curves were similar to the ones presented in Fig. 6.11A, which made impossible to perform measurements at a constant applied voltage. A hydrogen amperometric sensor based on La0.9Sr0.1YO32δ protonconducting electrolyte equipped with a metallic capillary was thoroughly investigated [199]. It was found that the developed sensor exhibits good operation reproducibility, clear response, and precision for the detection of trace hydrogen content (0.13.3 vol.%) in process gases at 500° C600°C. As it follows from Fig. 6.7, the VI relationship of the amperometric sensor are characterized by a limiting current region with a strictly horizontal section confirming the absence of electronic conductivity in the La0.9Sr0.1YO32δ ceramic in reducing atmosphere. The amperometric humidity sensor, comprising oxygen ion and proton conducting ceramic electrolytes, was recently fabricated and studied [206]. The sensor comprised (1) a plate made of YSZ electrolyte (green in Fig. 6.8), (2) another plate (yellow in Fig. 6.8) made of La0.9Sr0.1YO32δ, (LSY), and (3) a metallic capillary; both plates were equipped with platinum electrodes, and they were glued using a glass-sealant (Fig. 6.8). The cells were connected in series. By applying a positive potential to the

Sensors based on solid oxide electrolytes

(A)

(B)

0.04

0.3

x = 0.38

x = 3.3 x = 2.0 x = 1.25 x = 0.71 x = 0.38

0.25

x = 0.20

0.03

x = 0.10

I, mA

I, mA

197

0.02

0.2 0.15 0.1

0.01

0.05 0

0 0

0.5

1

0

1.5

0.5

U, V

1

1.5

2

2.5

U, V

Figure 6.7 The dependences of current as a function of applied voltage at 550°C for x vol.% H2 1 N2 gas mixture at low (A) and relatively high (B) hydrogen concentration [199].

1

5 V

3

2

A

4

Figure 6.8 A general view (left) and the schematic of the sensor comprised oxygenand proton-conducting electrolytes (right). (1) YSZ electrolyte, (2) LSY electrolyte, (3) capillary, (4) platinum electrodes, and (5) high-temperature glass sealant. Arrows are N2 1 H2O flow [206].

inner electrode of the YSZ cell a steam pumping out of the sensor chamber was obtained. At the corresponding applied voltage the steam concentration inside the chamber tends to zero and the limiting current appears. It was stated that the limiting current depends linearly on the steam concentration in N2 1 H2O atmosphere in the pH2O range from 0.004 to 0.078 atm, as shown in Fig. 6.9B. The amperometric sensor comprised oxygen ion (YSZ) and proton conducting (CaZr0.95Sc0.05O32δ) ceramic electrolytes for humidity analysis in oxidizing atmospheres was also studied [207]. The design of the sensor was similar with the one described earlier. [206] with exception of the capillary material; in this case a ceramic capillary was used in order to avoid the corrosion of the metallic capillary. It was stated that the VI curves had plateaus pH2O in the range from 0 to 0.11 atm (Fig. 6.10, left). However, the limiting currents’ dependence on the steam concentration does not intersect the origin.

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Solid Oxide-Based Electrochemical Devices

Figure 6.9 Voltampere characteristics of the sensor for different water vapor pressure values in nitrogen (A); the limiting current as a function of water vapor pressure (B) and all the data correspond to an operating temperature of 650°C [206].

Figure 6.10 Voltampere dependences of the sensor depending on different water vapor partial pressure (x between 0 and 0.11 atm) in air atmosphere at 750°C (left); limiting current as a function of water vapor partial pressure in wet air atmospheres at 750°C, with correction (right). Inset: the same dependence without correction [207].

The linear curve emerging from the origin can be obtained after the correction procedure (Fig. 6.10, right), which consists of the subtraction of the limiting current level recorded in dry atmosphere from those for wet conditions. In Ref. [201] the authors reported on unusual oxygen detection by means of a solid state amperometric sensor based on a CaZr0.9In0.1O32δ proton-conducting electrolyte. The sensor’s design was similar to that is shown in Fig. 6.13C. Pumping hydrogen in the form of protons inside the sensor’s chamber leads to the decrease of oxygen concentration in the chamber due to its interaction with protons according to the following reaction: 0:5O2 1 2H1 1 2e2 5 H2 O

(6.29)

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At definite voltage and current the oxygen concentration inside the chamber becomes zero. After that, free hydrogen can appear inside the chamber by the reaction 2H1 1 2e2 5 H2 :

(6.30)

However, before the appearance of free hydrogen in the chamber, the applied voltage must become higher by about 500 mV (Fig. 6.11A) as it was earlier discussed. Concentration dependences of the limiting current are close to the linear ones (Fig. 6.11B). As it follows from Fig. 6.11A, for a wide range of the oxygen concentrations, it is impossible to measure the limiting currents by applying a definite voltage; the higher the oxygen concentration, the higher voltage must be applied in order to reach the limiting current. This is not convenient for a practical use. There are two ways to overcome such inconvenience in the utilization of any amperometric sensors: (1) to lessen S/L parameter of the diffusion barrier and (2) to decrease the Ohmic resistance of sensor. The first way reaches the limiting current at lower applied voltage and the second one increases the inclination of the initial parts of the VI curve, thus shifting the beginning of the plateaus to the region of the lower applied voltages. The concept of multielectrode amperometric sensors for the analysis of multicomponent gas mixtures was first formulated by Somov [29], and later it was confirmed in series of works of Somov et al. [191,208213]. Multielectrode amperometric sensor contains several working electrodes that are separated from the gas phase by the same diffusion barrier. The first electrode must be sensitive to the electrode reaction of only one

Figure 6.11 The VI curves of the sensor for different oxygen concentrations in wet N2 1 O2 gas mixture at 550°C (A) and concentration dependences of the limiting current of the sensor at 550°C625°C (B) [201].

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Solid Oxide-Based Electrochemical Devices

of the gas components and insensitive to the electrode reactions of the rest components. The second electrode must be sensitive to the electrode reaction of only one of the rest gas components and insensitive to the electrode reactions of the other gas components, and so on. The sensitivity is determined by the electrode material and the applied potential. The analysis of a definite number of different gas components requires the same number of the working electrodes in the cell. The gas phase composition is changed from one electrode to the next. In this way a high selectivity of the individual electrodes is achieved. The simplest design of the double electrode tubular amperometric sensor is shown in Fig. 6.12. In some designs a single counter electrode was used (Fig. 6.12, left); the more reliable sensor design contained separated counter electrodes (Fig. 6.12, right). Typical tubes used by Somov et al. had a length of 34 cm and an outer diameter of 3 mm. Sensor for the simultaneous detection of NO and oxygen in N2 1 O2 1 NO mixture contains two platinum working electrodes [191]. By applying the corresponding voltage between the first pair of electrodes (working and counter), it is possible to reach a total oxygen pumping out from the sensor chamber; therefore the mixture N2 1 NO moves to the second working electrode. By applying the corresponding voltage of the same polarity between the second pair of electrodes, it is possible to totally decompose NO. The measured current in the first case corresponds to the oxygen concentration and in the second case to the nitrous oxide concentration. For each sensor the values of the applied voltage must be properly adjusted. The authors [191] reported that at the first electrode they obtained a selectivity to O2 of 1 and at the second electrode a selectivity to NO of 0.99, for mixtures N2 1 O2 1 NO with the oxygen concentration 1%5% and from 0 to 2600 ppm for NO. Sensor for the simultaneous detection of oxygen and combustibles used gold for the first working electrode and platinum for the second

U1 I1

U2

U1 I2

I1

Gas

Gas

Diffusion channel

Diffusion channel

U2 I2

Figure 6.12 Schematic illustration of gas-diffusion cell with two working electrodes arranged in series.

Sensors based on solid oxide electrolytes

201

one. Gold was chosen for the first working electrode because it does not catalyze reaction between oxygen and combustibles. As in previous case, the first working electrode serves for the pumping out of oxygen. By applying the corresponding voltage of the opposite polarity to the second pair of electrodes, it is possible to oxidize a combustible component and the measured current gives information on the combustible component concentration. In literature [210] the following mixtures were analyzed with the double electrode amperometric sensor: N2 1 O2 1 combustibles (H2, CO, CH4, C3H8, NH3). It was, in particular, stated that the sensor could reliably measure methane in concentration up to 10% in mixture with N2 1 2%O2. Despite the very impressive results obtained in the area of multielectrode sensors, we did not find any work concerned with the development of this type of sensors.

6.4.3 Coulometric sensors Vashook et al. [51] presented a general consideration of “oxygen solid electrolyte coulometry (OSEC).” There they describe the solid electrolytebased coulometric techniques that have wider application than for a gas sensing. Here we limit our consideration by an application of OSEC to the analysis of gases. The solid electrolyte coulometry technique is based on Faraday’s electrolysis law. The measuring procedure includes the charge calculation passed through the electrolyte by integration of the current by time with the following calculation of the produced (or disappeared) electrochemically active component. The design of coulometric sensors is similar to that of the amperometric sensors. However, in this case, the diffusion flux between the chamber and the analyzed atmosphere must be negligible during the measurement. An YSZ cell with platinum electrodes was periodically used as an oxygen sensor, for monitoring oxygen concentration in the reactor or as an oxygen pump to quantitatively titrate oxygen into the reactor or out of it. Change in the partial pressure of the electroactive gas component in the sensor chamber can be found supposing that the gas behaves as an ideal one Δp 5

qRT nFV

(6.31)

where q is the charge passed through the electrolyte, n is the number of electrons involved in the electrochemical reaction with one mole of an

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Solid Oxide-Based Electrochemical Devices

electroactive component, and V is the chamber volume. If the current is kept constant during Δt and p means the partial pressure of the electroactive component after pumping into the sensor chamber from zero to p, Eq. (6.30) can be transformed to Δp 5

RTIΔt nFV

(6.32)

There are two main kinds of coulometric sensors: purge and enrichment devices [203]. In the first kind the measurement is based on the electrochemical pumping out of the chamber of an electrically active component (from pout to zero) and in the second kind, the measurement is based on the reverse procedure (from zero to pout). Both kinds of the sensors work with two steps. In the first kind the gas in the chamber and the external atmosphere must be at the first step brought into equilibrium. It is possible to reach it by diffusion through a capillary, however, it requires much time because of the low diffusion rate through the capillary. Another way to reach equilibrium is to electrochemically pump an electroactive species into (out of ) the sensor chamber until EMF 5 0. At the second step, electrochemical pumping is applied until the electroactive component concentration in the chamber is zero. This moment is determined by the sharp increase of the applied voltage. If the current is constant, pout is proportional to Δt. pout 5

RTIΔt nFV

(6.33)

This step must be fast to avoid significant diffusion of the electroactive species from the external atmosphere into the chamber. However, the applied voltage must be of an appropriate value (not too high) to avoid the electrochemical reduction of the electrolyte. In the second kind of coulometric sensors the chamber is closed and gastight (similar to the one shown in Fig. 6.6; additional electrodes are placed on the top plate and the top plate serves as a potentiometric sensor). A current at the first step is applied to pump-out the electroactive gas until a sufficient vacuum inside the chamber (p°) is obtained. A potentiometric sensor can be used, with the external gas as reference point. The relative vacuum (p°/pin) is evaluated from the EMF value of the top sensor. At the second step the direction of the current is reversed and Δt is measured until EMF 5 0. The second step can be slow, that is, by choosing a small current, to improve the accuracy in the measurement of Δt.

Sensors based on solid oxide electrolytes

203

Coulometric sensors based on oxygen ion electrolytes were used for the control of oxygen activity [19], for trace gas analysis (oxygen, hydrogen, hydrocarbons) in the ppb range [214]. Coulometric sensors based on proton-conducting electrolytes were used for hydrogen analysis [136,215]. However, this type of sensors did not find a wide application, mainly due to complexity in their use and because of long time required for the measurements.

6.5 Combined sensors Combined sensors consist of at least two electrochemical cells, one of which operates as the pumping cell and the other one as the potentiometric cell. The first cell serves for the electrochemical pumping of the electrochemically active gas component into (or out of) the sensor chamber, thus creating a reference atmosphere inside the chamber. The second cell is used for measuring the EMF. In the first combined sensor, described by Haaland [23], the internal oxygen reference was generated by initial pumping out of all oxygen from the known internal volume of the sensor chamber and then quantitatively pumping oxygen into the chamber, until the oxygen’s partial pressure both inside and outside will be the same, when EMF is equal to zero. In this case the procedure of calculating the oxygen quantity is analogous to that used for coulometric sensors. The obtained information is used, combined with the ideal gas law, to calculate oxygen partial pressure inside the chamber, thus determining the same in the analyzed gas. Benammar et al. [216] developed and implemented a theory for the operation mode of a fully sealed miniature zirconia pump-gauge oxygen sensor, based upon the maintenance of the ratio of the mean internal and external oxygen partial pressures close to unity in order to minimize leakage effects. Results verified the theoretical predictions. The system operated well in the region of 1%10% oxygen concentration, displayed a response time to changes in oxygen’s partial pressure of less than 1.5 s. As it followed from the same authors [217], this method required a very complicated electrical measuring system, which included more than 70 units. A humidity sensor with an original design was developed by Katahira et al. [60]. The sensor consisted of two discs of the SCY protonic electrolyte glued with each other by the aid of a high-temperature glass sealant. As can be seen in Fig. 6.13A, a small hole was made in one disc, through which the inside and outside spaces of the sensor were connected. One cell was used for hydrogen pumping into the sensor’s chamber, and

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(A)

(B)

A

A

Pumping cell V

Sensing cell (C)

A

V Protonic electrolyte Glass sealant

Analyte flow H+-ion flow

Pt electrodes

Hydrogen flow

V

Figure 6.13 Principal scheme of the sensor with a hole in the electrolyte plate [60] (A). The schemes and the working principles of the sensor with a capillary in potentiometric (B) and amperometric (C) modes of operation [218].

0.25

0.25

Ilim, mA

0.2

= 0.997

0.2

0.15

0.15

0.1

0.1

0.05

E, V

R2

0.05 tgα = –3.306.10–2

0

0 0

2

4

6 8 x, vol.% H2

10

12

–8

–6

–4 –2 InpH2, atm

0

Figure 6.14 The calibration curves of the sensor working with N2 1 0.02H2O 1 xH2 mixtures at 500°C in the amperometric (left) and potentiometric (right) modes of operation [218].

the second cell served as the potentiometric cell. The authors obtained good EMF response against water vapor pressure over a wide range of pH2 O (4.6150 Torr) at 700°C. An original design of a hydrogen sensor based on two electrochemical Pt|BZCY|Pt cells (where BCZY 5 BaCe0.7Zr0.1Y0.2O32δ) has been developed by Kalyakin et al. [218]. The main feature of this sensor relies in its ability to operate in a potentiometric (Fig. 6.13B) as well as in an amperometric (Fig. 6.13C) mode. In the first mode of operation, hydrogen is pumping in the sensor chamber, thus creating a hydrogen reference atmosphere, and the EMF can be measured (Fig. 6.14, right). In the second mode the limiting current can be measured (Fig. 6.14, left). Theoretical and experimental dependences in both cases were in a good agreement.

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6.6 Concluding remarks As a rule, the designs of the mentioned sensors are simple and consist of electrochemical cells with single or separated gas chambers (spaces). This also simplifies the organization of electrical and gas lines. However, preference should be given to the sensors that can work under environmental conditions. In most of the investigated sensors, platinum electrodes were employed. The design and development of new electrodes seem to be not less important compared to electrolytes, mostly due to lower costs and the expanded temperature range of Pt-free sensors. It should be pointed out that there still are unsolved questions concerning (1) electrochemical activity, (2) thermal and chemical compatibility, and (3) thermodynamic and chemical stability of the electrode systems.

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CHAPTER 7

Solid-oxide metalair redox batteries Cuijuan Zhang1 and Kevin Huang2 1

School of Chemical Engineering and Technology, Tianjin University, Tianjin, P.R. China Department of Mechanical Engineering, University of South Carolina, Columbia, SC, United States

2

Contents 7.1 7.2 7.3 7.4

Introduction Concept of solid-oxide metalair redox battery Thermodynamics and kinetics of solid-oxide metalair redox battery Solid-oxide metalair redox battery operated on different chemistries 7.4.1 Fe-based chemistry 7.4.2 Other metals-based chemistry 7.5 Performance improvement of SOIARB 7.5.1 Improving performance of the reversible solid-oxide fuel cell 7.5.2 Improving performance of the energy storage unit 7.5.3 Proton-mediated redox activity of iron oxide 7.5.4 Remarks on the cycling degradation of solid-oxide metalair redox battery 7.6 Metalair batteries derived from solid-oxide metalair redox battery 7.7 Summary Acknowledgments References

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7.1 Introduction With ever-increasing energy demand and environmental protection consensus, clean and renewable energies such as solar and wind have been attracting increasing attention as alternatives to traditional fossil fuels. However, their intermittent nature makes the large-scale integration into the existing electrical grid a great challenge in terms of frequency stability and safety, which has already been stressed by the imbalance between generation and load (Fig. 7.1) [1]. In such context, developing energy storage technology is regarded as the viable solution to address the imbalance [1,2]. An energy storage system suitable for large-scale grid and Solid Oxide-Based Electrochemical Devices DOI: https://doi.org/10.1016/B978-0-12-818285-7.00007-1

© 2020 Elsevier Inc. All rights reserved.

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Figure 7.1 Schematic of balancing generation and demand via load leveling, a typical case of load shifting [1].

Figure 7.2 Classification of potential electrical storage for stationary applications [1].

renewable energy applications is preferred to be high cycling efficiency and rate capability, fast in response time, safe, scalable, and low lost [3]. Among all the energy storage technologies developed so far (Fig. 7.2) [1], the electrochemical batteries such as high-temperature NaS battery, redox flow battery, and alkaline metalair battery stand out [27]. However, the current performance of these batteries can only partially satisfy the requirements. For example, the NaS battery can charge/discharge energy at high rates with good cycle efficiency, but thermal management of molten Na/S and high fabrication cost hampers a

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widespread application [8]. The redox flow battery has been shown with excellent cycle efficiency, but it suffers from cation crossover, hydrogen evolution, high self-discharge rate, low energy density and toxicity [1]. In comparison, aqueous alkaline Znair and Feair batteries show a higher energy density, lower cost, and better environmental friendliness [3,6,7]. However, the CO2 management related to carbonization of alkaline electrolytes [7], electrode flooding [3], dendritic growth of Zn metal and hydrogen evolution during charging [7,9], and self-discharging and passive layer formation during charging for the Feair battery [3] must be properly addressed before they can be commercially deployed for large-scale grid and renewable storage. To enable these batteries for practical grid storage, significant breakthroughs in materials and engineering designs are needed. Alternatively, developing advanced batteries with a novel chemistry is another way to break the performance barrier.

7.2 Concept of solid-oxide metalair redox battery A solid-oxide metalair redox battery (SOMARB) has been demonstrated as a new type of all-solid-state battery suitable for grid and renewable energy storage. It was first patented by Westinghouse in 1996 [10], which consisted of bundles of cathode-supported solid-oxide fuel cell (SOFC) and Fe/FeO redox-couple bed. It worked by switching between electrolyzer and fuel cell mode and thus storing energy by redox reactions of Fe/FeO mediated by H2/H2O. This work has been paid rare attention due to the low power density inherited from the cathode-supported tubular SOFCs and system complexity. Huang group from the University of South Carolina reported a high-performance SOMARB based on anodesupported tubular SOFC in 2011 [11]. The working principle is illustrated in Fig. 7.3. This device is composed of a reversible SOFC (RSOFC) and an energy storage unit (ESU). Based on a dense oxide ion electrolyte and two porous air and fuel electrodes, the RSOFC works as an electrical charger and discharger while the ESU located inside the fuel-electrode chamber functions as an energy store via metal/metal-oxide redox couple mediated by the H2/H2O shuttle. During the discharge, metal (Me) is oxidized to metal oxide (MeOx), releasing H2 gas, which is electrochemically oxidized to H2O at the fuel-side of RSOFC by O22 diffused across the oxide ion-conducting electrolyte from the air electrode. The generated H2O diffuses back to ESU and reacts with the metal to form more H2 to sustain the electrochemical oxidation until all metals (or a

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Figure 7.3 Working principle of SOMARB consisting of RSOFC and ESU [12]. ESU, Energy storage unit; RSOFC, reversible solid-oxide fuel cell; SOMARB, solid-oxide metalair redox battery.

controlled portion) are depleted. The battery needs to be charged. During the charge, RSOFC operates as an electrolyzer with electricity as the energy input to split H2O into H2 at the fuel-side. The resultant H2 diffuses back to ESU and reduces MeOx to Me, producing more H2O to sustain the electrochemical reduction of H2O to yield H2 until all MeOx (or a controlled portion) are consumed. The battery is ready for next dischargecharge cycle. The overall reaction is the transformation between Me and MeOx through oxygen. Compared with other batteries, SOMARB has several distinctive advantages as follows: 1. It is an all-solid-state structure, which ensures high safety while making the system modular, compact, and scalable for grid storage application. 2. The energy of this device is determined by Me/MeOx in the ESU while the power is determined by the surface area of RSOFC. The decoupling of RSOFC and ESU components allows flexible energy and power designs for tailored applications. 3. Compared to the conventional H1/OH2/Li1/Na1-based batteries, SOMARB’s O22 chemistry delivers double electrons, thus rendering higher energy density. 4. The fuel electrode and ESU are physically separated, enabling a faster chargedischarge cycle without the concerns of structural damages as commonly encountered in conventional storage batteries, which is a valuable asset to rapidly harvest energy from renewable sources when the natural high energy flux such as solar and wind is available.

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7.3 Thermodynamics and kinetics of solid-oxide metalair redox battery In order to develop suitable ESU for SOMARB, the basic requirement is the operation window in terms of temperature, lifetime, fuel mixture, current density, galvanostatic, or potentiostatic operation [13]. Temperatures lower than 800°C are desirable to integrate the SOMARB with the present commercialized SOFC. Although the overall reaction is Me 1 x/2O22MeOx, according to the working mechanism of SOMARB (Fig. 7.1), the ΔG of forward and backward reaction of Me 1 H2O(g)2MeOx 1 H2(g) should be neither too positive nor too negative to ensure feasible chargedischarge cycles at the operating temperatures. To find suitable Me/MeOx couples for this reaction, ΔG of this reaction involving various elements in the periodical table is calculated, and the results are shown in Fig. 7.4. Fe, Sn, Cd, Mo, and W can be candidates for ESU materials. The oxygen partial pressure [p(O2)], in which the redox reactions of the ESU materials take place, is limited by the cell components and the possible composition of H2/H2O in the fuel electrode. The highest and lowest p(O2) is determined by the oxidation of Ni anode (10214 atm @800°C) and decomposition of zirconia electrolyte (10236 atm @800° C), respectively, for the traditional RSOFC based on Ni-cermet anode and zirconia electrolyte [13]. In the SOMARB system, p(O2) is

Figure 7.4 Thermodynamic calculation of Me/MeOx with HSC 5.0 software.

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Figure 7.5 (A) Equilibrium redox couples as a function of temperature, p(H2) and p (H2O). (B) Theoretical EN of Fe/FeOx redox couples as a function of temperature.

determined by p(H2) and p(H2O). As shown in Fig. 7.5A, the equilibrium redox couples are dependent on p(H2) and p(H2O) as well as temperature. According to the Gibbs’ phase rule, there should be a fixed Nernst potential (EN) at a given temperature in the presence of two discrete phases for an isobaric Me/MeOx binary system. The theoretical EN for Fe/FeOx is 0.97 V for Fe/FeO at 800°C, 1.067 and 1.083 V for Fe/Fe3O4 at 550°C and 500°C, respectively (Fig. 7.5B). Conversely, if the EMF is measurable, it can also be used to confirm the phase relationship (Fig. 7.6A) [14]. EN as a function of p(H2O) in a stagnant flow of N2/H2O and H2/H2O was measured at 800°C for Fe-based ESU. EN of 0.97 V was constant

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Figure 7.6 (A) EN recorded during the reduction of Fe2O3 by H2 at 800°C [14]. (B) EN as a function of H2O content in a closed-loop flow of N2/H2O and H2/H2O [11].

with p(H2O) in the case of N2/H2O, whereas it occurs only when p (H2O) . 35% in the case of H2/H2O (Fig. 7.6B), which corresponds to the equilibrium partial pressure of H2 and H2O [p(H2)/p(H2O) 5 65.1/ 34.9, that is, EN 5 0.97 V] for the reaction (Fe 1 H2O 5 FeO 1 H2) at 800°C [11]. Actually, EN is virtually controlled by the thermodynamic equilibrium between Me and MeOx with the actual mass ratio of Me: MeOx varying with the state of charge or discharge. It should be noted that for SOMARB, neither the conventional CeO2-based nor Bi2O3-based bilayer electrolytes can be used as an electrolyte, although they show high oxide ion conductivity, because the cell open-circuit voltage (OCV) is generally lower than the EN of redox couples in the ESU due to the electronic conduction. The leaked oxygen flux would gradually consume all the metals in the ESU, leading to serious cycling degradation.

7.4 Solid-oxide metalair redox battery operated on different chemistries 7.4.1 Fe-based chemistry Among the various metal candidates, iron is the most attractive due to its high energy density, low cost, and environmental friendliness. The proofof-concept of iron-based SOMARB (SOIARB) was demonstrated in labscale with an anode-supported tubular RSOFC [NiYSZ/YSZ/ La0.6Sr0.4Co0.2Fe0.8O32δCe0.8Sm0.2O22δ (LSCF-GDC)] and 85 mol.% Fe2O315 mol.% ZrO2 ESU at 800°C at a constant current density ( j) of 50 mA cm22 and with 10 min discharge and 10 min charge duration [11].

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Figure 7.7 (A) Charge and discharge characteristics of SOMARB at 800°C at j 5 50 mA cm22 with a closed-loop flow of 53.2% H2ON2. (B) Plot of energy capacity as a function of the number of charge and discharge cycles [11]. SOMARB, Solidoxide metalair redox battery.

The battery delivers stable cycling for at least 20 cycles with instantaneous response. The discharge-specific energy (DSE) is 348 Wh kg21-Fe over 20 cycles with a 38.5% Fe-utilization (UFe), and round-trip efficiency (RTE) is 91.5% (Fig. 7.7). The rate of rechargeability (50 mA cm22) is at least one-order of magnitude higher than that of Li-ion battery (B5 mA cm22) and similar to that of redox flow batteries. The results show that SOIARB can deliver high storage capacity, rate capacity, and RTE even at lower iron utilization. A number of 10,000 redox cycles of uninterrupted operation were demonstrated on short stack in Siemens (Fig. 7.8) [15]. The discharge capacity of first stack (SSt1) with Cr0.94Fe0.05Y0.01 positive electrode interconnector plates decreases from 1040 to 190 mAh over 10,090 cycles (discharge voltages: 890700 mV; charge voltage: 10451400 mV) mainly due to Cr evaporation. The second stack (SSt2) with gold positive electrode interconnector plate shows much slower degradation, which can be reduced by more than six times. The discharge capacity decreased from 1070 to 400 mAh over 10,166 cycles (discharge voltage: 890 mV, charge voltage: 1045 mV). Due to the strict requirement on sealing, that is, even slight leakage will result in serious degradation in cycling performance, a novel method employing H2 bypass and capillary tube was employed, which allows the available RSOFC test bench as well as the stack technology to be used and test Feair batteries without complicated modifications [16]. With a charge/discharge current of 150 mA cm22, charge capacities of 9.430.4 Ah per 80 cm2 active cell area and RTE of 84% can be achieved with Fe2O3/8YSZ, Fe2O3/CaO,

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Figure 7.8 Charge/discharge capacity of SOMARB of two short stacks at Siemens over B10,000 cycles [15]. SOMARB, Solid-oxide metalair redox battery.

and Fe2O3/ZrO2 ESU materials. After B130 cycles with Fe2O3/ZrO2 ESU material, B11% of the initial capacity was lost. Later investigation showed that the capacity and efficiency of SOIARB are strongly dependent on the degree of UFe, that is, higher (lower) charge and energy storage capacity but lower (higher) RTE can be produced at higher (lower) UFe [14,17,18]. Computational study with a high-fidelity multiphysics model revealed that the operating current density has the most pronounced effect on the H2 concentration distribution, EN, specific energy, and RTE [19]. The initial porosity in the ESU materials must be higher than 50% at high j to avoid significant diffusion limitation. High RTE can be achieved at the expense of useful capacity. Enhancement of the electrolysis electrokinetics of RSOFC and FeOx-reduction kinetics of ESU materials is the key to achieve high capacity with high efficiency. Heat balance analysis [20] indicated that the heat generated during the discharge cycle is more than what is needed for the charge cycle. The use of air as a working fluid to regulate the heat flow and heat balance within the battery is a practical engineering solution to maintain the desirable operating

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temperature and high energy efficiency for the battery system. Air utilization and inlet temperature are the two most important parameters that can be tailored to regulate the heat flow between cycles. When SOMARB works at a high jB150 mA cm22, the battery becomes thermally sustainable but at the expense of lower electrical cycle efficiency.

7.4.2 Other metals-based chemistry Besides iron, several other metals can be used as the ESU for SOMARB. The first one is W [21]. W and WO2 are the two equilibrium phases within the temperature range of interest based on the phase diagram. Compared with Fe/FeO, the W/WO2 redox couple shows higher EN and theoretical energy density (Wh L21). A SOMARB with W/WO2 as the ESU (commercial WO3 as precursor) was continuously cycled at j 5 100 mA cm22 for three consecutive 2 h cycle at 800°C (Fig. 7.9A), (A) 1.8 1.6

Cycle 1

1.4 E (V)

1.2

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Energy density (ave)=3.55 kWh L–1

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ηrt(ave)=53%

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Discharging specific charge (ave)=1117 Ah g−1-Mo

0.4

550ºC

0.2 0.0

0.0 0.6 1.2 0.0 0.6 1.2 0.0 0.6 1.2 0.0 0.6 1.2 0.0 0.6 1.2 0.0 0.6 1.2 0.0 0.6 1.2 0.0 0.6 1.2 0.0 0.6 1.2 0.0 0.6 1.2

Specific charge (Ah g−1-Mo)

Figure 7.9 (A) Battery voltage as a function of charge density for SOMARB based on Wair at j 5 100 mA cm22 at 800°C [21]. (B) Electrochemical performance of SOMARB based on Moair at j 5 10 mA cm22 at 550°C [22]. SOMARB, Solid-oxide metalair redox battery.

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producing a dischargecharge density of 5.36 kAh L21 and a discharge energy density of 3.55 kWh L21 with RTE of 53%, which are higher than the case of Fe/FeO under the same conditions, 4.45 kAh L21, 2.90 kWh L21, and 50%, respectively (here the energy densities are normalized to the metal-oxide volume that is equivalent to an oxygen flux needed to sustain the redox reaction). The achieved energy density represents only 67% of the theoretical value, which infers that a part of energy has been lost to RSOFC polarization reactions and ESU redox kinetics resistances. The second metal is Mo [22]. The equilibrium redox couple is Mo/ MoO2 redox couple according to the MoO phase diagram. The MoO2 chemistry has both thermodynamic and kinetic advantages over other metalO2 counterparts for SOMARB in terms of EN, maximum theoretical specific energy (Wh kg21) and maximum theoretical energy density (Wh L21). The SOMARB with Mo/MoO2 (commercial MoO3 as precursor) was cycled at j 5 10 mA cm22 for 10 cycles at 550°C (Fig. 7.9B), which produced an average specific charge of 1117 Ah kg21Mo, average DSE of 974 Wh kg21-Mo (normalized to the mass of actually consumed Mo by the oxygen flux for the redox reaction), and RTE of 61.7%, higher than the cases of Fe/Fe3O4 under the same conditions. Although both W- and Mo-based SOMARB show better performance than their Fe-based counterparts, their high cost, high vapor pressure at elevated temperatures [13] make their practical application great challenges. Iron is still preferable for SOMARB.

7.5 Performance improvement of SOIARB SOMARB is composed of RSOFC and ESU. Accordingly, the performance of SOMARB is strongly dependent on that of both RSOFC and ESU (Fig. 7.10). Although the early SOMARB was demonstrated at high operating temperatures (e.g., 800°C) [11], the intermediate- and lowtemperature SOMARB is preferred from the perspective of system cost, durability, and reliability. Two serious challenges are facing the lower temperature SOMARB, namely, high electrode polarization losses in RSOFC and sluggish kinetics of FeOx reduction to Fe. Computational modeling indicates that a battery with Fe/Fe3O4 ESU becomes virtually nonrechargeable if operated at j 5 15 mA cm22 and UFe 5 60% at 550°C [23,24]. Correspondingly, lots of efforts have been devoted to improving the performance of SOMARB through RSOFC and ESU optimization. In the following section, those efforts will be detailed.

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Figure 7.10 Strategies to enhance the performance of SOMARB through RSOFC and ESU optimization. ESU, Energy storage unit; RSOFC, reversible solid-oxide fuel cell; SOMARB, solid-oxide metalair redox battery.

7.5.1 Improving performance of the reversible solid-oxide fuel cell According to the support type, RSOFC can be divided into anode-, cathode-, and electrolyte-supported RSOFC. Due to the high electrode polarization, SOMARB with the cathode-supported RSOFC showed very low power density. Considering the serious of leakage issue, either from the electrolyte (such as pinholes) or from the sealing, the electrolytesupported configuration was adopted in the early development. Nevertheless, decreasing the electrolyte thickness and thus reducing the ohmic resistance is needed to achieve high-performance SOMARB. By reducing the thickness of LSGM electrolyte from 350 to 180 μm and infiltrating Ni(NO3)2Gd(NO3)3Ce(NO3)3 solution into the NiCe0.8Gd0.2O22δ (GDC) anode, the area-specific resistance of the RSOFC at 550°C decreased by 60% compared with the baseline battery. Accordingly, the performance of SOIARB with optimized RSOFC is remarkably improved combined with the optimized redox kinetics of ESU materials. The DSE and RTE are 1236 Wh kg21-Fe and 82.5%, respectively, which are only 892 Wh kg21-Fe and 40.5% for the baseline battery at j 5 10 mA cm22 and 10 cycles with 2 h discharge and 2 h charge at 550°C (Fig. 7.11) [25]. By employing anode-supported RSOFC assembled with (ZrO2)0.89(Sc2O3)0.1(CeO2)0.01 (SCSZ) electrolyte, Ni-SCSZ anode and

Figure 7.11 Performance of the (A, B) baseline and (C, D) optimized SOIARB at 550°C for 10 cycles with 2 h per cycle at j 5 10 mA cm22. (A, C) E versus charge capacity, (B, D) AC impedance spectra measured before and after battery cycling [25].

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Figure 7.12 Cycling performance of SOIARB at 550°C at j 5 10 mA cm22 with 10 min discharge and 10 min charge: (A) anode-supported RSFOC and (B) electrolytesupported RSOFC [27]. RSOFC, Reversible solid-oxide fuel cell.

La0.8Sr0.2MnO3-(Bi0.75Y0.25)0.93Ce0.07O1.51δ cathode, the maximum power density at 550°C was 154.5 mW cm22, B5 times of that of the electrolyte-supported RSOFC (33.5 mW cm22) [26]. Under the same testing conditions (10 mA cm22, 10 min discharge and 10 min charge) with 85 mol.% Fe2O315 mol.% ZrO2 ESU, SOIARB with anodesupported RSOFC shows stable cycling, delivering DSE of 1264.0 Wh kg21-Fe and RTE of 86.6% over 60 cycles versus 1056 Wh kg21-Fe and 59.8% for the electrolyte-supported SOIARB over 100 cycles (Fig. 7.12) [27]. The fast decay in the electrolyte-supported SOIARB is mainly originated from the worsening bonding between electrolyte and anode during cycling [27]. All those results show the remarkable influence of RSOFC on SOIARB performance. By optimization of the electrodes of anode-supported RSOFC, the performance of SOIARB is expected to be further enhanced. As aforementioned, CeO2- and Bi2O3-based materials cannot be used as electrolytes for SOIARB due to the electron conduction. ZrO2- and LaGaO3-based materials can be excellent candidate owing to their high oxide ion conductivity and high oxide ion transference number (B1). However, the easy reactivity of both electrolytes with traditional high-performance

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electrodes, for example, La12xSrxCo12yFeyO32δ, Ba12xSrxCo12yFeyO32δ, and La2NiO4 cathodes reacts with zirconia electrolyte to form insulating La2Zr2O7; Ni-cermet anode reacts with LaGaO3-based electrolyte, brings grant challenges to the optimization of RSOFC. In such context, infiltration can be a good choice after the coarsening issue at the elevated temperatures can be appropriately addressed [2830].

7.5.2 Improving performance of the energy storage unit Regarding to the Fe/FeOx ESU, the performance can be enhanced by improving the redox kinetics and increasing the sintering resistance. To improve the redox kinetics, at least two approaches can be adopted. The first is to prepare nanomaterials. Fe2O3 nanoparticles were prepared by infiltrating the Fe(NO3)3 aqueous solution into a commercial porous ZrO2 catalyst support (51 m2 g21). The performance of SOIARB was improved by 13% higher specific energy density and 48% higher RTE over the baseline battery. However, the fast thermal coarsening resulted in poor cycle stability over even five cycles (2 h per cycle) at 550°C [25]. Fe-based ESU nanomaterials with size B100 nm, prepared by the carbothermic reduction reaction (CRR) at 1000 °C, shows coreshell structure with the shell rich in iron carbide (Fig. 7.13B0 ). The resultant SOIARB exhibited outstanding cycling stability over 100 cycles at j 5 10 mA cm22 for 10 min discharge and 10 min charge at 550°C. The average DSE and RTE are 1188 Wh g21-Fe and 76.3%, respectively, which represents a 12.5% and 27.6% improvement over the baseline (Fe2O3ZrO2 prepared by coprecipitation) [32]. Temperatureprogrammed reduction (TPR) test revealed that the Fe-based materials derived from CRR show faster redox kinetics and higher stability, which probably due to its special microstructure. The coreshell structure was well maintained after cycling test. Further study revealed that Fe-based ESU from CRR (Fig. 7.13B and B0 ) can cycle at 500°C whereas that from urea-combustion cannot (Fig. 7.13A and A0 ). Considering that iron oxide with different crystal facets exposed showed distinctive hydrogen reduction activity [33,34], iron oxide with crystal planes of high-density Fe atoms exposed was prepared with Fe-based metalorganic framework (MOF), MIL-88B(Fe), as precursor. The resultant Fe2O3 shows octahedral shape with a particle size of 100200 nm (Fig. 7.13C0 ) and has a surface area of 7.7 m2 g21. Selected area electron diffraction patterns revealed that such octahedral-shape particles mainly crystallize in the (110) and other

Figure 7.13 (AC) Cycling performance of SOIARB at 500°C at j 5 10 mA cm22 with 10 min discharge and 10 min charge with Fe-based ESU prepared by different methods with different microstructures (A0 Cv). (A, A0 ) Fe2O3ZrO2 ESU prepared by urea-combustion; (B, B0 ) FeFeCxZrO2 ESU prepared by CRR; (C, C0 , Cv) Fe2O3 prepared by calcining FeMOF precursor [31]. CRR, Carbothermic reduction reaction; ESU, energy storage unit; MOF, metalorganic framework.

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planes (Fig. 7.13Cv). The density of Fe-atom is 10.1 atom nm22 for the (110) plane, the highest for Fe2O3 oxide. With such Fe2O3 as ESU material, SOIARB can cycle for more than 50 cycles at 10 mA cm22 at 500°C (Fig. 7.13C) [31], a significant improvement over the urea-combustionand CRR-synthesized Fe-based ESU materials. The second approach to improve the redox kinetics of iron oxide is to add catalysts. CeO2 [25] and metals such as Pd [12] have been proved to be effective. Dispersing fine particles of catalytic transition metals such as Co, Ni, Cu, and noble metal Pd into the Fe-based ESU material can significantly improve the reduction kinetics of Fe2O3. The TPR profiles (Fig. 7.14A) show a two-step reduction behavior of Fe2O3, a minor peak at lower temperatures B400°C (Fe2O3-Fe3O4) and a major peak at higher temperatures .450°C (Fe3O4-Fe) [35]. Since the original

Figure 7.14 (A) TPR profiles of baseline and metal-impregnated Fe2O3ZrO2 samples. Experimental conditions: 5% H2/N2, room temperature to 500°C, ramp rate 10° C min21, and 2 h holding at 500°C; (B) cycling performance of SOIARB at 500°C with metal-impregnated Fe2O3ZrO2 ESU at j 5 10 mA cm22 with 10 min discharge and 10 min charge. ESU, Energy storage unit; TPR, temperature-programmed reduction.

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amounts of Fe2O3 loaded for the TPR analysis were kept the same for all samples, the time spent to complete the reduction of Fe3O4-Fe can be used as a qualitative indicator of the reduction kinetics. Accordingly, the addition of those metals improves the reducibility of iron oxide, which increase in the order of Co , Cu , Ni  Pd. The enhanced reduction activity is not due to the surface area change but the catalytic effect of the impregnated metal species such as spillover effect [36]. In fact, the surface area and pore volume of impregnated samples show a slight decrease probably because of pore blocking. Consequently, SOIARB with catalysts impregnated Fe-based ESU shows significantly improved rechargeability. The addition of Co, Cu, and Ni has enabled 11, 18, and 21 cycles, respectively, whereas the catalyst-free battery cannot even perform one single cycle at j 5 10 mA cm22, 10 min discharge and 10 min charge, at 500°C. The best catalyst is apparently Pd, with which the battery exhibits .50 stable discharge/charge cycles (Fig. 7.14B) [12]. The average DSE is B1216.6 Wh kg21-Fe, and RTE is B77% over 50 cycles. Those results also suggest that TPR can be a powerful tool to help screen catalysts to improve the reduction kinetics of Fe2O3. Furthermore, SOIARB with Pd-catalyzed Fe2O3 ESU materials has the capability to perform at higher UFe up to 80% at the same j 5 10 mA cm22 but at the expense of RTE [12]. The DSE (calculated based on the total Femetal loaded) is 123.2, 606.4, and 960.3 Wh kg21-Fe at UFe of 10%, 50%, and 80%, respectively. The corresponding RTE is 72.0%, 68.0%, and 65.8%, respectively (Fig. 7.15). After cycling at UFe 5 50% for 25 cycles, the DSE and RTE are 593.4 Wh kg21-Fe and 62.9%, respectively. In addition, SOIARB can also work at higher C-rates, which is an advantage over NaS and alkaline metalair batteries. The Pd-catalyzed SOIARB can cycle at C/4.8 (11 mA cm22, 264.1 mA g21-Fe) and C/2.9 (18.5 mA cm22, 441.5 mA g21-Fe) at a moderate UFe 5 21% (Fig. 7.16). More than 50 cycles can be achieved with the highest charging voltage below 1.40 V at C/4.8, whereas only 10 cycles can be completed before the charging voltage rises to 2.0 V (the set cutoff voltage to avoid decomposition of zirconia electrolyte). The corresponding DSE and RTE are 228.9 Wh kg21-Fe and 67.8% at C/ 4.8 over 50 cycles, and 228.9 Wh kg21-Fe and 59.9% at C/3 over 10 cycles [12]. It indicates that the current density is more impactful than the cycle time on the rechargeability. Further microstructure analysis reveals that the slow kinetic rate of Fe3O4 reduction that is unable to match up with the electrolysis current, rather than the microstructural changes in RSOFC

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Figure 7.15 Performance of 500°C SOIARB with Pd-catalyzed Fe-based ESU at a fixed j 5 10 mA cm22 but different UFe. (A) Battery voltage profiles versus time, (B) discharge- and charge-specific energy and RTE versus UFe [12]. ESU, Energy storage unit; RTE, round-trip efficiency.

Figure 7.16 Performance of 500°C SOIARB with Pd-catalyzed ESU at different cycle current densities but the same UFe 5 21%. (A) Voltage profiles versus time at a cycle rate of C/4.8 and C/2.9. (B) Comparison of discharge and charge specific energy and RTE at different C-rates [12]. ESU, Energy storage unit; RTE, round-trip efficiency.

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electrode and ESU materials, is the root for the faster performance decay at higher rate. The reduction kinetics of iron oxide should be further improved. When pure Fe2O3 was used as ESU materials, oxide reduction and exposure to the elevated operating temperature of 800°C led to considerable sintering and coarsening of the metal particles. A dense outer layer of FeO/Fe3O4 was formed during the oxidation stage due to the outward diffusion of iron metal from the core through the iron oxide layer toward the gas/oxide interface. Ongoing sintering, especially during the reduction process, led to densification of the initially porous materials (Fig. 7.17A and B) [13,16,37]. Sintering results in decreased surface and thus a decreased reaction rate and a loss of capacity. Layer formation of either oxide or metal closes existing pores and slows down the gas transport into the center of the storage [3840]. Consequently, a deteriorated reaction rate and ultimately a loss of capacity follow. The addition of 30 vol.% 8YSZ as a scaffold decreases the tendency of the iron sintering during the reduction stage and thus smaller particle size. The external layer grown during the oxidation stage tends to be less dense (Fig. 7.17C and D) [37].

Figure 7.17 Samples of ESU materials based on (A, B) pure Fe2O3 and (C, D) Fe2O330 vol.% YSZ in the oxidized state after 10 half cycles at 800°C in Ar-2% H27%H2O (A, C) and in the reduced state after 11 half cycles at 800°C in Ar-2%H2 (B, D) [37]. ESU, Energy storage unit.

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Increasing the volume of 8YSZ to 70% leads to slower degradation at the expense of lower storage capacity. So the balance between sintering resistance and capacity must be taken into account. SOIARB with 30 vol.% 8YSZ modified Fe2O3 ESU shows stable cycling performance for more than 200 cycles at j 5 150 mA cm22 at 800°C. Similar effect was found with ZrO2 scaffold but not with Y2O3 probably due to the formation of YFeO3. 3 wt.% Cr2O3, 3 wt.% Cr2O3 1 3 wt.% Ce0.6Mn0.3Fe0.1O2, 3 wt.% Cr2O3 1 3 wt.% Ce0.8Sm0.2O2 (SDC), 3 wt.% Cr2O3 1 3 wt.% PrBaMn2O5 have also been shown to effectively improve the sintering resistance at 800°C [41]. The small Fe particle size was sustained by adding Cr2O3 1 PrBaMn2O5 after 10 redox cycles at 350°C. Furthermore, the activation energy for Fe oxidation was dramatically reduced from 62.0 kJ mol21 for pure Fe to only 9.5 kJ mol21 for Fe with Cr2O3 1 PrBaMn2O5. The redox stability, degree of oxidation of Fe powder, and the oxidation rate were significantly improved over 10 cycles (Fig. 7.18). SOIARB with Cr2O3 1 PrBaMn2O5-modified Fe ESU shows discharge capacity of 800 mAh g21-Fe at j 5 0.04 mA cm22 over 20 cycles at 350°C.

120

Fe2O3 + 3 wt.% Cr2O3 Fe2O3 + 3 wt.% Cr2O3 + 3 wt.% CMF Fe2O3 + 3 wt.% Cr2O3 + 3 wt.% SDC Fe2O3 + 3 wt.% Cr2O3 + 3 wt.% PBMO

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Figure 7.18 Oxidation degree of the Fe2O3 powder with various catalysts at 350°C. Various catalysts are 3 wt.% Cr2O3, 3 wt.% Cr2O3 1 3 wt.% Ce0.6Mn0.3Fe0.1O2, 3 wt.% Cr2O3 1 3 wt.% Ce0.8Sm0.2O2 (SDC), 3 wt.% Cr2O3 1 3 wt.% PrBaMn2O5 [41].

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In addition to adding sintering resistant scaffold, an alternative approach to suppress iron agglomeration and outward diffusion is by using a double or triple oxide containing iron and a second metal, which forms and remains stable under the oxidizing conditions present during cycling and decomposes during reduction into metallic iron and the second metal oxide. It can be expressed as [13] Fex By Oz -reduction-Fe 1 By Ow -oxidation-Fex By Oz After examining a series of metal oxide combinations, the only oxide with long-term stability that can be easily oxidized and reduced within the envisaged operational window is the combination of iron oxide and calcium oxide [13]. CaFe3O5 can be a promising ESU material owing to the good storage capacity and the good resistance against degradation [40]. It can be reduced into Fe and CaO via Ca2Fe2O5 that prevents metallic iron from forming large agglomerates. With increasing reduction time, more Fe is released from the scaffold leaving CaO. The whole structure gets more porous. Both the large porosity and the good scaffold of CaO/Ca2Fe2O5 prevent a layer formation on top of the storage material. Upon reoxidation, iron oxidizes to Fe3O4 accompanied by taking up of Ca21 ions from the scaffold quickly so that Ca2Fe2O5 destabilizes and CaFe3O5 forms. During oxidation, the porosity decreases (Fig. 7.19). As long as this porosity allows for effective diffusive gas transport, an outer layer formation can be suppressed and repeated redox cycles are possible without further degradation. However, stack test shows that SOIARB with Fe2O3/CaO as ESU materials gave lower charge per layer (9.4 vs 12.6 and 30.4 Ah), energy per layer (8.5 vs 10.8 and 25.8 Wh), and iron utilization (64% vs 93% and 84%) compared with its Fe2O3/YSZ and Fe2O3/ZrO2 counterpart at 800°C, although the former shows higher porosity. UFe is low because B30% of the iron was still in the form of Ca2Fe2O5 and was not fully reduced after charging [16].

7.5.3 Proton-mediated redox activity of iron oxide Considering the involvement of hydrogen and water vapor in SOIARB, which are also necessary for high-temperature proton conduction in BaCeO3- and BaZrO3-based materials, the effect of proton conductors BaZr0.8Y0.2O32δ (BZY20) and BaCe0.7Zr0.1Y0.1Yb0.1O32δ (BCZYYb) as support for iron oxide was investigated [42]. The ESU was prepared by infiltrating Fe(NO3)3 aqueous solution into BZY20 and BCZYYb as well

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Figure 7.19 Sketch of a sintered porous body initially consisting of Fe2O3 and CaFe2O4 after sintering (A) and changes of the microstructure and the phase composition after repeated redox cycles in reduced state (B) and in oxidized state (C) [40].

as ZrO2 supports. SOIARB with ZrO2 support is nonrechargeable at j 5 55.1 mA cm22 at UFe 5 5% at 550°C. In sharp contrast, its counterparts based on BZY20 and BCZYYb supports cycled stably within 50 cycles (Fig. 7.20A). Furthermore, BCZYYb, with the highest proton conductivity, can achieve RTE of 73% (at C/5) even at UFe 5 100%. The long-term cycle stability testing further shows that the battery with BCZYYb as support can cycle at C/4 and UFe 5 25% for more than 200 cycles, achieving DSE of 282264 Wh kg21-Fe and RTE of 50%63% at 550°C. TPR results show that Fe2O3/BCZYYb has lower reduction temperature (578°C vs 636°C) and lower reduction activation energy (129.6 vs 114.2 kJ mol21) and thus faster reduction kinetics compared with Fe2O3/ZrO2. A hypothesis of a parallel pathway that mediates the oxidation of Fe and reduction of FeOx through active proton species in the proton-conducting support was proposed (Fig. 7.20B). The

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Figure 7.20 (A) SOIARB voltage profiles versus time with baseline ZrO2 as support and proton-conducting BZY20 and BCZYYb as support at j 5 55.1 mA cm22 and UFe 5 5% at 550°C. (B) Schematic illustrating the proton-mediated Fe redox reaction during a charge/discharge cycle [42].

produced, fast-moving, active proton defect is transported through BCZYYb bulk to its interface with Fe, where it is reduced by Fe to H2. The proton-conducting ceramic provides an additional pathway to produce H2 during a discharge process. A reverse process is expected for the charge cycle. The use of proton-conducting ceramic provides another strategy to enhance the redox kinetics of iron oxide ESU materials for SOIARB.

7.5.4 Remarks on the cycling degradation of solid-oxide metalair redox battery Although many advantages are inherited in the SOMARB technology, the cycling stability is still a great challenge especially at high temperature and high current density. The degradation of SOMARB is closely associated

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Figure 7.21 Probable causes for the performance degradation of SOMARB during cycling. SOMARB, Solid-oxide metalair redox battery.

with that of both RSOFC and ESU components (Fig. 7.21). For RSOFC, posttest analysis revealed that the dominate increase in polarization resistance comes from the anode, which is probably originated from Ni coarsening and decreased electrolyteanode bonding [4348]. Further improvement in low-temperature RSOFC will boost the performance of SOMARB. For ESU materials the most serious degradation comes from the metal coarsening. For example, the specific surface area reduced from 8.9 m2 g21 for fresh reduced Pd-impregnated Fe2O3ZrO2 to only 1.9 after 50 cycles at C/4.8 and UFe 5 21% at 500°C [12]. Correspondingly, improving the sintering resistance of ESU materials can be a focus for the future development.

7.6 Metalair batteries derived from solid-oxide metalair redox battery A battery similar but strictly not the same with SOMARB was also proposed. This battery can be assumed as an oxygen concentration cell, where oxygen permeates through the oxide ion-conducting electrolyte during discharge, that is, oxygen shuttle system [4952]. p(O2) at the fuel side can be maintained at a low value by oxidation of metals with oxygen permeated from the airside (Fig. 7.22). These metals can be Si, Fe, Mg, Li, Sn, and Zn. The electrodes for oxidation of oxide ion do not touch directly with the active materials, which can suppress the degradation of the electrode during redox cycles. Different from SOMARB, this derived battery generally cannot charge due to the difficulty in reduction of metal

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Ar Out In

Air electrode : O2 + 4e– → 2O2–

Valve Sealant

Fuel electrode : 2O2 → O2 + 4e– Galvanostat Pt line

Me + x/2 O2 → MeOx (Me = Metal) CSZ electrolyte

Tubular electrolyte (CSZ)

Low PO2

Alumina tube Pt electrode

Me

MeOx

Me: Li, Mg, Fe, Zn, Sn Metal

High PO2

Pt Pt anode Cathode O2 O2 O2– Pt

Pt 1 mm

Figure 7.22 Schematic of the oxygen shuttle battery concept [52].

oxides investigated [52]. In addition, electron conduction appears in the oxide ion-conducting electrolyte (Ca-stabilized zirconia, CSZ) in the extremely low p(O2) (#10235 atm). The oxide ion transport number is only B0.9 at 800°C [52]. Such Siair battery shows redox behavior, Si can be oxidized into SiO (major) and SiO2 (minor) during discharge; the latters can be reduced into Si during discharge, which is supported by the OCV measurement [50]. The battery with current of 0.5 mA gave an average energy density of B400 Wh kg21-Si and RTE of B45% over 20 cycles at 800°C (Fig. 7.23). The low efficiency is probably originated from the electron conduction in CSZ electrolyte, gas leaking, and slow redox kinetics of Si/ SiOx. In comparison, Mg-, Li-, and Zn-based air battery cannot be charged under the investigated conditions. The discharge capacity was 1154 mAh g21-Mg and 2179 mAh g21-Li at J 5 0.077 mA cm22 at 800°C for Mgair and Liair batteries, respectively [49,51]. A serious problem with this battery is the sintering of metal/metal oxide after discharge due to the high operating temperatures [4952]. Adding sintering-resistance materials can be an alternative. Another metalair battery, with Fe or Fe-based cermet instead of Ni or Ni-based cermet as anode, was developed. In this system, Ni electrode and the H2/H2O redox processes are avoided, which operates in dry conditions and hydrogen is just used for the first in situ chemical activation of the active material. During discharge, metallic Fe is oxidized to FeOx by

Solid-oxide metalair redox batteries

243

Figure 7.23 Chargedischarge properties of a Siair battery with Pt/CSZ/Pt cell: (A) chargedischarge curves and (B) energy density and RTE [50]. CSZ, Ca-stabilized zirconia; RTE, round-trip efficiency.

O22 from the molecular oxygen reduction at the cathode. The charge process is the opposite (Fig. 7.24) [53,54]. Similar to SOMARB, CeO2based electrolyte cannot be used for this battery; otherwise, it will lead to rapid spontaneous discharge [54]. The cycling performance of the battery with La0.8Sr0.2Ga0.8Mg0.2O3-δ (LSGM) electrolyte shows specific capacity of 566 mAh g21-Fe, specific

244

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Figure 7.24 Configuration and working principle of the solid-state Feair battery [53].

energy of 512 mWh g21-Fe, voltage efficiency of 68%, faradaic efficiency of 44% at j 5 1.4 A g21-Fe, and 650°C with high and low cutoff voltages of 2 and 0.25 V, respectively, and time limit of 60 min (Fig. 7.25) [53]. Shortening the time limit (i.e., reducing the iron utilization) to 25 min slightly reduces the specific capacity (547 mAh g21-Fe), specific energy (489 mWh g21-Fe) but increases the voltage efficiency (72%) and faradaic efficiency (66%). The average specific capacity and energy are 508 mAh g21-Fe and 458 mWh g21-Fe over 100 cycles at 650°C with RTE of B53.7%. The performance declines with decreasing temperatures. Nevertheless, the formation of an iron oxide network during the discharge process causes increased polarization resistance that hampers the battery performance. Although the above two metalair batteries have some similarities with SOMARB, they are quite different in terms of feasible redox cycles and decouple energy and power configuration. Consequently, they show either poor chargeability or faster cycling decay. The performance of SOMARB and comparison with other high- and low-temperature metalair batteries can be found in Table 7.1.

7.7 Summary Characterized by high energy density, high rate capability, and high safety, SOMARB is a promising technology for large-scale energy storage. Many

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Figure 7.25 (A) Specific capacity and energy, (B) faradaic efficiency and voltage efficiency as a function of cycle number at 650°C [53].

metal/metal oxide couples can be used as ESU such as Fe/FeO, Fe/ Fe3O4, Mo/MoO2, W/WO2. Although the first SOMARB was demonstrated at high operating temperatures (800°C), developing intermediateand low-temperature SOMARB is more favored from the viewpoint of cost, durability, and reliability. However, the lower temperature SOMARB is facing challenges such as high electrode polarization resistance in RSOFC and sluggish redox kinetics of ESU. The approaches to improve the performance of RSOFC such as using thin film electrolyte, developing novel high-performance electrode materials, and optimizing

Table 7.1 Performance of solid-oxide metalair redox battery and comparison with other metalair batteries. Temperature (°C)

ESU

j (mA cm22)

Charge/ discharge duration (min)

Cycle number

DSE (Wh kg21-metal)

RTE (%)

Reference

500

MOF-derived Fe2O3 Pd-impregnated Fe2O3ZrO2

550

Fe2O3ZrO2 FeZrO2 Fe2O3ZrO2 Fe2O3ZrO2 Pd-impregnated Fe2O3ZrO2 Fe2O3ZrO2 Fe2O3Cr2O3PrBaMn2O5 Fe2O3 MoO2 WO2 Fe-GDC

10 60 36 10 10 159 60 30 10 10 10 10 10

50 30 14 50 500 25 50 10 100 100 100 100 24

35.6a 226.5a 548.8a 38.1a/1216.6b 36.7a/1174.4b 593.4a/1149.2b 238.6a/1153.1b 228.9a/1102.6b 1056.0b 1188.0b 1264.0b 760b 443.8a

71.2 65.4 58.1 76.7 68.5 62.9 67.8 59.9 59.8 76.3 86.6 55.3 81.4

[31]

500

10 13.8 18.5 10.0 10.0 10.0 11 18.5 10 10 10 50 40 50 0.1 5 10 100 1.4 A g21

10

20 50 30 10 3 100 25 10 20 100 297 20

348a B550a 450a 974b 2.90 kWh L21-Wb 458 428 217 400 773 764.5 453

91.5 B50 B82 61.7 61.7 53.7 54.6 51.4 45

[11] [41] [46] [22] [21] [53]

550 650 700 800 350 500 550 800 650 600 550 800 RT RT RT

Si Znair Znair Feair

0.025 A g21 10 10

10 120

DSE, Discharge-specific energy; ESU, energy storage unit; MOF, metalorganic framework; RTE, round-trip efficiency. a The mass of metal is calculated based on the total metal loaded. b The mass of metal is calculated based on the actually consumed by the oxygen flux provided by RSOFC according to Faraday’s law.

57 70

[12]

[32]

[17]

[50] [55] [56] [57]

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microstructure are first discussed. The strategies to enhance the performance of ESU are then discussed in detail. They include improving the redox kinetics via nanostructuring, exposing high-density Fe-atom planes, introducing catalysts, and employing proton-conducting solid oxide as support for ESU, and alleviating the sintering issue during cycling via introducing sintering resistant scaffold such as ZrO2 and YSZ. The probable reasons for the energy loss and cycling degradation are discussed. Finally, the performance comparison with other high- and lowtemperature metalair batteries is carried out. Compared with other rechargeable batteries, SOMARB is capable of achieving high specific energy and power without safety concerns. Higher operating C-rate, inherent safety features, and low maintenance suggest SOMARB is an excellent candidate for stationary grid and renewable energy storage. Future power enhancement in RSOFC, redox activity, and sintering resistance improvement in ESU will further extend the battery’s cycle life at high C-rate and metal utilization. With concurrent advances in SOFC stack and system design, SOMARB is expected to play an important role in future grid and renewable energy storage.

Acknowledgments This work is kindly supported by the Natural Science Foundation of China (51702230).

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CHAPTER 8

Solid oxide fuel cell systems Giovanni Brunaccini

Consiglio Nazionale delle Ricerche - Istituto di Tecnologie Avanzate per l’Eenergia “Nicola Giordano”, Messina, Italy

Contents 8.1 Introduction to solid oxide fuel cell systems (benefits and limits) 8.1.1 Short energy scenario background 8.2 Solid oxide fuel cell systems current applications 8.2.1 Power generation 8.2.2 Automotive applications: auxiliary power units and propulsion 8.2.3 Power backup systems 8.2.4 Hybrid systems exploiting biogas/biofuel production 8.2.5 Combined heat (cooling) and power generation 8.2.6 Demonstration for critical environment applications 8.3 Basic system architecture 8.3.1 Ancillary devices 8.3.2 Blowers pumps reformer heat exchangers afterburner power converter(s) 8.3.3 Power conditioning devices impacts 8.3.4 Control algorithms for automatic system optimization 8.4 Numerical models 8.4.1 Simulations of specific behavior 8.5 Solid oxide fuel cell system costs References

251 253 255 255 258 259 260 263 265 266 266 267 271 273 276 280 285 288

8.1 Introduction to solid oxide fuel cell systems (benefits and limits) Based on electrochemical reactions (reduction/oxidation), solid oxide fuel cell (FC) (SOFC) systems are capable of converting the primary energy of fuels into electrical energy without fuel combustion. This feature makes such systems (like other FCs technologies) able to overcome the Carnot cycle efficiency limitation so that, generally speaking, the main strongpoint that stimulated several research activities is the potentially high fuel to power conversion efficiency. Solid Oxide-Based Electrochemical Devices DOI: https://doi.org/10.1016/B978-0-12-818285-7.00008-3

© 2020 Elsevier Inc. All rights reserved.

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Hence, while environmental concerns are growing and primary energy consumption reduction is a pushing necessity of every user/application category (from small residential, to commercial, industrial, automotive, dedicated energy production, and so on), their high-efficiency generation becomes an outstanding and relevant feature with respect to traditional generator based on fossil fuels combustion. Besides this, among the currently available FC technologies, SOFCs show a number of appreciable properties: • absence of noble metal as catalysts: so that the cost of raw materials for their building is low; • capability of being fed with different fuels: besides hydrogen, even low-weight hydrocarbons and their mixtures (even coming from biomass process) can be exploited (through direct internal oxidation or through appropriate reforming process) to generate power with highconversion efficiency; and • operation at high temperature: so that the waste heat has sufficient temperature to run a bottoming cycle (e.g., gas turbine) or to enable cogeneration (combined heat and power, or CHP, generation) to satisfy electrical and thermal load at once (with about 1:1 ratio, even applying a modulation to this proportion) and increase the overall system efficiency. In the face of such desirable features, SOFCs show some nonnegligible disadvantage: • The limited capability of withstanding with load transient: mostly due to the high operational temperature, the relevant variation of heat generation while power generation varies determines temperature variations and gradients, so that both electrolyte conductivity impact and mechanical stress on the cell materials affects both generation performance and cells lifetime. • Long start-up time with respect to lower operating temperature devices, to make the electrolyte reach sufficient conductivity; moreover, the start-up requires external components (as a gas burner or an electrical heater, together with appropriate control system) to reach operational conditions. • High manufacturing costs: mainly due to the necessity of dealing with thin ceramics, the manufacturing waste is expensive and limits the current series/mass production. However, to discuss the potential and actual contributions of SOFC systems to today’s world, it would be useful to analyze their collocation in

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253

the energy sector, both with regards to the energy contest [centralized generation, distributed generation (DG), renewable source management] and the other energy conversion/production systems.

8.1.1 Short energy scenario background According to the World Energy Outlook (WEO) report by the International Energy Agency [1], the worldwide energy demand will have a growing trend in the year 2040 perspective. The current power generation systems, implementing a centralized production mainly from fossil fuels (coal and natural gas above all as per the today WEO statistics in [2]), have risks of becoming insufficient over time, in terms of both primary energy availability and infrastructure capacity. This, besides the environmental matters, would lead to a rapid energy source shortage. Different causes with various natures are contributing to such global energy demand growth. Examples of these causes are • the worldwide population increment (impacting even on the natural resources consumption); • the development of new high-energy consumption services (highspeed transmission, high-speed transportation); • social and economic improvement in (previously) underdeveloped countries: this implies more energy (even with high pollution impacts) for services, transportation, manufacturing (goods production), and so on; • new residential, commercial, and industrial building constructions (and therefore their energivourous impact); and • the global average temperature increment (so that more cooling energy is required). To satisfy such growing energy demand without wasting primary energy, low environmental impact (sustainable) and high-efficiency energy conversion systems (from primary sources to the user) are necessary. Besides this, renewable energy sources (RES), which are of course environment friendly, are expected to have higher diffusion and expansion with respect to other sources such as coal, gas, and nuclear. However, their unpredictable behavior over time makes them not capable of matching the power needs of loads (i.e., users/customers). Thus their unpredictable power injection into the grid may lead to power network instability due to both possible abrupt generation and consumption gap over time. Moreover, RES penetration in the power

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network determine new issues even considering the perspective of grid lines overload (mostly in the short-term perspective) due to the time shift between actual production and load dynamics (in different observation time windows, from seconds to hours), so that control mechanisms must be introduced to implement regulatory actions. On the other hand, FC-based systems operate as controlled generators, so that the power generation may well be adapted to the served load and, in parallel, to support the electric grid regulation. Indeed, also for FCs, the generation dynamics have critical consequence on the system production modulation. This is due to two main issues: • the energy conversion efficiency (at least at system level) has an optimal working point (depending on the system design phase), so that power modulation impacts on the fuel consumption, electric-tothermal power ratio, and so on; • especially for high-temperature FCs (e.g., SOFC), the power modulation dynamics is limited and slow; moreover, even the lifetime of the FC stack is reduced with respect to the steady state (i.e., constant power) working point; therefore this impacts on generation costs. Indeed, to overcome these limitations and support the power network, as well as automotive applications, the FC system studies are often addressed to the analysis, development and prototyping of hybrid configurations, making use (in the most of cases) of batteries or gas turbines. Indeed, in the last few years, the interest in FC systems has been affected by the parallel development and performance enhancement of electrochemical storage devices at commercial level, so that some systems have been mainly addressed to niche market applications such as small power applications (100 kW to 1 MW), especially in areas where lowpolluting emission is a fundamental feature as presented by Popel’ et al. [3] in 2018. European projects promote the development of SOFC systems. For instance, in the 10 60 kW (the so-called Mini FC-CHP) power range, the ComSos project is addressed, as described by their website [4], to the demonstration for commercialization of CHP configurations based on SOFC technology, as summarized in [5]. In that project, three manufacturers are committed to develop more than 20 systems to end-user facilities for a total of 450 kW. Another example of dedicated funding from institutions to foster the interest in SOFC systems is given by the Connecticut Department of Energy & Environmental Protection that has recently claimed projects for

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more than 250 MW in their Clean Energy policy explained in Ref. [6]. Within these, 52 MW are dedicated to four FC installations, one of which is a 10 MW SOFC plant in Colchester in the next few years, to install energy production plants in urban areas close to the served loads.

8.2 Solid oxide fuel cell systems current applications Low environmental impact and high-energy conversion efficiency make SOFC technology a promising candidate to replace traditional internal combustion engines and generators in different applications nowadays. Among the currently available energy-conversion devices, as in the work by Ellamla et al. [7], SOFCs showed efficiency higher than 60% for electrical power and over 90%, including thermal power, low noise emissions, no moving parts in the generation devices (ancillary hardware may require fans and/or water pump, instead). From the environmental impact point of view, SOFC exhausts have very small amounts (especially in steady state operation) of polluting and greenhouse impacting emissions (CO2, CO, nitrogen, and sulfur oxides), so that even applications in urban areas have been proposed and installed. Moreover, their energy density and specific energy (i.e., per mass and volume unit, respectively) suggest their exploitation both in stationary and in automotive/aircraft sectors. A nonsecondary aspect is the low price of the used materials. Catalysts for high temperature FCs (such as nickel above all) have noticeably lower price than noble metals used in low temperature FCs, effectiveness of which is determined by the enhancing effect of temperature to the reactions kinetics. This is because electrochemical redox reactions are fostered by temperature that reduces the activation energy, for instance, in methane and hydrogen oxidation at the anodic compartment.

8.2.1 Power generation Concerning the CO2 emission reductions and fossil fuel independence for power generation, the paper by Tan et al. [8] analyze the case of SOFC system used to produce energy for building supply. In particular, in the Chinese scenario, they remarked the valuable industrialization and urbanization processes that make China, one of the most CO2 emitters and energy consumers. For this reason, starting from the newly adopted environmental policies in 2016 to replace traditional centralized generation with cleaner fuels and more effective plants, SOFC are seen as an ideal

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solution to combine domestic hot water production, space heating, and power generation both in residential and in public buildings. For this reason, such power generators can be addressed as the socalled DG, that is, the utilization of small size (1 kW scale up to 100 kW scale) production systems that directly serve a local (main) load and that are connected to the public grid. In such a situation, depending on system design, market conditions (i.e., dedicated contracts), power availability, and other boundary constraints and incentives, the generated energy may be injected into the grid to provide energy services while reducing the energy loss over power line thanks to the production close to the consumer of the most part of the generated power. From this point of view, the grid can be assimilated to a sort of energy storage to compensate for the discrepancy between the actual load and the internal power production, instead of the main energy source. The DG systems are mainly based on RES such as photovoltaic (PV) and wind turbine (WT) plants. However, mainly due to their unpredictable behavior over time, such plants, especially after large scale spread, have risks of becoming an instable grid source, due to the injection of (unexpected) power from the users toward the centralized production plants. Therefore to smoothen such production instability, an adjustable generator is needed. FC systems may support this function, and thanks to their high efficiency (up to 50% 60% in electrical generation, up to 70% 80%, including the thermal power production, if required by the prosumer load) may be well integrated in a low-polluting emission active-user plant. Moreover, in such a grid-tie configuration, thanks to their compactness and generation stability, recently SOFCs have been proposed as an apparatus to support the internal generation of microgrids able to exchange programmable energy amounts to optimize the power distribution, reduce the energy loss due to long “production-to-consumption” distance, and at same time procrastinate investments on power line enhancement to support growing aggregate energy demand. While increasing the design power, on the other hand, SOFC systems are able to support even MW scale generation. In several research studies, they are combined (thanks to the gas exhaust high temperature) with gas or steam turbines run as bottoming cycles to improve overall production (conversion) efficiency. A novel target function, which simplifies the load curves predictions to the transmission line operator, for such plants is the profilation of the

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generation/consumption over time (usually with daily term) to allow the big power producers to optimize the control (switch on/off, working point variation with sufficient time with respect to the actual needs) of their production plants. Indeed, even depending on the installation site, the FC technology selection must take into account both electrical issues (e.g., grid connection and desired system dynamics), fuel availability (whether a gas line reaches the installation site or a fuel tank is required), installation space, load (electrical and thermal) demand. For instance, dealing with electrical load dynamics, since SOFC systems have slow modulation capability (with respect to the electrical load transients), their use is commonly studied in combination with faster response devices such as electrochemical batteries or turbines (both gas and steam-fed). To conclude, examples of SOFC-based systems at different power generation scale are reported. In residential applications field, compactness and low cost are fundamental to promote the SOFC technology diffusion. For example, during the FC Expo 2015 in Japan, FCO Power showed a 700 W SOFC system claiming the two earlier-mentioned requested features (5 kW dm23 and 415/kW in 10-year projections); in particular, each cell component was laminated (down to 0.4 mm for the whole cell) before the (sub-)stack sintering and assembling (explained in Ref. [9]). This lamination process is expected to reduce the required raw materials and, therefore, the overall cost. Moreover, the absence of a single-cell structure allows one to avoid cell support for mechanical robustness and to simplify the cooling thanks to more uniform temperature distribution over the thin layers-based architecture. Further, the compactness (comparable to a wall mount heater) lets the system be adapted to both new apartment and to retrofitting. The ultimate commercialization is expected to be fulfilled in summer 2020. At higher design power value scale, a 200 kW SOFC system installation, whose details are reported in Ref. [10], was recently performed within the IKEA store in San Diego. This is the fourth SOFC system installed for IKEA in California by Bloom Energy (and one more is planned to be installed, to reach 1.5 MW in total), as reported by Yirka [11] while reporting the pathway for the energy independence by 2020. In their overall project, even solar (252 kW, PV rooftop array) and wind source are included as sources, and charging stations for electric vehicles.

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The FC plant is fed with biogas and requires just a little more space than a usual backup genset. This is not the only recent installation by Bloom in the latest years. Among these, two examples (in their press release [12]) are given by a total of 3.5 MW energy servers have been installed this year in Santa Clara (California, at the Agilent headquarter) aiming to reduce the carbon footprint (of about 4000 t year21), water utilization, and greenhouse gas (GHG) emissions in those facilities. Second, another installation was done (750 kW SOFC, for Morgan Stanley headquarter) at the end of 2016, to demonstrate the feasibility of installation even in urban areas to limit the pollution impact through onsite energy production.

8.2.2 Automotive applications: auxiliary power units and propulsion The earlier-mentioned compactness/energy density makes the SOFC systems proper for onboard generation. In particular, due to their low capability of rapid power modulation, they can be used in the case of overnight staying with the main engine (internal combustion engine,ICE) turned off or for electricity generation in emergency. Moreover, experimental applications include the battery recharge and internal (auxiliary) services for ships and trucks, as well as the electric load of any vehicle, with the additional benefit of reducing fuel consumption thanks to the conversion efficiency higher than ICE. Second, the ability of being fed with different fuels (once purified from contaminants, such as sulfur compounds) with only partial reforming (or even with direct oxidation, depending on the hydrocarbon weight) simplifies, reduces costs and required space and extends mean time between failures (MTBF) of the fuel treatment system with respect to the hydrogen-fed FCs. Examples of SOFC systems as auxiliary power units (APUs) include aircraft applications mainly to start the primary engine, to supply the onboard electric circuitry and actuators. In the case of small (typically recreational and unmanned) aircrafts, SOFC systems have been used to support main (electric batteries) propulsion to reduce noise and pollutant emissions, but also to extend the aircraft mission range (with internal generation for battery recharge). Nowadays, due to the higher efficiency (i.e., lower conversion loss) and reliability of electric power management systems in comparison with pneumatic and hydraulic devices, the aircraft industries are addressed to implement the AEA (all electrical aircraft) paradigm and, before completing this

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pathway, the MEA (more electric aircraft) intermediate step treated (among others) by the paper of Rajashekara et al. [13], Morioka et al. [14], and the NASA Aircraft Electric/Hybrid-Electric Power & Propulsion Workshop [15]. While increasing the electric part of the aircrafts to replace traditional pneumatic and hydraulic controls, high efficiency and compact technologies help one to reduce the space required by generators/storage to increase payload and reduce fuel consumption. Indeed, the real limitation of FCs systems in this sector is the lowpower (with respect to conventional turbines) density, so that it is currently still impossible to replace the main propulsion. However, in limited applications (such as small recreational or unmanned aerial vehicles), FCs can support high-power density batteries as range extenders or to release extra power in the case of emergency. In such a field, different scientific literature works (as, for instance, the one by Fernandes et al. [16]) are focused on the cell geometry selection (planar vs tubular) by comparing, ease of production process, power density, lifetime over cyclic usage, start-up time, and so on. Generally speaking, a first result was achieved by Karakoussis et al. [17]; in their analysis for SOFC-based APUs, the authors distinguished planar and tubular cell geometries, thus determining a fundamental difference. As result, in the former geometry, most of the environmental impact comes from the stack components; on the contrary, in the latter geometry, the balance of plant (BoP) produces most of the emissions. In automotive sector, a real world approach is represented by the biofuel-fed SOFC-based system (developed by Nissan Motor Company and reported in their bulletin [18]). Thanks to the SOFC conversion efficiency, besides an almost carbon neutral process, they claim an autonomy range of about 600 km and a powerful acceleration (while keeping very low noise level), combining the advantages of thermal and electrical vehicles (as reported in Ref. [19]). The vehicle has an onboard reformer to process the bioethanol (or a blend with water), so that the economic framework can be supported in regions rich of sugarcane and corn, without huge change of the existing infrastructure, and so almost ready for the market (even in collaboration with other automakers, as claimed in Ref. [20]).

8.2.3 Power backup systems Despite the long (or, at least, not-immediate) start-up, SOFC generators can be used to supply loads even in the case of electrical grid failure. This allows one to increase the so called “resiliency” of the powered plant.

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However, due to the slow thermodynamic response (due to the thermal inertia of the SOFC stack and limited mechanical resistance of cells and sealing in the case of cycled loads) to rapidly/suddenly variable electrical loads, the SOFC system needs supporting by a quite faster electrical storage device (such as batteries) to cope with load transients. From this point of view, the storage system is used to smooth the SOFC working point variations. Therefore the natural gas network (or gas canister) is converted in the UPS primary resource besides the main (or supplementary, depending on the overall plant design) power supply. However, it is possible to implement hybrid systems (with renewable sources and/or storage batteries) to exploit the strongpoints and compensate for the weakness of each technology. For instance, the slow dynamics of the SOFC can be compensated by the electrochemical batteries installation and, in converse, support the generation from RES to contrast their unpredictable behavior (due to wind gale or very low wind speed, for WT, clouds and short distance shadowing for PV plants, and so on).

8.2.4 Hybrid systems exploiting biogas/biofuel production According to the European Biogas Association (EBA) Statistical Report 2017 [21], in the period between 2010 and 2016, the number of biogas plants in Europe increased from about 10,000 to more than 17,000 and installed electrical capacity from 4000 to 10,000 MW. The recent study by Barelli et al. [22] evaluated (in simulation) the potential benefits of the solid oxide fuel cell gas turbine (SOFC GT) combination in microgrids, by exploiting the strongpoints of each technology and compensate for their weak points. The study considered the thermodynamic limitations that prevent SOFC systems from (electrical) load following operations. In particular, from the electrical load point of view, the hybrid scheme developed exploits the dynamic behavior of the GT to let the SOFC system satisfy the baseload with its high efficiency. Indeed, a slow modulation of the SOFC working point was considered within its allowed dynamics. The results showed an average efficiency of about 54.5% (on 24-h long load profile), assuring an overall power production modulation of about 42% despite the SOFC system is expected to modulate only one third of its nominal value.

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Moreover, due to its expected high efficiency and fuel utilization flexibility, a hybrid architecture studied by different research groups is the combination of SOFC and micro gas turbine (MGT), even in applications fed with biofuels. Among the literature works, Krummrein et al. [23] simulated the operation of such a plant with cyclic architecture. In detail, the air compressor increases the SOFC working pressure to improve conversion efficiency. In parallel, the SOFC exhausts are (partially) burned (even with some fresh fuel if necessary to produce enough heat) to be (in part) expanded in the turbine to create the propulsion of compressor and electrical generator and (in part) used to heat the feeding gases. That study highlights the possibility to exploit biofuel (and, in general, fuel with fluctuating composition), whose methane content can drop down to 60% (with a 33% generation performance drop) or even to 40% with only slight conversion efficiency reduction. This represents a promising solution toward CO2 neutral energy market, by operating the necessary regulation in power plant whose renewable sources (e.g., PVs and WTs) have unpredictable fluctuations over time. SOFC systems demonstrated their effectiveness to increase the power conversion efficiency (with respect to traditional ICEs) even in the case of fueling from biogas. This fuel is usually the product of treatment plants of anaerobic digestion (AD) of organic waste and wastewater (e.g., from landfill and sewage). Despite the main components being methane and carbon dioxide, a fundamental feature of the biogas is its variable composition over time. This also affects the heating value and then the combustible components may result in becoming too much diluted to be used in ICEs; on the contrary, SOFC may use CH4/CO2 blends with low fuel content as proven by Staniforth and Kendall [24]. Moreover, the high temperature of SOFC exhaust can be even used in the thermal pretreatment of the digester. The waste water treatment plants (WWTPs) are fundamental to assure that the contaminants/pollutants (typically organic matter, phosphate, and nitrogen compounds) coming from domestic and industrial wastewater are not reinjected into the environment. Moreover, their operation allows collecting, separating, and reintroducing resources such as water, energy, and fertilizers, as well as (as expressed in the work by McCarty et al. [25] when higher efficiency will be achieved) they could be self-sustaining from an energy use point of view. Anyway, WWTPs have environmentally impacting emissions, in particular greenhouse gases (GHG) such as methane and CO2, as well as

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NOx. The main process of such plant is the AD (as explained by Wu et al. [26]), which due to the plant conversion (i.e., CH4 production) efficiency, has a theoretical percentage of recovered energy is about 81%. Saadabadi et al. [27] demonstrated that the AD operated by bacteria, in these plants, first disintegrates the complex organic matter through enzymes and then converts (through hydrolysis) the enzymes products into sugar and amino acids. In the last process, archaea convert those intermediate into (mainly) methane. Since the initial organic matter composition is variable, even the methane production is variable, so that the entire conversion process may lead to net energy loss; this is due to the necessary mechanical, electrical, and thermal energy requests. This is because the waste pretreatment needs heating for the initial sludge degradation (not necessary, but this improves the methane production), the digester requires matter stirring and pumping, and temperature control to enhance reaction yield. The energy conversion step is traditionally carried out by ICE or GT in which the biogas is burnt; as we know, this has lower conversion efficiency with respect to FCs, above all for electrical power production (e.g., for grid injection, due to the indirect conversion in ICE and GT direct conversion in FC). Moreover, different SOFC integration benefits can be envisaged: • The high temperature of the SOFC exhausts, this can be exploited to provide heat to the pretreatment reactor. • The ammonia extracted in the pretreatment can be used as SOFC fuel. • The CO2 component of the biogas helps the methane reforming into the SOFC. Concerning with the WWTP, a multifuel SOFC demonstration system was developed by Convion to exploit biogas (as reported in their press release in Ref. [28]) from an industrial site in Collegno (Italy) in the frame of the European project DEMOSOFC. With the aim of reducing carbon emissions, energy waste from onsite generation, and promoting the energy independence of the local plant, the system allows one to support the fundamental functions of the wastewater treatment apparatus designed to a community of about 180,000 people, as per the results reported in Ref. [29]. The feeding gas has about 60% 65% of methane content (from the anaerobic process of organic matter) and (due to the local utilization) does not require additional processing to be distributed through pipeline. Overall, the system replaces (by its own generation)

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about 30% of the energy bought from the grid (so increasing the plant resilience against disruptive events) and the heat generated is sufficient to support the wastewater processes.

8.2.5 Combined heat (cooling) and power generation Also known as cogeneration (CHP) and trigeneration (CHCP), such configurations aim to satisfy the aggregate load demand both in terms of thermal and electrical energy. Indeed, compared with separated generation, the combined approach allows one to customize the electrical-to-thermal ratio according to the user needs. Due to the already-mentioned advantages (in comparison with GTs and ICEs), SOFC systems have been increasingly used for integration in CHP plants. Moreover, thanks to the high exhaust temperature, both heat exchangers can have reduced size and the drained heat can support a larger number of applications. In particular, in the paradigm of the socalled smart grid and smart cities, Elmer et al. [30] showed that the expected energy savings can benefit even by using such exhausts in district heating and hot water production. On the other hand, SOFC/CHP integration needs some additional effort to become commercially valid in everyday applications. In particular, thermodynamics, cost, and lifetime must be addressed by engineering processes. Indeed, mainly due to the not mature technology at commercial scale, most of the available literature deals with numerical modeling (i.e., system simulations), addressing the thermodynamics issues by assessing the system performance (maximum power, fuel utilization, and electrical efficiency) while varying stack pressure, fuel dilution, temperature, and system layouts. Due to the recent introduction of FC with to respect other generation technologies, SOFC systems are mainly studied in combination with traditional generator to improve both technical (i.e., overall conversion efficiency) and environmental (i.e., pollutant emissions, mainly SOx, NOx, CO, and CO2) performance. From the economic point of view, the current price of (pre-)commercial SOFC systems is still not competitive with fossil fuel based generators, unless the environmental and social costs are considered. A full energy cost evaluation as in the work by Scataglini et al. [31], modeling different buildings (hotels and hospitals) supplied with 10 250 kW SOFC systems, including the reduction of externalities

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(cost of environment restoration, health impact), GHG emissions, and heating savings demonstrate that the leveled cost of energy (LCOE, whose details for calculation are given in Ref. [32]) is very close (and even lower) than the average LCOE in the case of centralized (traditional sources mix) production. Moreover, compared with centralized generation, CHP helps one to reduce transmission loss and, by coupling the system with appropriate heat exchanger and/or storage. In particular, application tailored on SOFC systems has been envisaged in those cases where a water loop heat pump (WLHP) can be exploited in building thermal management to transport heat from overheated zones (e.g., for human activities) to cold zones (that have to be made warm for human comfort). In such cases, as demonstrated by Tan et al. [8] since the WLHP operates a redistribution of the thermal energy, an SOFC system can be exploited for CHP by supplying the WLHP with electricity and use the waste heat to support the space heating and cooling. In stationary applications, the SOFC technology is particularly appreciated in the cases characterized by an electrical-to-thermal load ratio around one. For instance, Zink et al. [33], analyzed (by developing a model of the system and case study assessment) the possibility to use a natural gas fed SOFC system for building space heating and cooling, hot water production. By integrating an absorption machine with an SOFC system, the authors predict economic and environmental benefits, as well as a total production/conversion efficiency of about 87%, with a sustainable economic performance expected in 10 years. An example of CHP system to support a PV plant was recently built in an industrial area in Lempäälä (Finland) (from the collaboration between Convion and Elcogen, reported in the Elcogen case study report [34]), even thanks to the investment aid (reported in the Lemene project description [35]) of the Ministry of Economic Affairs and Employment. In particular, two FCs systems (116 kW in total) in CHP configuration have been installed to support the energy self-sustaining (as claimed in [36]) of a business district together with a 4 MW PV plant and an 8 MW biogas engine in the frame of the LEMENE project to reach the Finnish targets of 55% self-sufficiency (as claimed in the brief communication in Ref. [37]) and low-carbon energy generation. In addition, the developed plant aims to the power security of the installation site and the capability of offering energy reserve for the public grid.

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Another recent example of SOFC-based CHP plants is given by the containerized system that has been developing by FuelCell Energy (in 2017, under US DoE contract) to supply commercial and residential users in Pittsburgh (within the NRG Energy Center) whose development was described by Ghezel-Ayagh [38]. The system (that does not require water at full power) is fed with natural gas (since the system includes a desulfurizer), but the development roadmap (reported in Ref. [39]) includes the goal of biogas operations. The 200 kW (at AC section) system consists of two 100 kW modules (80 cells each) working with about 62% electrical generation efficiency (more than 70% at stack level) and the capability of heat recovery that sums up to an overall CHP conversion of about 89%. The technology perspective (as claimed in [40]) is the alternate operation as FC and electrolyzer, allowing one to locally produce hydrogen, and that can be used in a subsequent phase. The containerized integration allows one to easily transport the system after the assembly in factory.

8.2.6 Demonstration for critical environment applications In the last decade, the exploitation of liquid fuels (including biofuels) was addressed even in small power applications (,1 kW), as in the demonstration prototype reported in Ref. [41], developed by Protonex. They adapted their previous systems to be fed with gasoline, kerosene, and biofuels, in military environment even thanks to its high efficiency, low weight, and noise level, both as a portable generator and APU under harsh operating conditions. Among the possible applications in critical environment (at even smaller design power value), a noticeable example was the achieved reliability of an SOFC-based power network through five 25 W systems (by Adaptive Materials Inc., in a US DARPA funded project). Such systems (according to Ref. [42]) were developed to supply a (mobile) computer network to store medical data in a rural community in Las Caldares (Dominican Republic). Such mobile power network was used to overcome the inherent power availability of the local grid to support power critical services. Concerning critical services provided with low environmental impact, for example in medical/hospital environment, an SOFC system installation has been recently announced in Ref. [43] by the SUNY Medical Center (in Brooklyn, New York, United States). Through a joined initiative from the Californian company Bloom Energy and the US energy

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company Con Edison, almost half of the campus electrical consumption will be served by a 1.8 MW SOFC system, so that the benefits expectations deal with the grid relief, the increased reliability of the supply (even including 2/3 of the University Hospital of Brooklyn) and reduction of air pollution around the installation area.

8.3 Basic system architecture 8.3.1 Ancillary devices Despite being the heart of every SOFC-based generator, the stack needs to be supported by other devices to be properly operated (i.e., generate electrical power). Moreover, since the main SOFC technology applications include the CHP generation, to harness, collect, and exploit the waste heat from “exhaust gases,” a specifically recover system must be added. Generally speaking, since the stack must be fed with appropriate fluid/ gas stream, depending on the available fuel, a fuel treatment system could be necessary. Moreover, from the thermal and thermodynamic points of view, the gases entering the anodic and cathodic compartments (fuel and oxidant, respectively) need being heated up to avoid temperature drop of the stack mass (and electrolyte, compromising its conductivity) or affect the thermal balance of the redox reaction. From the dynamics of the process fluids perspective, the fluid dynamic resistance of the cell flow field must be compensated by appropriate devices to increase the gas pressure at the stack/system inlets, even considering the opportunity to make the stack work at pressure higher than the ambient value. While assessing the performance measurement of an SOFC system, the overall evaluation must include several parameters (performance indicators) such as power generation (nominal, peak, and specific per mass and volume values), durability (lifetime), power decay over long time, conversion efficiency (that is fundamental to evaluate the fuel cost over system life), geometric size, weight (depending on the system application), the internal consumption of the ancillary devices, and others. Indeed, the abovementioned required ancillary devices need appropriate connections schemes to the stack, since the pathways of the input and output gases affect the thermal management and the efficiency of the system. For instance, the exhaust gases may be burned to generate heat both to support the system start-up (since the stack is at room temperature) and to heat up the “fresh” gas feeds (fuel, oxidant).

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Depending on the system architecture and technology, even water consumption and control system complexity (cost, mean time between failures, required installation space) may be used, while comparing different systems with one another. Moreover, besides the evaluation at normal operation time, even startup and shut-down phases may be used to have a thorough comparison among different systems. Since the SOFC technology needs to reach high temperature (e.g., 750°C) some energy (and time) must be spent to lead the cells at their design working point. This implies both the installation of heating equipment and a nonnegligible start-up time. From the one hand (beside the economic cost) the heating equipment (electric or gas powered) has both an intrinsic energy cost (consumption to run), an additional cost due to its control system (in particular if a redundancy is required for the sake of safety). On the other hand, to evaluate the system performance over time (and, therefore, the overall cost estimation while replacing the traditional power generators), phenomena, and events impacting on the degradation in long run, like thermal and redox cycles, which are correlated with the number of allowed start-up/shut-down, must be introduced and estimated, as well as their marginal impact on the energy conversion efficiency.

8.3.2 Blowers pumps reformer heat exchangers afterburner power converter(s) The first consideration is the necessity of injecting the gaseous streams, fuel, and oxidant, respectively, in the anode and cathode compartments, by overcoming the fluid dynamic resistance of the stack and piping (mainly) and other components. To do this, depending on the gas pressure (i.e., if flowing from high pressure canisters or from low pressure lines or sucking air from atmosphere), there may be necessity of a blower or suction fan to increase pressure or, on the contrary, a pressure regulator (i.e., to add a pressure drop) to avoid that the high pressure gas create mechanical stress/damage (up to the rupture/destruction) of the cells in the stack. Blowers are used to inject the oxidant in the cathode compartment (to have redox reaction) and (if present) to the afterburner. To avoid continuous regulation, which may lead to gas flow rate fluctuations and power consumption overshoot, blowers are actually operated in a small number of working points (flow rate/pressure drop) optimized with respect to the stack operation design.

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Pumps allow one to feed the system with water or other fluids. In particular, a pump may be used to provide the cathode compartment with feedwater to support the system thermal management; on the contrary, a pump with fine flow rate regulation can be used to inject water (steam) into the anodic stream to trigger steam reforming in the reforming reactor. A schematic diagram to summarize the presence of the most common ancillary devices around the cell stack is given by Fig. 8.1. In that scheme, typical (even combined) alternatives are highlighted with different color dashed borders (lines, rectangles): • in orange: the gas reformer, for the fuel preprocessing (dry or with steam) and support the internal fuel oxidation; • in blue: the two rectangles suggest the possibility of using the heat power in the exhaust gases to produce hot water for reuse in the system itself or to provide heat power to an external load (cogeneration); • in red: the burner offgas could be used to drive a gas turbine and, depending on the gas flow rate and temperature, the turbine may drive air and fuel compressor (or blowers, to reduce internal electric consumption) and/or a second electric generator; and

Figure 8.1 Block diagram of most common ancillary devices BoP in an SOFC system. BoP, Balance of plant; SOFC, solid oxide fuel cell.

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in green: the pump for feedwater whose presence depends on the system design (thermal balance). Due to the I V curve behavior, to supply an electrical load, one (or more) power converter(s) is (are) required. Power converters are necessary to make the voltage stable at different power generation and to limit the drained current, both to avoid cells’ damage and to start appropriate trigger/feedback signals to the other ancillary devices. In particular, • fuel (and indeed even oxidant, depending on the thermal management strategy) flow rate is proportional (due to the Faraday law, by means of the stoichiometric factor) to the stack current (and, therefore, to the load power); therefore, in the case of CPOx, even anodic air flow must be adjusted; • if the thermal management is operated by the feedwater, even the pump operation point (rotation or peristaltic regime) may vary (usually, in stepwise mode); and • cell/cells cluster voltage values (if monitored) thresholds (for diagnostic). As above reported, the main role of the power converter is the adaptation of the voltage variation of the FC stack (at different current values) to a load requiring (almost) stable voltage (at different power values). Therefore, since the total voltage span of a single cell is about 1.5:1 2:1 from Open Circuit Voltage ( OCV) to maximum power point voltage, the same ratio is necessary as input range of the power converter. Indeed, depending on the load, the generated power conversion (in terms of voltage and current) has to lead to direct current (DC) or alternate current (AC); for this reason, different converters need to be considered. In other words, starting from an unregulated DC generation, both DC/DC converters (voltage regulators) and DC/AC converters (called “inverters”) may be required to interface the load, as presented by Fig. 8.2. Among the former group, step-up (or boost converters) and step-down (or buck converters) are able to, respectively, increase and decrease the stack voltage, so that giving design specification to determine the cell number of the stack and the DC/DC working mode, depending on the served load. On the contrary, in the latter group (i.e., inverters), the main feature that distinguishes two categories is the ability to be tied to the (public) grid. Hence, inverters able to be grid tied have to be compliant with (national) regulations to avoid disturbance to the power network and

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Figure 8.2 Power conditioning devices to electrically connect the stack to the supplied load. The DC/DC converter (voltage regulator) adapts the output voltage level to the load. The DC/AC converter (inverter), if required (depending on the load), allows the system to generate alternate voltage and current (as in the depicted case to connect the electric grid). AC, Alternate current; DC, direct current.

synchronize the generated alternate voltage/current waves with the grid (at the “point of delivery”). In contrast, for off-grid applications, the inverter must be able to create the sinusoidal behavior of the generated alternate voltage/current on its own, as typically is in UPS or island mode power supply systems. From the power regulation point of view, the DC/DC adjustment must include the following: • output voltage setting: to support the load requirements (i.e., its input voltage range); • as three alternatives one another: • output current limitation: to let the load drain the correct power value; • input current regulation: to avoid disruptive stack current rush; and • input voltage regulation: to limit the power. Input current regulation is, additionally, fundamental to limit/adjust the FC system contribution in a larger plant. Second, the DC voltage regulator can be used, as in Fig. 8.3, to assure the supply to the auxiliary devices at the appropriate voltage disregarding the SOFC stack working point. For instance, let us consider a hybrid production (or even mixed, with energy storage devices) plant whose power generation can be modulated over time to provide the user, or even the electric grid, with energy services. A possible connection scheme of SOFC/battery hybridization is given in Fig. 8.4, in which the DC voltage regulator is used to both uncouple the SOFC working point from the load demand and allow the battery recharge from the SOFC generator. Depending on the design choices, ancillary devices can be powered from either the SOFC generator or the battery.

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Figure 8.3 The auxiliary devices may be supplied (once reached the working conditions) by the power from the stack; depending on their allowed supply voltage range, a DC/DC voltage regulator may be required. DC, Direct current.

Figure 8.4 A possible electrical connection to hybridize the SOFC generator with an electrical storage device (battery). The voltage regulator allows one to impose the SOFC generator working point and the battery discharge and charge. SOFC, Solid oxide fuel cell.

In this case, in the plant design phase, accordingly the baseload value or expected hourly profile can be entirely satisfied with the deterministic energy sources and the load fluctuations can be compensated by using adjustable resources (batteries, flywheels, FCs, and so on) whose constraints depend on the dynamics of each single resource.

8.3.3 Power conditioning devices impacts A second component affecting the overall system behavior is the power conditioning devices, whose efficiency is mainly influenced by the switching transient (due to the high-frequency commutations of internal PWM generation circuitry) losses that result in voltage drop between the input and output power sections. Therefore current fluctuation, the so-called ripple, is measurable through the power converters and is even sent back to the FC stack. This phenomenon can be split into two main kinds, the high-frequency ripple (directly generated by the high switching frequency circuitry) and the low-frequency ripple (resulting from the mutual modulation of different switching circuits). Despite the high frequency ripple’s

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ability to be suppressed by custom design filters, the low-frequency ripple influences (superposing a periodic current component) the FC stack working point and, as a consequence, the expected lifetime, due to the uncontrollable fluctuations of the process variables (temperature, pressure, fuel, and oxidant stoichiometry). For this reason, in the literature, several works are reported to find system-based solutions (on the BoP around the stack); such studies present tailored topologies as in the work by Mason and Jain [44], band-filtering techniques as in the work by Moon et al. [45], or operating directly on the ripple source (DC/DC and DC/AC converters) like Liu et al. [46] or Lai et al. [47] to mitigate such detrimental impacts. Thus, above all, the increasing penetration of DG (mainly through RES) led to highlighting the importance of power quality at the delivery (i.e., injection) point. This is due to the disturbance that the possible growing number of unregulated systems (and in particular inverters) may introduce into the grid. The main causes of such disturbances are • the (current) harmonic components, which affects the connected electronic boards; • unregulated reactive power, that is, an inverter output impedance that results in an “unregulated” power factor (phase discrepancy between voltage and current waves); and • delay between the produced voltage wave and the corresponding grid phase, causing a composed voltage power, different from sinusoidal wave. Linear passive filters succeed in cutting high order harmonics but have low ability to cancel the third harmonics (3 3 fundamental frequency) and risk of causing phase shift (i.e., delay) to the fundamental frequency of the generated sine wave (50 Hz). For this reason, the power conversion systems must be equipped with active power filters. Such filters operate as power converters that introduce nonlinear effect (due to the presence of electronic switches) but, if properly designed, can regulate (usually minimizing) reactive power and cancel the third harmonic component. Indeed, even reactive power can be used to provide grid services; this is used to support the distribution grid to regulate the grid voltage RMS value. In stand-alone applications, the highly variable production from renewable sources must be compensated to satisfy the load. Regardless the

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load is stationary or rapidly variable; the power conversion system must distribute the load transient among the SOFC generator and the batteries (or other controlled production/storage devices). In the literature, this topic is addressed by different works, mainly in simulation environment, to determine both control strategy and auxiliary lumped components values (capacitance, inductance, and resistance). A first limiting factor is the different dynamic response of different technologies. Generally speaking, since SOFC generators may only withstand very slow power/current variations, the transient load variation is “absorbed” by the storage and, after the quickest effects, the SOFC generator will be able to adapt its operation point to the new “averaged” power (load) value.

8.3.4 Control algorithms for automatic system optimization The development of SOFC technology depends also on the evolution and enhancement of the system integration and control. In this research field, SOFC systems can be compared in terms of overall layout and power generation configurations to highlight the benefits and weakness of each design choice. In detail, the arrangement of fuel processing (if required and even in multiple steps), the thermal management of the stack (using heat exchangers and/or postcombustor, to reuse thermal power from exhausts, bypass valves to tune gas mixing), other ancillaries (blowers, dosing valves, fans, even for fuel recycle) determines different compromise between conversion efficiency, system simplicity, fuel utilization, and power balancing (electrical vs thermal). For example, gas recirculation was evaluated by Chitsaz et al. [48], by analyzing four configurations of trigeneration (SOFC-based) systems. By investigating the gas recirculation from both anode and cathode compartments, the work demonstrates that (despite the increased complexity and the correlated gas management effort) both the exergetic efficiency and the economic evaluation show higher indicators if both recirculation processes are performed. Due to the number and complexity of the relations among several concurrent process variables on the system performance, at present, system control optimization approaches include artificial intelligence (AI) techniques (whose principle are described in Ref. [49]) such as artificial neural network (ANN, proposed by McCulloch and Pitts [50]), fuzzy logic (FL, proposed by Zadeh [51]) and genetic algorithms (GA, whose

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fundamentals are reported by Holland [52]). Such techniques are usually applied to determine possible set of process parameters where a nonlinear multiple-input (cell temperature, fuel and oxidant pressures, fuel and oxidant flow rates, and even structural parameters of cells) multiple-output (current, voltage) system represent a complex device to be analyzed from a theoretical and mathematical point of view. On the contrary, such AI techniques approach the optimization process through empirical data to achieve satisfactory performance with reduced computational effort, thanks to the reliability (due to the experimental origin of the data) of the used computation datasets. Even combined approaches, such as neuro-fuzzy inference can be applied to improve control accuracy and off-line algorithm refining (i.e., the initial ANN training). Usually, to reduce the computational effort at run-time, different layouts (varying the number of layers, the number of neurons in each layer, and the transfer functions between two adjacent layers) may be simulated to compare the results one another and minimize the system complexity with sufficient accuracy (discrepancy between actual output and calculated output). For instance, Entchev and Yang [53] implemented a 3-layer ANN neuro-fuzzy inference control: an input layer (usually called “perceptrons”) to collect stack and gas parameters, a hidden layer (whose neurons operate as weights to combine the influence of each input parameter to determine each output variable). The usual representation of such a structure (input output architecture), including the weights associated with the various intrinsic system relations (weighted sums to approximate the system behavior with a linear combination of the input and status), is provided in Fig. 8.5. The subsequent step is the creation of a fuzzy inference engine (or adaptive-network-based fuzzy inference system) that is used to implement learning capability in the adjustment of membership functions of the FL machine. In detail, the FL is based on the definition of (partially overlapping) intervals, usually labeled like “low,” “intermediate,” “high,” and so on, to distribute the whole variables span in a sort of mapping through membership functions. An example of such distribution as membership function of one process/control variable is given in Fig. 8.6. Indeed, such functions map the abovementioned variable values toward probability to put at each labeled interval, on the basis of “fuzzy” (i.e., “vague” and “blurry”) association that an operator/investigator as a

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Figure 8.5 Generic scheme of a 3-layer artificial neural network. It is possible to distinguish an input layer (perceptrons) to collect the process variables, a middle layer (hidden nodes) to combine the input variables, an output layer (to determine the control variables or to predict the system output).

Figure 8.6 Representation of a generic membership function of a fuzzy logic machine, characterized with different (partially) overlapping subdivision range and membership probability.

designer or a user of an appropriate controlling tool implements a strategy of adjusting external actions to optimize the system working point. An alternative technique, often used to compare different solutions to a single problem (e.g., the optimization of a set of parameters representing

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the system working point at a steady state) trying to determine an optimization procedure by iterative steps, consists of the genetic algorithms. This AI technique tries to extract a selection of best fitting solutions from a “population,” that is, all the proposed/tested tentative solutions (called “chromosomes”), each consisting of a ordered set of parameters (called “genes”) in each step of the population “evolution,” based on a predefined “fitness score” determined by the distance from and expected target function. Once determined the selection of the best “chromosomes,” the algorithm combines (“crossover” phase, even introducing a random component) genes coming from two selected chromosomes to result in the new “era” in which the new solutions are measured against the “fitness function” to determine the selection of the subsequent iteration. Indeed, a random process determining arbitrarily “mutations” on genes is usually added to introduce new “genetic matter.” Starting from the above summarized techniques, optimization algorithms have been developed in the literature. One of the most computationally lights is the radial movement optimizer (whose details are given by Nassef et al. [54]), which evaluates the target function over small variations of the working point around a preliminarily assessed working satisfactory point, until finding a best fitness (e.g., the highest power density generation). Even GA can be enhanced by hybridization with other expert system techniques. For example, a radial basis function neural network (applied by Wu et al. [55]) is used to determine the input parameters (temperature, flow rates, gas pressures, and so on) of an SOFC stack working point, by minimizing (in the sense of the least square metrics) the error between expected output variables and simulation. In particular, the GA technique is used to generate (in the evolutionary iterations with crossover and mutations) the aggregate of weights, centers, and width (of the intervals to which the NN parameters belong) to update the underlying neural network. After each iteration as explained by Goldberg [56], the GA selection (i.e., by the fitness of generated population individual), crossover (among the selected individuals), and mutation (to introduce novel “genetic matter”) are operated to simulate the population evolution.

8.4 Numerical models As done in various physics applications (fluid dynamics, electromagnetic wave transmission, heat transmission, vibrations, and so on), even an

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SOFC-based system can be modeled, both in design and diagnostic phases, it is possible (at least with proper approximation) to forecast the behavior at different levels of representation details. In particular, simulations may describe a system just from a single aspect of multiple physics phenomena and their interactions. Moreover, the simulation algorithms can represent just one single device (usually in deep detail) or the combination of each system component. Usually, in this latter case, to focus on complex architecture and to avoid abnormal computation effort increment, each single component may be represented as a “black box” (i.e., lumped elements associated to one or more transfer functions or with multiple dimensions tables/vectors, without considering the components geometry) whose input and output parameters constitute the connections between the “boxes.” In most cases, the modeling process is based on equations (“process drive” approach) coming from theoretical (energy and mass conservation) equations or on “data-driven” techniques (in particular in the modeling of complex phenomena with expert system solutions). Solution methods include both analytical and numerical expressions. The former ones (which the work by Janardhanan and Deutschmann [57] belongs to) are easier to evaluate and (in most cases) represent the theoretical expression of the simulated phenomenon under ideal (simplified) working conditions (e.g., uniform distribution temperature, adiabatic reactors, instantaneous gas diffusion, infinite size of the components to avoid border effects). To enhance the accuracy of such forecast methods, the analytical expressions may be integrated and tailored with empirical correction factors/coefficients to include the effects under nonideal conditions. From a system point of view, the most commonly evaluated parameters are • performance in terms of power generation (nominal and peak value); • long-term performance decay (optimal working point deviation from beginning-of-life to end-of-life, in terms of fuel consumption, voltage at maximum power, conversion efficiency); and • lifetime. Generally, several commercial simulation software applications have integrated development environment with dedicated library function to implement customized architecture with well-known components (cell stack, fuel reformer, water pumps, heat exchangers, other reactors) whose description parameters (attributes) are used as coefficients (straightforwardly or after intermediate calculation) of mass and energy balance equations.

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Second, to reduce the computational effort (therefore the simulation running time), the simulation details can be increased only on a specific part of the system. This can be done by simulating the stack, the reforming conversion (as transfer function), or the single auxiliary component only and then using the results to develop simplified models of each component to simulate the overall system behavior. This technique was used, for instance by Yakabe et al. [58], to study transient behavior like at the start-up or during rapid and relevant load transients, when the air-flow response requires long time to be stable. To solve such kind of problems, Choi and Stenger [59], or Sedghisigarchi and Feliachi [60,61], considered both nonlinearity of the electrical response, while varying fuel flow rates and electrical load. By means of a simplified modeling, Jurado [62] decomposed the system in a nonlinear static section and a linear dynamic section to analyze the effects of fuel flow rates, pressure, and temperature variations. Concerning hybrid power generation systems, in simulated literature investigations, different layout and coupling schemes are present. Whiston et al. [63] accomplished a comparison between simple SOFC and hybrid SOFC-microGT systems was performed even at 1 kW power generation scale. In that work, starting from the assumption that despite SOFC microturbines having better generation efficiency than only SOFC (standalone) systems (66% vs 59%, respectively), the formers are currently available only as demonstrators for economic matters, the authors assess the overall life costs, on the basis of commercial systems performance and construction data at 1 kW (or less) scale. From the calculations, the analysis results in a lower cost of hybrid system in the case of baseline operation; on the contrary, once the SOFC system is operated in CHP applications, the overall economic performance is higher than the hybrid configuration. Indeed, the exergetic studies on SOFC technology are addressed to MW scale and indicate different causes to the exergy destruction in the conversion process. For instance, Calise et al. [64] and Gandiglio et al. [65] investigated, respectively, on both a 1.5 MW hybrid system and a high-power SOFC generator (220 MW as module, 270 MW as hybrid, 280 MW if pressurized) and concluded that the stack is the main section of exergy drop and the afterburner as a second exergy destruction source; moreover, the latter cited paper performing the evaluation even for a stand-alone SOFC generator and, in this case, afterburner and preheaters were the main causes of exergy drop. Calise et al. [66] achieved a different

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result from investigations running the system at partial load, since in this case the system control strategy (i.e., air flow rate, fuel flow rate, and combustor bypass control) becomes the main point for that evaluation. This seems to be attributable to the high sensitivity of GTs to the input condition variations due to the SOFC generator performance variations, so that the narrow useful range of mass flow rate and pressure of the GT, as well as the air compressor working range, reduce the number of realistic solutions coming from the simulations (i.e., a great number of numerical solutions do not consider physical constraints about GT working point and/or technological limits on temperature, pressure, rotation speed, and so on). Investigation on different hybrid systems has been carried out in the literature, to combine different thermal cycles with SOFC generators. For instance, recently, Hosseinpour et al. [67] analyzed an SOFC Goswami combination as an assessment of the possibility of wood-fed SOFC (through biomass gasification) to produce electrical power, integrating a Goswami cycle machine to exploit the waste heat to generate refrigeration power (besides the electrical generation from turbine). Such evaluation demonstrated (under a set of assumption of ideal behavior of the process, to reasonably simplify the simulation) the evidence of finding a trade-off between increasing power density (electrical and cooling) and indicated that the main efficiency drop causes (i.e., irreversibility sources) are the gasification reactor (biomass to syngas conversion), and the boiler of the bottoming cycle. At their maximum efficiency working point, the analysis estimated the possibility of increasing the energy efficiency from 40% to 58.5% with the integration of the bottoming cycle with respect to the SOFC generator only. Among the system layouts currently present in the literature, Eisavi et al. [68] analyzed the difference of two opposite connections (parallel and series) of the cathodic compartment feeding of two methane-fed (with internal reforming) generators (each including two SOFC stacks), while studying the integration (using a single postcombustor in every system) with a gas turbine. As a benchmark, they used a single stack generator with GT coupling and in the two modified configurations the anode compartments are fed separately (i.e., in parallel) through a gas “splitter.” From the study, it resulted that the efficiency indicators (both electrical and exergetic) increase from the base case to the parallel connection and even better in the case of series connection for the overall systems. In detail, the overall electrical output is higher in the series connection even

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thanks to the lower consumption for air compression (despite reducing the generation from gas turbine with respect to both the benchmark and the parallel connection layout). Moreover, the economic evaluation performed showed that the series connection has the lowest cost ($ h21) and the benchmark layout has the highest one. As above described, different research works deal with different performance indicators (like efficiency values, costs, environmental impacts, and system complexity) and, concerning with the optimization of an SOFC system performance, each indicator can be useful to characterize and compare different systems with one another. In the literature the recent paper by Cheng et al. [69] addressed the study of a multiple-objective constrained optimization, by the comparison of four (commercial) systems whose generators can be distinguished on the basis of feeding fuel, fuel processing, and coupling layout (even with hybridization purpose with other technologies). The analysis, carried out with simulations scaled on a 10 kW base and addressed to an exergoeconomic assessment, models each system device in the Matworks MATLAB development environment through genetic algorithms techniques. A more detailed model is dedicated to the stack (for temperature distribution analysis) and lumped elements represents the remaining BoP devices. The gas was applied to optimize the nominal working points (temperatures, gas pressures and flow rates, cell voltage, and current) to compare the performance achievable by each system.

8.4.1 Simulations of specific behavior 8.4.1.1 System/performance degradation over time Degradation models study the effect of operation over time on the overall system performance by splitting the impacts on stack and BoP, but this latter part is very seldom present in the literature. From the stack side, the main causes are due to the inner chemical reactions (such as electrode poisoning, materials oxidation, and carbon deposition) and physic modifications of the cell structure (such as cyclic volume variation typically due to thermal gradients and thermal cycles, and nickel sintering). On the other hand, Greco et al. [70] investigated the effects of a reformer failure in terms of performance degradation and system safety. 8.4.1.2 Gas leakage in solid oxide fuel cell system operation Despite the commonly provided gas tightening to the stack cells, in real operation on the long run, some gas leakage (from the anodic and

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cathodic compartments, both through the electrolyte interface or the lateral surfaces) is unavoidable. The main mechanism of such phenomenon roots, as reported by Rasmussen et al. [71], in pressure difference (a sort of drift of the bulk gas as a whole) and concentration gradient (in which each mixture component has its own diffusion coefficient, so that they are almost independent of one another) between the anodic and cathodic compartments. However, both lead to a mixing of fuel species and oxidant, so that a part of the expected redox reaction, and the consequent power production, will be lost. Anyway, minimal leakage amount is usually tolerated, despite being a cause of accelerated performance degradation over long run. In the literature, Halinen and Pennanen [72] distinguished (on the basis of the involved leaking interfaces) two main leakage categories: internal and external. The internal leakages are paths into the stack or through the inlet and outlet of gas manifold, so that the anodic leakages cross the cathodic manifold outlet and the cathodic leakages cross the anodic manifold outlet. On the other hand, the external leakages involve flushes from a stack compartment and the manifold, for example, (fresh) process air flow from the manifold that penetrates the anode inlet or outlet, or cathode outlet. Therefore, the composition of the flowing mixture depends on the starting point of the leakage and the crossed interfaces, so that even flammable mixtures may be present; this risk is increased by the presence of a catalyst and high temperature in the stack. In general, the most evident consequence is the reduction of available fuel; this may occur both for oxidant leakage in the anode (as a part of the fuel reacts in the anode compartment with the oxygen) and fuel leakage toward the cathode compartment, combusted resulting in CO2 and water production. Thus, the fuel utilization will grow. This may lead to three dramatic consequences: • First, there is the possibility of fuel flow rate lower than the stoichiometric value, required to generate the expected current (according to the Faraday law), so that the anode risks to be oxidized. • Moreover, the internal stack temperature will increase over the design (i.e., optimal) value. • Furthermore, on the contrary, the already reacted fuel will not be provided to the postcombustor, so that the thermal balance of the whole system will be influenced by the leakage phenomena in terms of both

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output temperature and thermal energy provided to the “fresh” feeding gases, affecting the overall efficiency of the system. Indeed, while considering systems ready to become commercial products, even the presence of such temperature variations can cause unpredictable thermal gradients in the system and, if the system layout includes anode exhaust recirculation (as reported by Dietrich et al. [73]), the gas composition results different from the expected one and may lead to problems (oxygen presence in the fuel stream and condensing steam due to the lower temperature) during system start-up/heating up as demonstrated by Halinen et al. [74]. The solution of such an issue could be addressed (if economically feasible while compared with the cost of voltage/performance degradation and lifetime reduction) by in situ measurement of the leakage composition. 8.4.1.3 Distributed generation and system dynamics simulation matters Concerning with DG, SOFC systems have been proposed to achieve both clean energy production and power quality support. Telli and Barkat [75], for instance, selected an SOFC generator to supply both power network and a dynamic voltage restorer (DVR), as components of a node of a distributed power network. Due to the expected small power generation (as per the DG paradigm), SOFC generators appear adequate to such task mainly thanks to their high efficiency, fuel flexibility, nonnoble catalysts, and the high exhaust temperature to feed a cascaded bottoming cycle to recover thermal power (either to generate additional electrical power with a GT or satisfy a thermal request by cogeneration). In that work, the system modeling was mainly addressed to overcome voltage sags (thanks to the DVR implementation) and enhance the power quality for sensitive load that would be damaged by grid interruption or voltage disturbance (drops, spikes, and so on) with the additional benefits coming from the FC utilization with respect to a battery-based storage pack (like an additional energy source, separation between energy capacity and rated power, long lifetime). To pursue such results and preserve overall system efficiency (which could be affected by DC-link voltage deep variations), the investigation was focused even on the control strategy of the DVR (through a PI regulator in the control loop) to interface the SOFC system with the grid in a two-stage (DC/DC and Voltage Source Inverter, VSI) power conversion layout, equipped with ancillary components (filters, clamping diodes, and transformer) to minimize the current distortion.

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In the (long term) transition to decarbonized energy production and hydrogen use in large scale generation, an intermediate step is the use of methane/hydrogen blends (or hydro-methane, like the so-called hythane) in different compositions. Several research groups addressed this opportunity both to determine the suitable dilution, even with specific interest in the consequences and adaptation process on domestic equipment (usually fed with natural gas), pipelines, compressors, vehicles, and so on, even concerning the safety issue with the hydrogen component. Many of these studies indicated a profitable use of such mixtures in several applications, with the additional advantage of CO2 emissions reduction with respect to the traditional fuels. This theme was recently investigated by Cinti et al. [76] through a micro-CHP SOFC system running on natural gas pure and in blending with hydrogen, six gas compositions in total, with internal or external (steam) reforming, by simulating it in Cycle-Tempo development environment. The introduction of hydrogen in the feeding stream may simplify the reforming process, since hydrogen reduces the risk of carbon deposition on the anode catalyst. The simulations indicated that the stack efficiency slightly decreases while the CH4 concentration increases (as well as the thermal and overall system efficiency). On the contrary, the electrical efficiency of the system decreases in the case of blending with respect to the pure CH4, since the reforming effect is lower with respect to the total chemical energy at the input of the system. 8.4.1.4 Hybrid biofuel fed plants simulation approach In order to exploit biogas produced in an AD (from sewage sludge and food waste) plant, a hybrid SOFC/MGT system was developed in Busan (Korea). The plant analysis and design performed by Kim and Chun Kim [77] were addressed to convert 100 t day21 of sewage sludge and 120 t day21 of food waste through the operation of 4 digesters at controlled temperature (36.5°C, despite requiring additional heating and, therefore, additional cost) to promote anaerobic bacteria action (to reduce the overall process time to 20 days). The biogas is mixed with the anode exhaust and then reformed to increase the hydrogen fraction of the SOFC stack feeding mixture. A simplified block diagram of SOFC system fed from biomass and waste water is depicted in Fig. 8.7. The MGT section is driven by the expansion of the combustion products of stack exhaust. Such combustion is also regulated by mixing the stack exhausts with some biogas from the AD plant to optimize the yield of the MGT production; in particular, the biogas flow holds the

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combustion products temperature in a range whose maximum and minimum allow one to avoid, respectively, the necessity of a cooling system and the supply of external power to operate the MGT. The MGT expansion, besides the power generation, drives the cathode air compressor to avoid stack temperature (and therefore the performance) drop. Such plant is capable of treating more than 130 3 106 m3 year21 of sewage sludge and, from the calculations performed in the cited study, would be capable of supplying a 2500 kW hybrid SOFC/MGT (including the about 28% internal consumption for digester thermal management) and so permitting a CO2 reduction by 50% in the served community, with an expected payback time of 6 years. Babar and Khattak [78] showed an example of lumped parameters modeling to estimate the yield of a polygeneration system in terms of electrical power, together with (water and space) heating and cooling from a hypothetic 10 kW biofuel-fed SOFC system. The authors used the exhausts production of the FC generator (i.e., stack and ancillaries like combustor, blowers and power conversion devices). In that work, the model was based on • the single cell generation measurements (voltage and current density) characterization; • the implementation of the irreversible overvoltage (through literature data for electrochemical parameters and empirical constants); • the effect of anodic stream dilution with respect to standard pure hydrogen characterization; and • the self-consumption of ancillary devices (BoP). While running a system on biogas, the fuel dilution affects the power performance. In most cases, the main diluting gas is CO2, which, despite fostering the internal reforming and helping one to avoid carbon

Figure 8.7 Block diagram of the main devices to feed an SOFC generator starting from biomass/waste water treatment plant sewage. SOFC, Solid oxide fuel cell.

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deposition (especially reducing the stack operational temperature), has two detrimental effects, as assessed by Saebea et al. [79]. The former is the possibility of creating a temperature gradient of within the stack due to the endothermic behavior of the reforming; the latter is an efficiency reduction of the fuel conversion. From this point of view, in a later literature work, Saebea et al. [80] addressed the analysis of CO2 filtering membrane to improve SOFC system performance while operating on biogas feed. A performance comparison was performed between the configuration with and without a CO2-selecting membrane interposed between the reformer and the stack anode inlet, while operating in a heat recovery configuration (from all exhaust gas, i.e., burning unreacted anode and reformer output gas with cathode exhaust air). Their investigation shows that, starting with a well-known mixture CH4/CO2 60%/40%, the membrane permeability and thickness determine a different anode inlet gas composition with respect to the case without the membrane. From the simulations, the SOFC efficiency (as well as the thermal efficiency) increases with the presence of the membrane, but, conversely, the electrical efficiency tends to be reduced due to the H2 flow reduction in the system coupled with the membrane. Moreover, a more detailed analysis should include the additional energy required to restore the gas pressure (i.e., the consumption of a fuel compressor) in the system equipped with the filtering membrane.

8.5 Solid oxide fuel cell system costs The cost estimation of an innovative technology toward the market, which has (obviously) high capital costs even due to research activities, prototyping, product development, should begin with the comparison with the traditional technology (or technologies) that is (are) targeted to be replaced (or, at least, flanked). From this point of view, while evaluating the feasibility and opportunity/effectiveness of a new power generation system, a fundamental role is played by the economic assessment in terms of overall value of capital, operation, and maintenance costs. In parallel, since the installation/use of a power generation system is imposed by loads/users demand, a correct evaluation cannot disregard similar alternatives comparison. One of the most used terms to characterize the FC technology in general is the high-conversion efficiency, since it is usually compared with traditional internal combustion generators that are limited, at least, by the

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Carnot principle, that is overcome by FCs thanks to the direct oxidation of fuel. Second, while considering alternatives with combustion, the CO2 generation has necessarily weight in the technology selection process. In this case, metrics (among other the carbon footprint as the most common) are nowadays available to label and compare different devices. Due to the CO2 (and, indeed, other hydrocarbons) effect, the SOFC technology capability of exploiting the CO2 to have (at least) a partial reforming of the fuel makes such systems sustainable to reduce carbon footprint and, at same time, have a promising solution to support carbon sequestration policies. In particular, Rillo et al. [81] worked on SOFC stacks and Jones et al. [82] on smaller laboratory devices (cells, short-stacks) that fed with CH4/ CO2 mixture with dilution down to 20% (such as in biogas production, even from waste recycle) and so exploit mixtures so poor in hydrogen to be insufficient for ICEs. Besides the reuse and low emission of CO2, even other compounds, for example, NOx and SOx production is by far lower than ICEs, so that the overall cost analysis should adequately consider this evidence in a fair comparison with other energy conversion devices. Once considered the potential benefit in terms of pollution emissions, it is possible to focus on the production cost. In the literature, the estimations are correlated to the production of different sizes (i.e., nominal power) and the number of system per year. In a review, Contini et al. [83] evaluated two-system power values (25 and 250 kW) in the perspective of four production rates (100, 1000, 10,000, 50,000 U year21) and showed a breakdown of the direct manufacturing costs (by separating stack and BoP) showing that, in every scenario, the BoP constitutes the main cost source, followed by the stack. In detail, under mass production hypothesis, the primary cost in the BoP is due to the power management (about 70% 75% of total production cost), both electric (power regulator and inverter) and thermal (heat exchangers/CHP-dedicated devices) side. On the other hand, Colantoni et al. [84] estimated around 25% 30% of the production cost, the sum of fuel and air processing, control system (electronics), and components for system assembling. Nowadays, the US Department of Energy (DOE) [85] claims as “costeffective” the power production by using SOFCs fed with coal and natural gas, so that multiyear initiatives to fund R&D project are addressed to

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reach an overall production (manufacturing) cost of 6000$ kWe21 working at least 5000 h (0.5%/1000 h of power decay), in their 2020 targets table [86]. From the EU side, the energy savings trend made mandatory the requirement of “nearly zero energy” for new buildings by the end of 2020. For this reason, even considering that the buildings (at present) represent 40% of the overall energy demand and 36% of CO2 emissions (whose most part is due to the residential segment), the SOFC technology is seen as a promising solution thanks to both the high-conversion efficiency together with a high value (i.e., temperature) of the waste heat, so that it appears ideal for trigeneration. This simplifies the electric and thermal integration while considering a DG paradigm with a lot of prosumers (i.e., active consumers) that can exchange (at different level, from home or building, up to district, city or region) power (electric and thermal) with a higher overall efficiency generation with respect to the separate production. Facci et al. [87] carried out a technical-economic analysis of CHCP with a relevant-sized power system (indeed using ten 2.5 kWel systems) that (in the Italian prices and taxes scenario) analyzed four study cases (i.e., combination of grid-connected SOFC, cooling systems, and boiler) against a reference plant (in which the electrical energy is totally bought from the grid) to determine the savings in terms of primary energy consumption and fuel. Their results highlight that the SOFC introduction allows reducing the overall energy cost (about 60% cost saving, or about 50% while optimizing the primary energy consumption) with respect to the reference scenario. However, such calculation does not include the initial capital cost, still high for SOFC systems, that (in the present Italian scenario) lets forecast a payback period longer than 10 years (i.e., about twice the present commercial SOFC systems expected lifetime). The evaluation of the (both positive and negative) potential impacts of replacing or integration of the traditional internal combustion engine with SOFC-based systems usually follows specific rules to unambiguously compare different integration solutions/architectures. Methodologies like the life cycle assessment (LCA) are standardized to have numerical evaluation of specific indicators that indirectly measure parameters correlated to the sustainability of different technologies (both products and processes). As a literature reference, the international standard ISO 14040 (whose first edition roots in 1997 and whose current updated release is ISO 14044:2006) has been addressed to evaluate the complete Environmental

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Management in terms of materials (polymers, ceramics, metals) and (primary) energy utilization in a so-called from cradle to grave (i.e., from the design to the disposal) approach. Given that FC technologies have higher efficiency and lower emissions than traditional internal combustion engine in their operational phase, the sustainability of such (recent) technology has been evaluated in a limited number of scientific works in terms of • system production (stack, fuel processor, control system, filters, heat exchangers, other auxiliary devices, assembly process); • fuel production/processing: hydrogen is (obviously) the lowest impact on environment, but only if its production from different sources (fossil fuels reforming, coal gasification, and water electrolysis) is demonstrated sustainable (in terms of primary energy utilization and conversion efficiency); and • system disposal at the end-of-life: depending on the material content and transformation from the beginning to the end of system life (to evaluate possible reuse of such materials). With reference to the SOFC systems, the literature works are usually addressed to determine the distribution of the overall system building and operation phase, with a breakdown among each system components per each impact category (e.g., global warming, acidification, and toxicity potential). An overview of such categories can be found in the Guidance Document for performing LCAs on FCs and H2 Technologies [88]. Such studies allow one to improve the environmental performance (e.g., sustainability indicators) by discovering the most impacting manufacturing processes and possible material replacements.

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Index Note: Page numbers followed by “f” and “t” refer to figures and tables, respectively.

A

C

Air electrode material, 110 111 composite ceramic/mixed conductor, 112 113 mixed O2 /e conducting, 111 112 single-phase mixed triple conducting electrode material, 113 115 Alloys metals and, 104 105 nickel-based, 31 Amperometric sensors, 173 174, 189 201, 190f, 191f, 196f Anaerobic digestion (AD), 261 Ancillary devices, 266 267 Area-specific resistance (ASR), 27 28, 32 33 Arrhenius form, 1 2 Artificial intelligence (AI) techniques, 273 276 Artificial neural network (ANN), 141, 273 274, 275f Automatic system optimization, control algorithms for, 273 276 Automotive application, sensors for, 185 Auxiliary power units and propulsion, 258 259

Capacity factor (CF), 129 Carbothermic reduction reaction (CRR), 231 233 Carnot cycle efficiency, 251 Cell/stack modeling, multidimensional approaches to, 134 141 one- and two-dimensional models, 139 140 three-dimensional models, 140 141 zero-dimensional models, 135 139 Ceramic/metal composites, 105 110 Chromium poisoning, 28, 31 32 Climbing image nudged elastic band (CINEB) model, 8 Cobaltite-based cathode material, 111 112 Combined ion effect, 174 Combined sensors, 203 205 Coulometric sensors, 201 203 Coulometric titration, 169 Cubic perovskite structure of CaTiO3, 3f Cyclic voltammetry (CV), 38 39 Cycling degradation of solid-oxide metal air redox battery, 240 241

B Ba-based perovskite oxides, 13 Balance of plant (BoP), 259, 268f Barium cerate, 94 97 Barium zirconate based materials, 97 98 Binding energy (BE), 57 58 Blowers pumps reformer heat exchangers afterburner power converter(s), 267 271 Boron anomaly, 174 Brownmillerite A2B2O4-based materials, 101 102 Butler Volmer equation, 131 133

D Discharge-specific energy (DSE), 223 224 Distributed generation and system dynamics simulation matters, 282 283 Dusty gas model (DGM), 142 143 Dynamic high pressure (DHP) setup, 65 Dynamic voltage restorer (DVR), 283

E Electrical-to-thermal ratio, 263 Electrocatalysis toward bifunctional oxygen evolution reaction/oxygen reduction reaction catalysts, 21 22 Electrochemical active thickness (EAT), 133

295

296

Index

Electrochemical impedance spectroscopy (EIS) measurements, 133 134 Electrochemical pumping sensor, 168 169 Electrochemical sensor, 170, 189 Electrode-electrolyte interface, 36 37 Electrode materials, 104 115 air electrode material, 110 111 composite ceramic/mixed conductor, 112 113 mixed O2 /e conducting, 111 112 single-phase mixed triple conducting electrode material, 113 115 fuel electrode material, 104 110 ceramic/metal composites, 105 110 metals and alloys, 104 105 mixed conductive oxides, 110 Electrodeposition, 36 50 galvanostatic and pulsed current electrodeposition, 46 50 potenciodynamic and potentiostatic electrodeposition, 40 45 Electrodes, 172 173 Electrolyte materials, 94 104 BaCeO3 BaZrO3 mixed systems, 98 99 BaCeO3 perovskite-based materials, 94 97 BaZrO3, 97 98 SrZrO3, 99 100 Electrolytes, 36 37, 170 172 Electrolyzer cell (EC) mode, 11 12 Electromotive force (EMF), 169, 203 Electron conduction and catalytic features at doped BaZrO3, 14 17 Electron spectroscopy for chemical analysis (ESCA_ microscopy, experimental setup developed at, 59 67 Elettra synchrotron facility, 55 57 ESCA microscopy, experimental setup developed at, 59 67 scanning X-ray photoelectron microscopy (SPEM), operating principle of, 59 67 X-ray photoelectron spectroscopy, operating principle of, 57 59 Energy storage unit (ESU), 219 220 improving performance of, 231 238

Equilibrium potentiometric sensors (EPSs), 177 185, 180f automotive application, sensors for, 185 humidity sensors, 182 hydrogen sensors, 182 isotope sensors, 181 melts’ analysis, sensors for, 182 184 operation principle, 177 180 reference electrodes, 180 181

F Faraday’s law, 43, 201 Fe-based chemistry, 223 226 Ferritic stainless steels, 31 32 Fresnel zone plates (FZPs), 59 64 Fuel electrode material, 104 110 ceramic/metal composites, 105 110 metals and alloys, 104 105 Fuzzy logic (FL), 273 274

G Galvanostatic and pulsed current electrodeposition, 46 50 Gas-diffusion-controlled solid-electrolyte oxygen sensors, 168 169 Gas leakage in solid oxide fuel cell system operation, 280 282 Gas polarographic sensor, 168 169 Genetic algorithms (GA), 273 274, 276 Gerischer elements, 134 Glassy-ceramic sealants, 175 177 Glassy sealants, 174 175 Goldschmidt tolerance, 94 96 Greenhouse gas (GHG) emissions, 258 Grotthuss mechanism, 93

H Hemispherical energy analyzer (HEA), 57 62, 64 High-pressure X-ray photoelectron spectroscopy (HP-XPS), 60f High-temperature electrolysis, 126, 158, 160 Humidity sensors, 182 Hybrid biofuel fed plants simulation approach, 283 285

Index

Hybrid systems exploiting biogas/biofuel production, 260 263 Hydrogen electrode, 104 Hydrogen production, 160 Hydrogen sensors, 182

I Inactive silver, 168 169 Insertion device, 59 62 In situ photoelectron spectromicroscopy, 55 ESCA microscopy, experimental setup developed at, 59 67 scanning X-ray photoelectron microscopy (SPEM), operating principle of, 59 67 SOFCs SPEM characterization in different configurations and operating conditions, 67 87 in situ SPEM characterization of SOFC anodic systems, 69 75 in situ SPEM studies on SC-SOFCs to SPEM characterization of selfdriven cells, 75 87 X-ray photoelectron spectroscopy (XPS), operating principle of, 57 59 Interconnectors, 27, 29 30 area-specific resistance (ASR), 32 33 electrodeposition, 36 50 galvanostatic and pulsed current electrodeposition, 46 50 potenciodynamic and potentiostatic electrodeposition, 40 45 metallic interconnectors, 30 32 ferritic stainless steels, 31 32 protective coatings, 33 36 Iron-based SOMARB (SOIARB), 223 226 Iron oxide, proton-mediated redox activity of, 238 240 Isotope sensors, 181

K Key performance indicators (KPIs), 126 129, 128t Knudsen mechanism, 195

297

Kröger Vink notation, 4 5, 91 92

L Lambda sensor, 185 LEMENE project, 264 Leveled cost of energy (LCOE), 263 264 Life cycle assessment (LCA), 287 Limiting current sensor, 168 169, 191 Linear accelerator (LINAC), 61f Linear passive filters, 272 Local thermal equilibrium (LTE) approximation, 146

M Measuring electrodes, 173 Melts’ analysis, sensors for, 182 184 Metal air batteries derived from solidoxide metal air redox battery, 241 244 Metallic interconnectors, 30 32 ferritic stainless steels, 31 32 Metals and alloys, 104 105 Micro gas turbine (MGT), 261, 283 284 Minimum energy path (MEP), 8 Mixed conductive oxides, 110 Mixed ion-electron conductor (MIEC), 1 4 proton conduction in, 18 21 Mixed potential sensors (MPSs), 186 189 Mixed proton and electron conductors (MPECs), 11 13 Monte Carlo methodology, 140 141 Multielectrode amperometric sensor, 169, 199 200 Multifunctional sensors, 169

N Near-ambient pressure (NAP), 55 57, 59, 65 Nickel-based alloys, 31 Nickel-based cermet, 109 110 Niobates, 102 104 Norskov approach, 17

O One- and two-dimensional models, 139 140

298

Index

Open-circuit voltage (OCV), 138 139, 142, 177 178, 223 Orthoniobate, 103 104, 103f Orthotantalate, 103 104, 103f Oxidation resistance, 30 Oxygen anion migration, 4 10 Oxygen evolution reaction (OER), 14, 21 22 Oxygen gauges, 168 169 Oxygen reduction reaction (ORR), 1, 14, 21 22 Oxygen sensors, 178 Oxygen solid electrolyte coulometry (OSEC), 201 Oxygen transport, 1 2 Oxynitride glasses, 176

P Passivation, 30 Perceptrons, 274 Perovskite-based oxides, 1 general structural and electronic features, 2 10 oxygen anion migration, 4 10 mixed proton electron conductor for proton-conducting solid oxide fuel cells, 10 17 Ba-based perovskite oxides: stability versus hydration, 13 electron conduction and catalytic features at doped BaZrO3, 14 17 triple conducting oxides (TCOs), 17 22 electrocatalysis toward bifunctional oxygen evolution reaction/oxygen reduction reaction catalysts, 21 22 enhancing proton conduction in mixed ion-electron conductor materials, 18 21 Perovskite oxides, Ba-based, 13 Phosphates, 102 104 Platinum, 168 169, 173 Potenciodynamic and potentiostatic electrodeposition, 40 45 Potentiometric sensors, 177 189, 183f equilibrium potentiometric sensors (EPSs), 177 185, 180f

automotive application, sensors for, 185 humidity sensors, 182 hydrogen sensors, 182 isotope sensors, 181 melts’ analysis, sensors for, 182 184 operation principle, 177 180 reference electrodes, 180 181 mixed potential sensors (MPSs), 186 189 Power backup systems, 259 260 Power conditioning devices impacts, 271 273 “Production-to-consumption” distance, 256 Protective coatings, 33 36 Proton-conducting phase, 112 113 Proton-conducting solid oxide fuel cells, mixed proton electron conductor for, 10 17 Ba-based perovskite oxides, 13 electron conduction and catalytic features at doped BaZrO3, 14 17 Proton conduction in mixed ion-electron conductor materials, 18 21 Protonic-based ceramics for fuel cells and electrolyzers, 91 brownmillerite A2B2O4-based materials, 101 102 electrode materials, 104 115 air electrode material, 110 111 fuel electrode material, 104 110 mixed conductive oxides, 110 electrolyte materials, 94 104 BaCeO3 BaZrO3 mixed systems, 98 99 BaCeO3 perovskite-based materials, 94 97 BaZrO3, 97 98 SrZrO3, 99 100 perovskite-related material, 100 101 phosphates, niobates, and tantalates, 102 104 proton defect formation, 91 93 proton transport, 93 Protonic ceramic fuel cell (PCFC), 104, 109, 112 114

Index

Protonic defects, 91 92 Proton-mediated redox activity of iron oxide, 238 240 Pyrex seal, 173 174

R Rayleigh criterion, 62 64 Redox kinetics, 231 234 Reference electrode (RE), 172 173 Renewable energy sources (RES), 129, 253 254 Reversible SOC (rSOC) operation, 132 Reversible solid-oxide fuel cell (RSOFC), 227 228 improving performance of, 228 231 Ripple, 271 Round-trip efficiency (RTE), 223 224

S Scanning X-ray photoelectron microscopy (SPEM), 55 57 operating principle of, 59 67 Sealants, 173 177 glassy-ceramic sealants, 175 177 glassy sealants, 174 175 Sensing electrodes (SEs), 173 Sensors based on solid oxide electrolytes, 167 amperometric sensors, 189 201 brief history, 168 169 combined sensors, 203 205 coulometric sensors, 201 203 electrodes, 172 173 electrolytes, 170 172 potentiometric sensors, 177 189, 183f equilibrium potentiometric sensors (EPSs), 177 185, 180f mixed potential sensors (MPSs), 186 189 sealants, 173 177 glassy-ceramic sealants, 175 177 glassy sealants, 174 175 Serial repeating unit (SRU), 141 Single-phase mixed triple conducting electrode material, 113 115 Soft X-ray scanning photoemission microscope at the ESCA

299

microscopy beamline at Elettra, 57 67 ESCA microscopy, experimental setup developed at, 59 67 scanning X-ray photoelectron microscopy (SPEM), operating principle of, 59 67 X-ray photoelectron spectroscopy (XPS), operating principle of, 57 59 Solid oxide cells (SOCs), 130 131 Solid oxide electrolysis, multilevel modeling of, 123 cell/stack modeling, multidimensional approaches to, 134 141 one- and two-dimensional models, 139 140 three-dimensional models, 140 141 zero-dimensional models, 135 139 materials and micro-electrochemistry, 130 134 elementary mass-action kinetics, 132 133 equivalent circuit kinetics, 133 134 global kinetics, 131 132 kinetic models, 130 131 operation of solid oxide electrolyzer as a part, 156 158 solid oxide electrolyzer integration with thermal and electric sources, 158 161 theoretical background, 127 129 key performance indicators (KPIs), 127 129, 128t thermal management of solid oxide electrolyzer stacks, 145 151 of solid oxide electrolyzer through the use of heat pipes, 151 155 typical operating conditions, 141 145 Solid oxide electrolytes, 168 Solid oxide electrolyzer cell (SOEC) systems, 127, 130, 132, 145f, 147 148, 150 Solid oxide electrolyzers (SOEs), 126 127, 137, 141 142, 147, 161

300

Index

Solid oxide fuel cell (SOFC) systems, 1, 27, 31 32, 67 87, 105 106, 130, 136 137, 219 220, 251 benefits and limits, 251 255 short energy scenario background, 253 255 costs, 285 288 current applications, 255 266 auxiliary power units and propulsion, 258 259 combined heat (cooling) and power generation, 263 265 critical environment applications, demonstration for, 265 266 hybrid systems exploiting biogas/ biofuel production, 260 263 power backup systems, 259 260 power generation, 255 258 in situ SPEM characterization of SOFC anodic systems, 69 75 in situ SPEM studies on SC-SOFCs to SPEM characterization of selfdriven cells, 75 87 simulations of specific behavior, 280 285 distributed generation and system dynamics simulation matters, 282 283 gas leakage in solid oxide fuel cell system operation, 280 282 hybrid biofuel fed plants simulation approach, 283 285 system/performance degradation over time, 280 SPEM characterization of SC-SOFC in a NAP-cell, 83 87 system architecture, 266 276 ancillary devices, 266 267 automatic system optimization, control algorithms for, 273 276 blowers pumps reformer heat exchangers afterburner power converter(s), 267 271 power conditioning devices impacts, 271 273 Solid oxide based electrolyzer and fuel cells (SOEC/FCs), 11 12

Solid-oxide metal air redox battery (SOMARB), 217 advantages, 220 221 concept of, 219 220 metal air batteries derived from, 241 244 operated on different chemistries, 223 227 Fe-based chemistry, 223 226 metals-based chemistry, 226 227 performance improvement of SOIARB, 227 241 cycling degradation, 240 241 energy storage unit, improving performance of, 231 238 proton-mediated redox activity of iron oxide, 238 240 reversible solid-oxide fuel cell, improving performance of, 228 231 thermodynamics and kinetics of, 221 223 working principle of, 220f Stack single repeating unit (SRU), 146 Steam-to-carbon (S/C) ratio, 109 110 Stefan Maxwell model, 142 143 Strontium zirconate based materials, 99 100

T Tantalates, 102 104 Temperature-programmed reduction (TPR) test, 231 233 Thermal energy storage (TES), 160 Thermal expansion coefficient (TEC), 27 28 Thermal management of solid oxide electrolyzer stacks, 145 151 of solid oxide electrolyzer through the use of heat pipes, 151 155 Thoria-based electrolytes, 170, 183 Three-dimensional models, 140 141 Transition metal (TM) oxides, 1 2 Triethylamine (TEA), 188 Triple conducting oxides (TCOs), 17 22

Index

electrocatalysis toward bifunctional oxygen evolution reaction/oxygen reduction reaction catalysts, 21 22 enhancing proton conduction in mixed ion-electron conductor materials, 18 21 Triple-phase boundary (TPB), 1, 105 Triple points, 105 Tuneable energy X-ray beams, 59 62

U Ultrahigh vacuum (UHV), 55 57, 59 Undulator, 59 62

W Waste water treatment plants (WWTPs), 261 263

301

Water loop heat pump (WLHP), 264 Working electrodes, 173

X X-ray photoelectron spectroscopy (XPS), 55 57, 58f operating principle of, 57 59

Y Yttria-stabilized zirconia (YSZ), 170

Z Zero-dimensional models, 135 139 Zero-point energy, 5 Zirconia-based electrolyte, 183 Zirconia-based galvanic cell, 168 169