Hybrid Nanofluids for Convection Heat Transfer [1 ed.] 0128192801, 9780128192801

Table of contents :
Cover
Hybrid Nanofluids for Convection Heat Transfer
Copyright
Contents
List of contributors
Biography
1 History and introduction
1.1 History
1.1.1 Conventional methods to enhance heat transfer
1.1.2 Microscale additives in fluids
1.1.3 Nanoscale additives in fluids
1.1.4 Nanoscale particles and nanofluids
1.1.4.1 Properties
1.1.4.1.1 Optical properties
1.1.4.1.2 Antibacterial properties
1.1.4.1.3 Catalytic properties
1.2 Introduction
1.2.1 Fundamental of conduction
1.2.2 Fundamental of convection
1.2.3 Fundamental of radiation
1.2.4 Fundamental of viscosity
1.2.5 Fundamental of density
1.2.6 Fundamental of heat capacity
1.3 Nanofluid and hybrid nanofluid
1.3.1 Unique characteristics of hybrid nanofluid
1.3.1.1 Comparison of hybrid nanoparticles and conventional nanoparticles
1.3.2 Microscale heat transfer
1.3.3 Nanoscale heat transfer
1.3.3.1 Higher thermal conductivity of the particles than the base fluid
1.3.3.2 Formation of a solid layer at the interface surface
1.3.3.3 Electrical charge on particle surface
1.3.3.4 Brownian motion of the particles
1.3.3.5 Thermophoresis
1.3.3.6 Diffusiophoresis
1.3.3.7 Special characteristics of particle flow
1.3.3.8 Shape of the particle, distribution, size, and formation of the masses
1.3.3.9 Clustering of nanoparticles
1.3.3.10 Analysis of convection in nanofluids
1.3.3.10.1 Diffusion model
1.3.3.10.2 Particle migration effect
1.4 Conclusion
Nomenclature
References
2 Hybrid nanofluids preparation method
2.1 Introduction
2.2 Methods of nanoparticles synthesis
2.2.1 Bottom-up
2.2.1.1 Sol–gel method
2.2.1.1.1 The sol–gel process steps
2.2.1.1.1.1 Preparation of a homogenous solution
2.2.1.1.1.2 Formation of the sol
2.2.1.1.1.3 Formation of the gel
2.2.1.2 Chemical vapor deposition
2.2.1.2.1 Types of chemical vapor deposition methods
2.2.1.2.2 Thermal chemical vapor deposition
2.2.1.2.3 Metal organic chemical vapor deposition
2.2.1.2.4 Plasma-enhanced chemical vapor deposition
2.2.1.2.5 Atomic layer chemical vapor deposition
2.2.1.3 Hydrothermal
2.2.1.3.1 Types of hydrothermal methods
2.2.1.3.1.1 Methods based on the use of organic additives
2.2.1.3.1.2 Methods based on the use of mold
2.2.1.3.1.3 Substrate-based methods
2.2.1.3.1.4 Heating methods in hydrothermal method
2.2.2 Top-down
2.2.2.1 Nanolithography
2.2.2.1.1 Optical lithography
2.2.2.1.2 Electron beam nanolithography
2.2.2.1.3 Scanning probe microscope lithography
2.2.2.2 Milling process
2.2.2.2.1 Vibratory ball mill
2.2.2.2.2 Attritor ball mill
2.2.2.2.3 Tumber horizontal
2.2.2.2.3.1 Tumber horizontal ball mill
2.2.2.2.3.2 Tumber rod mill
2.2.2.2.4 Plantarry mill
2.3 Nanoparticles
2.3.1 Properties of nanoparticles
2.3.2 Effect of nanoparticles volume fraction
2.4 Choosing an appropriate base fluid
2.5 Nanoparticle combination
2.6 Hybrid nanofluid preparation
2.6.1 Single-step method
2.6.2 Two step method
2.6.2.1 Addition of surfactants
2.6.2.2 Nanofluid pH control
2.6.2.3 Ultrasonic vibration
2.7 Conclusions and future direction
References
3 Thermophysical and rheological properties of hybrid nanofluids
3.1 Thermal conductivity
3.1.1 Measurement techniques
3.1.2 Theory
3.1.3 Experimental results
3.2 Viscosity
3.2.1 Measurement techniques
3.2.2 Theory
3.2.3 Experimental results
3.3 Heat capacity
3.3.1 Measurement techniques
3.3.2 Theory
3.3.3 Experimental results
3.4 Density
3.4.1 Measurement techniques
3.4.2 Theory
3.4.3 Experimental results
3.5 Wetting
3.6 Comparison of unitary and hybrid nanofluids
3.7 Challenges and conclusions
References
4 Hybrid nanofluids as a heat transferring media
4.1 Introduction
4.2 Natural convection heat transfer
4.3 Forced convection heat transfer
4.3.1 Single-phase and two-phase forced convection heat transfer
4.3.1.1 Single-phase
4.3.1.2 Two-phase
4.4 Heat transfer in porous media
4.5 Theoretical studies and models for prediction of heat transfer
4.6 Concluding remarks
Nomenclature
Greek letters
Subscript
References
5 Performance effecting parameters of hybrid nanofluids
5.1 Introduction
5.2 Nanoparticle concentration
5.3 Basefluid
5.4 Temperature
5.5 Sonication time
5.6 Surfactant addition
5.7 Particle size
5.8 Brownian motion of nanoparticles
5.9 Particle shape
5.10 pH value
5.11 Clustering effect
5.12 Conclusion
References
6 Applications of hybrid nanofluids in different fields
6.1 Introduction
6.2 Main applications of hybrid nanofluids
6.2.1 Solar energy
6.2.2 Refrigeration and heating, ventilation, and air conditioning applications
6.2.3 Heat exchanger
6.2.4 Heat pipes
6.2.5 Coolant in machining and manufacturing
6.2.6 Electronic cooling
6.2.7 Automotive industry
6.2.8 Generator cooling
6.2.9 Transformer cooling
6.2.10 Nuclear system cooling
6.2.11 Biomedical
6.2.12 Space, Ships, and defense
6.3 Conclusions
Nomenclature
Abbreviations
Symbols
References
7 Barriers and challenges in hybrid nanofluids development and implementation
7.1 Stability of hybrid nanofluids
7.1.1 Stability enhancement procedures
7.2 Viscosity and thermal conductivity modeling techniques for hybrid nanofluids
7.2.1 Viscosity modeling techniques for hybrid nanofluids
7.2.2 Thermal conductivity modeling techniques for hybrid nanofluids
7.3 Nanoparticles dispersion in hybrid nanofluids
7.3.1 Pairs of nanoparticles
7.3.2 Hybrid nanocomposites
7.3.3 Other approaches
7.4 Pumping power studies and approach on hybrid nanofluids
7.4.1 Pumping power comparison for water based hybrid nanofluids: theoretical approach
7.4.1.1 Pumping power comparison for several water based hybrid nanofluids: a numerical approach
7.5 Selection of proper hybrid nanofluids
7.5.1 Selection of suitable pairs of nanomaterials or hybrid materials
7.5.2 Selection of base fluids
7.6 pH control of hybrid nanofluids
7.7 Conclusion and perspectives
Nomenclature
Abbreviations
Roman letters
Greek letters
Subscripts
References
Index
Back Cover

Citation preview

Hybrid Nanofluids for Convection Heat Transfer

Hybrid Nanofluids for Convection Heat Transfer

Edited by

Hafiz Muhammad Ali Mechanical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia

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: 978-0-12-819280-1 For Information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Brian Romer Acquisitions Editor: Graham Nisbet Editorial Project Manager: Sara Valentino Production Project Manager: Prasanna Kalyanaraman Cover Designer: Mark Rogers Typeset by MPS Limited, Chennai, India

Contents List of contributors ...................................................................................................ix Biography..................................................................................................................xi

CHAPTER 1 History and introduction ............................................... 1 1.1

1.2

1.3

1.4

Hemmat Esfe Mohammad, Saeed Esfandeh and Mohammad Hassan Kamyab History ............................................................................................1 1.1.1 Conventional methods to enhance heat transfer ................ 2 1.1.2 Microscale additives in fluids............................................. 2 1.1.3 Nanoscale additives in fluids.............................................. 3 1.1.4 Nanoscale particles and nanofluids .................................... 4 Introduction ....................................................................................9 1.2.1 Fundamental of conduction .............................................. 10 1.2.2 Fundamental of convection............................................... 11 1.2.3 Fundamental of radiation .................................................. 11 1.2.4 Fundamental of viscosity .................................................. 13 1.2.5 Fundamental of density..................................................... 14 1.2.6 Fundamental of heat capacity........................................... 14 Nanofluid and hybrid nanofluid...................................................15 1.3.1 Unique characteristics of hybrid nanofluid ...................... 18 1.3.2 Microscale heat transfer.................................................... 20 1.3.3 Nanoscale heat transfer..................................................... 22 Conclusion ....................................................................................40 Nomenclature............................................................................... 41 References.................................................................................... 43

CHAPTER 2 Hybrid nanofluids preparation method ...................... 49 2.1 2.2

2.3

2.4 2.5 2.6

Masoud Afrand and Ramin Ranjbarzadeh Introduction ..................................................................................49 Methods of nanoparticles synthesis .............................................50 2.2.1 Bottom-up.......................................................................... 50 2.2.2 Top-down .......................................................................... 64 Nanoparticles................................................................................75 2.3.1 Properties of nanoparticles................................................ 75 2.3.2 Effect of nanoparticles volume fraction ........................... 77 Choosing an appropriate base fluid .............................................78 Nanoparticle combination ............................................................83 Hybrid nanofluid preparation.......................................................83

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2.6.1 Single-step method............................................................ 83 2.6.2 Two step method............................................................... 85 2.7 Conclusions and future direction .................................................88 References.................................................................................... 91

CHAPTER 3 Thermophysical and rheological properties of hybrid nanofluids ...................................................... 101 Hatice Mercan 3.1 Thermal conductivity .................................................................101 3.1.1 Measurement techniques................................................. 103 3.1.2 Theory ............................................................................. 104 3.1.3 Experimental results........................................................ 113 3.2 Viscosity .....................................................................................117 3.2.1 Measurement techniques................................................. 117 3.2.2 Theory ............................................................................. 119 3.2.3 Experimental results........................................................ 123 3.3 Heat capacity ..............................................................................127 3.3.1 Measurement techniques................................................. 127 3.3.2 Theory ............................................................................. 128 3.3.3 Experimental results........................................................ 129 3.4 Density........................................................................................130 3.4.1 Measurement techniques................................................. 130 3.4.2 Theory ............................................................................. 131 3.4.3 Experimental results........................................................ 131 3.5 Wetting .......................................................................................132 3.6 Comparison of unitary and hybrid nanofluids...........................132 3.7 Challenges and conclusions .......................................................135 References.................................................................................. 136

CHAPTER 4 Hybrid nanofluids as a heat transferring media...... 143 4.1 4.2 4.3

4.4 4.5 4.6

Hamza Babar, Muhammad Usman Sajid and Hafiz Muhammad Ali Introduction ................................................................................143 Natural convection heat transfer ................................................145 Forced convection heat transfer.................................................158 4.3.1 Single-phase and two-phase forced convection heat transfer............................................................................. 163 Heat transfer in porous media....................................................166 Theoretical studies and models for prediction of heat transfer ........................................................................................167 Concluding remarks ...................................................................167

Contents

Nomenclature............................................................................. 170 Greek letters............................................................................... 171 Subscript .................................................................................... 171 References.................................................................................. 172

CHAPTER 5 Performance effecting parameters of hybrid nanofluids.................................................................. 179 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 5.10 5.11 5.12

Tayyab Raza Shah, Hasan Koten and Hafiz Muhammad Ali Introduction ................................................................................179 Nanoparticle concentration ........................................................180 Basefluid.....................................................................................184 Temperature................................................................................186 Sonication time...........................................................................187 Surfactant addition .....................................................................190 Particle size ................................................................................191 Brownian motion of nanoparticles.............................................194 Particle shape..............................................................................197 pH value .....................................................................................201 Clustering effect .........................................................................203 Conclusion ..................................................................................204 References.................................................................................. 205

CHAPTER 6 Applications of hybrid nanofluids in different fields.......................................................................... 215 Furqan Jamil and Hafiz Muhammad Ali 6.1 Introduction ................................................................................216 6.2 Main applications of hybrid nanofluids.....................................218 6.2.1 Solar energy .................................................................. 218 6.2.2 Refrigeration and heating, ventilation, and air conditioning applications .............................................. 223 6.2.3 Heat exchanger.............................................................. 224 6.2.4 Heat pipes...................................................................... 228 6.2.5 Coolant in machining and manufacturing .................... 229 6.2.6 Electronic cooling ......................................................... 234 6.2.7 Automotive industry ..................................................... 236 6.2.8 Generator cooling.......................................................... 238 6.2.9 Transformer cooling...................................................... 238 6.2.10 Nuclear system cooling................................................. 240 6.2.11 Biomedical .................................................................... 243 6.2.12 Space, Ships, and defense............................................. 245 6.3 Conclusions ................................................................................245

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Nomenclature............................................................................. 246 Abbreviations.........................................................................246 Symbols..................................................................................246 References.................................................................................. 246

CHAPTER 7 Barriers and challenges in hybrid nanofluids development and implementation ............................ 255 Alina Adriana Minea 7.1 Stability of hybrid nanofluids ....................................................256 7.1.1 Stability enhancement procedures .................................. 258 7.2 Viscosity and thermal conductivity modeling techniques for hybrid nanofluids........................................................................260 7.2.1 Viscosity modeling techniques for hybrid nanofluids ... 260 7.2.2 Thermal conductivity modeling techniques for hybrid nanofluids ........................................................................ 261 7.3 Nanoparticles dispersion in hybrid nanofluids ..........................261 7.3.1 Pairs of nanoparticles...................................................... 263 7.3.2 Hybrid nanocomposites................................................... 263 7.3.3 Other approaches............................................................. 264 7.4 Pumping power studies and approach on hybrid nanofluids ....265 7.4.1 Pumping power comparison for water based hybrid nanofluids: theoretical approach..................................... 266 7.5 Selection of proper hybrid nanofluids .......................................271 7.5.1 Selection of suitable pairs of nanomaterials or hybrid materials .......................................................................... 272 7.5.2 Selection of base fluids................................................... 272 7.6 pH control of hybrid nanofluids ................................................272 7.7 Conclusion and perspectives......................................................274 Nomenclature............................................................................. 274 Abbreviations.........................................................................274 Roman letters .........................................................................274 Greek letters...........................................................................275 Subscripts...............................................................................275 References.................................................................................. 275 Index ......................................................................................................................281

List of contributors Masoud Afrand Department of Mechanical Engineering, Islamic Azad University, Najafabad, Iran Hafiz Muhammad Ali Mechanical Engineering Department, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, Saudi Arabia Hamza Babar Mechanical Engineering Department, University of Engineering and Technology, Taxila, Pakistan Saeed Esfandeh Department of Mechanical Engineering, Imam Hossein University, College of Engineering, Tehran, Iran; Department of Mechanical Engineering, Jundishapur University of Technology, Dezful, Iran Furqan Jamil Mechanical Engineering Department, University of Engineering and Technology, Taxila, Pakistan Mohammad Hassan Kamyab Department of Mechanical Engineering, Imam Hossein University, College of Engineering, Tehran, Iran Hasan Koten Mechanical Engineering Department, Istanbul Medeniyet University, Istanbul, Turkey Hatice Mercan Mechatronics Engineering Department, Faculty of Mechanical Engineering, Yildiz Technical University, Istanbul, Turkey Alina Adriana Minea Technical University Gheorghe Asachi, Iasi, ¸ Romania Hemmat Esfe Mohammad Department of Mechanical Engineering, Imam Hossein University, College of Engineering, Tehran, Iran Ramin Ranjbarzadeh Department of Civil, Constructional and Environmental Engineering, Sapienza University of Rome, Rome, Italy Muhammad Usman Sajid Division of Sustainable Development (DSD), College of Science and Engineering (CSE), Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF), Education City, Doha, Qatar Tayyab Raza Shah Mechanical Engineering Department, University of Engineering and Technology, Taxila, Pakistan

ix

Biography Dr. Hafiz Muhammad Ali, currently working as an associate professor of Mechanical Engineering at King Fahd University of Petroleum and Minerals, Saudi Arabia, received his doctoral degree in mechanical engineering from School of Engineering and Materials Science, Queen Mary, University of London, United Kingdom, in 2011. He was a postdoc at Water and Energy Laboratory of University of California at Merced, United States, during 2015 16. He is a noted faculty member having thermal sciences, heat transfer, and solar energy as his major areas of interest. Over the span of several years, he supervised numerous undergraduate and postgraduate students and his work produced more than 100 papers featured in various reputed international journals. He also represented his institution and Pakistan at several international and national conferences as an invited speaker and delivered various keynote talks. His other research interests include electronics cooling, condensation, nanofluids, heat transfer devices, and thermal management. He is the recipient of the “Best Young Research Scholar Award” for 2017 in the Engineering category, conferred by Higher Education Commission of Pakistan at the 7th HEC Outstanding Research Award Ceremony. He also had the honor of receiving HEC’s Best Research Paper Award (2013/2014) and Research Productivity Award by Pakistan Council of Science and Technology (2016 17). Apart from his academic duties, he is actively involved with editorial duties at several international journals, notably Journal of Thermal Analysis and Calorimetry (Springer), International Journal of Thermofluids (Elsevier), Journal Thermal Science, and Journal of Mechanical Engineering.

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CHAPTER

History and introduction

1

Hemmat Esfe Mohammad1, Saeed Esfandeh1,2 and Mohammad Hassan Kamyab1 1

Department of Mechanical Engineering, Imam Hossein University, College of Engineering, Tehran, Iran 2 Department of Mechanical Engineering, Jundishapur University of Technology, Dezful, Iran

Chapter Outline 1.1 History ................................................................................................................ 1 1.1.1 Conventional methods to enhance heat transfer.....................................2 1.1.2 Microscale additives in fluids ..............................................................2 1.1.3 Nanoscale additives in fluids ...............................................................3 1.1.4 Nanoscale particles and nanofluids ......................................................4 1.2 Introduction ......................................................................................................... 9 1.2.1 Fundamental of conduction ...............................................................10 1.2.2 Fundamental of convection ...............................................................11 1.2.3 Fundamental of radiation ..................................................................11 1.2.4 Fundamental of viscosity...................................................................13 1.2.5 Fundamental of density.....................................................................14 1.2.6 Fundamental of heat capacity............................................................14 1.3 Nanofluid and hybrid nanofluid ........................................................................... 15 1.3.1 Unique characteristics of hybrid nanofluid..........................................18 1.3.2 Microscale heat transfer....................................................................20 1.3.3 Nanoscale heat transfer ....................................................................22 1.4 Conclusion ........................................................................................................ 40 Nomenclature ........................................................................................................... 41 References ............................................................................................................... 43

1.1 History The initial spark of heat transfer science can be attributed to Galileo Galilei [1] with the invention of the Galilean thermometer in the 16th century and Newton [2] by presenting Newton’s cooling law as the first heat transfer formula in the 18th century. Then we can refer to Fourier’s mathematical theory of heat transfer Hybrid Nanofluids for Convection Heat Transfer. DOI: https://doi.org/10.1016/B978-0-12-819280-1.00001-X © 2020 Elsevier Inc. All rights reserved.

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CHAPTER 1 History and introduction

in 1822 [2]. In fact, from the beginning of the 17th century through the middle of the 19th century, many of the basic concepts of heat transfer, such as heat, temperature, thermal energy, specific heat, latent heat, and kinetic energy, were defined, as well as the first and second rules of thermodynamics were introduced. Nevertheless, the history of modern heat transfer science dates back to the 1930s and is still ongoing [3]. The breadth and variety of subsystems of heat transfer science over the years has led to the division of this science into many specialized subdivisions, including the three main subsections of convection, radiation, and conduction heat transfer. Today, heat transfer is one of the important branches of study in many engineering disciplines, including mechanical engineering and chemistry. The application of heat transfer phenomena in various industries, including electronics, marine industries, and power plants, is also clearly visible. For example, in the design of boilers, condensers, evaporators, heat exchangers, and radiators, heat transfer analysis is necessary to calculate their optimized size and determine their type.

1.1.1 Conventional methods to enhance heat transfer In recent years, many studies have been conducted on methods to increase the heat transfer rate in equipment used in various industries, which can be divided into two general active and inactive methods. Among the active methods, it is possible to increase the thermal areas [4
6], the application of electric current or magnetic field [7
9] and fluid injection or suction [10
13], and on the other hand inactive methods, special geometry flat plates and additive or enriched fluids are used to achieve more heat exchange. According to the information in Table 1.1 on the thermal conductivity of different fluids, conventional heat transfer fluids such as water, ethylene glycol, and engine oils have poor thermal properties compared to metals and even metal oxides. This has led many scholars to think about how to improve the thermal properties of conventional fluids in heat transfer. Akoh [14] introduced the idea of a very fine magnetic particle dispersal in conventional heat transfer fluids, for the first time. Subsequently many studies have been conducted on the behavior and estimation of the thermal conductivity coefficient of the fluids with the solid particles dispersed therein, among which the theoretical and classical models of Maxwell [15] and Hamilton and Crosser [16] are the pioneers to estimate the thermal conductivity of solid
liquid mixtures. Indisputably the researchers in their theoretical models have not referred to the problems caused by the sedimentation of these solid particles. The erosion of the system and the increase in power required for pumping as well as increasing energy consumption were other unannounced points in the Akoh, Maxwell, and Hamilton
Crosser researches.

1.1.2 Microscale additives in fluids As stated, one of the ways to improve the heat transfer is to add particles with better thermal properties to fluids such as water and ethylene glycol. Ahuja [17]

1.1 History

Table 1.1 Thermal conductivity coefficient of some fluids and solids. Thermal conductivity (W/mK)

Material

0.613 0.289 0.145 0.141 0.252 237 40 401 148

Water Glycerol Engine oil Pump oil Ethylene glycol Aluminum Aluminum oxide Copper Silicon

measured the thermal and viscosity conductivity of 50 and 100 μm of polyester spherical particles dispersed in sodium chloride and glycerin. Based on the results, the thermal conductivity of the fluid was increased three times when compared with the base fluid. Choi and Tran [18], in the American National Argon Laboratory, introduced new fluids for industrial applications. Masuda et al. [19] used ultrafine aluminum oxide, silicon oxide, and titanium oxide to enhance the thermal properties of host fluids and to calculate their thermal conductivity and viscosity. They also observed the conglomeration of microparticles in the base fluid. These fluids with particles in millimeters or micrometers were never welcomed and commercially used, due to their low stability, rapid settling, obstruction and trapping of the flow path, rapid erosion of the pipe wall and equipments, and the sharp increase in pressure drop across the fluid flow.

1.1.3 Nanoscale additives in fluids According to the difficulties with the use of microparticles in fluids, researchers have sought to find a way to solve these problems. Choi et al. [20] first dispersed solid particles with nanosize (between 1 and 100 nm) in the fluids, and the resulting suspension was called nanofluid. According to their studies, nanosized particles formed more stable suspensions than suspensions containing microparticles, so that their low sedimentation rate would minimize the problem of obstruction of fluids paths. This research and its results can be considered as the starting point for using nanoparticles to improve the thermophysical properties of fluids. Masuda et al. [19] and Pak and Cho [21] are other pioneering scientists in this field. Metal nanoparticles (aluminum, silver, copper, nickel, etc.), metal oxides (aluminum oxide, copper oxides, iron oxide, silicon oxide, titanium oxide, etc.), or polymers such as graphene, carbon nanotubes, and the like are nanoparticles that could be used as nanoscale additives in fluids. Water, ethylene glycol, propylene

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CHAPTER 1 History and introduction

FIGURE 1.1 An image of the surface-enhanced effect of nanostructured materials.

glycol, oil, etc. could also be used as the base fluid. In general, the advantages of adding nanoparticles to a fluid compared with fluids containing microparticles and ordinary fluids are as follows:

• increasing the effective surface (Fig. 1.1) and fluid heat capacity; • increasing the effective thermal conductivity of the fluid; and • lowering the possibility of obstruction caused by the presence of nanoparticles in the fluid compared to microparticles.

1.1.4 Nanoscale particles and nanofluids In terms of structure, materials generally have three dimensions: length, width, and height. If at least one of these dimensions be in the scale of nanotechnology (1
100 nm), that material is called nanostructured. The reason of attraction for nanotechnology is that nanoscale materials have completely different properties than macroscale materials. All of the physical, chemical, and biological properties of the macroscopic scale may vary substantially in nanoscale. These properties are conductivity of heat and electricity, magnetic properties, optical properties, physical strength of materials, reactivity, and reaction speed [22,23]. Some other applications of nanofluids are in microelectronics, fuel cells, pharmaceutical processes, hybrid engines [24], internal combustion engines in cooling and heat cycles, chillers, heat exchangers, and lowering temperature of boilers exhaust gas from chimney [25]. Nanofluids increase the thermal conductivity and heat transfer coefficient relative to the base fluid [26]. It should be noted that in addition to thermal behavior, knowing the rheological behavior of the nanofluids in deciding whether they are practically suitable for convective heat transfer is very important [27]. Nanostructured materials are divided into different groups based on the number of nanosized dimensions that is known as free dimension. The free dimension refers to dimensions of a material with larger size than nanosize. Accordingly the material is divided into four parts nanoparticles, nanowires, thin films, and bulk nanomaterials.

1.1 History

The energy structures (alignment or band) of materials are length, width, and height directions. In other words, every three-dimensional object has three distinct energy structures along its three dimensions, the resultant of them defines total energy structure of material. Dimensions of nanoscale materials that are in nanoscale have quantum confinement. The quantum confinement means that the bands of energy become discrete due to the size limitations of the nanoscale, and more limitations led to more energy levels. Therefore one of the main differences between different types of nanostructured materials is the number of continuous energy bands and discrete energy levels in three dimensions, which results in a large variation in their properties. In fact, nanomaterials are divided into four categories of nanodimensional: zero-dimensional, one-dimensional, two-dimensional, three-dimensional, and bulky three-dimensional nanomaterials in terms of their nanosized dimensions, which can be produced by top-down or bottom-up method. Top-down and bottom-up methods (Fig. 1.2) are used to build all of the mentioned nanostructures and are not related to a specific group of nanostructures. Generally by changing the size of nanoparticles in the range of 1
100 nm, the surface-to-volume ratio and the energy balance distance will change. These two variables are the cause of many changes in properties and features. In other words, by controlling the size of the nanoparticles, they can control nanoparticles properties, which is very important.

FIGURE 1.2 Top-down and bottom-up production methods to make different types of nanostructures.

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1.1.4.1 Properties Properties and features of nanoparticles generally depend on their material and size. Certainly it is not possible to check all of these properties. As a solution, all the properties and features in nanoparticles can be explained by two factors that are increasing the surface-to-volume ratio and discretization of energy levels. Some of these properties are summarized briefly.

1.1.4.1.1 Optical properties In general, when the light hits an atom, it may be absorbed, reflected, or crossed. The excitation mechanism of electrons is different in atoms, in normal materials, and in nanoparticles, which is shown in Fig. 1.3. According to Fig. 1.3, the absorption of light in ordinary materials with continuous energy bands also occurs, and electrons are transferred from the valence band to the conduction band (however, here the thermal energy can also excite the electrons toward the conductive band). In the right side of Fig. 1.3, the absorption of light by nanoparticles is also shown. As shown in the figure, nanoparticles, such as atoms, have discrete energy levels. Hence, nanoparticles are called artificial atoms as well. Moreover, nanoparticles below 10 nm are called quantum dots. By changing the size of the nanoparticles, the distance between the energy levels changes. Smaller size of nanoparticles cause increase in distance between the energy levels and vice versa. This makes it possible to adjusting the gap between energy levels by changing the size of the nanoparticles to absorb certain waves at a specific frequency. For example, it is possible to adjust the dimensions of the specific nanoparticles to absorb waves of infrared, ultraviolet, radio, and so on. This feature in the military and electronics industries has a great application.

FIGURE 1.3 Electrons excitation, from the left to right, in atoms, in normal materials, and in nanoparticles, respectively. Nanoparticles act like atoms because they have discrete energy levels and are known as artificial atoms.

1.1 History

FIGURE 1.4 The effect of nanoparticles sizes on their color.

Different colors of the nanoparticles in Fig. 1.4 show different distance between their energy levels. In Fig. 1.4, the color of the nanosized gold and silver in different sizes is shown with image of their electron microscopy. In nature three elements of iron, nickel, cobalt, and the combination of other elements with these three elements have magnetic properties, and other elements or compounds alone have no magnetic properties. In the world, magnets and magnetic materials are widely in use from simple applications such as window lifters, car wipers, printers, scanners, electrical appliances in kitchens, and speakers to extremely complex applications such as generator motors, and so on. Only certain compounds can have magnetic properties and it counts as a limitation. One of the most interesting and highly functional properties in nanoscale dimension is that many of the materials that do not have magnetic properties in their normal size can have magnetic properties below a certain size in terms of nanotechnology. Aluminum oxide nanoparticles, gold, etc. are some notable examples. This will remove the above limitation, and considering the vast application of magnetic materials, new materials with improved properties can be produced. For instance, the magnetic properties of some nanoparticles are used in medicine and pharmaceutical applications as well. The reason for the creation of magnetic properties in materials that do not have magnetic properties in the ordinary dimension is the high increase in the surface and the creation of broken

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CHAPTER 1 History and introduction

FIGURE 1.5 A microscopic schematic of generating magnetic properties in nanoparticles.

bonds on the surface in the nanoscale. When a bond is established, two electrons in one orbital are placed in opposite directions. This arrangement leads to the neutralization of the magnetic fields around them. The electrons are charged particles, so with moving of charged particles, magnetic field will generate around them (Fig. 1.5). Furthermore the atoms in the electrons have two kinds of spin moves (around themselves) and orbits moves (around the nucleus) that cause magnetic field. The magnetic field is a vector quantity, and the direction is also of great importance. However, the broken or incomplete bond means that there is a single electron in orbital and there is no second electron to neutralize its magnetic field. On the nanoscale, since the percentage of the atoms on the surface and the broken bonds is very high, most materials can have magnetic properties.

1.1.4.1.2 Antibacterial properties Some nanoparticles such as silver and gold have antimicrobial or antibacterial properties, which mean that germs cannot grow on them. These particles are commonly used in cosmetics, hygiene, textiles, and so on. Its uses include the creation of hands-free cleansing gels, use in soaps and shampoos, use in clothing, use in manufacture of antimicrobial clothes and medical equipment, etc. Some nanoparticles, such as zinc oxide or titanium oxide, have photocatalytic properties. These nanoparticles are semiconductor and have an energy gap. These materials are usually used to purify water and pollutants. When the light is exposed to these particles, these electrons are excited and move toward conduction band. There, the electron is transferred to the pollutant and it is destroyed. The term photocatalyst is said to materials that activate their catalytic properties with light exposure.

1.1.4.1.3 Catalytic properties The catalyst is a material that changes the chemical reaction (increase or decrease) but does not participate in the chemical reaction. A factor that influences the quality and performance of catalysts is a variable called a specific area.

1.2 Introduction

FIGURE 1.6 Nanoparticles as catalysts and chemical reactions on them.

The larger the catalyst area, the better its catalytic properties. The specific area of a catalyst is obtained using Eq. (1.1): S5

A ρV

(1.1)

This quantity is usually reported in units of m2/g and its value for commercial catalysts is between 100 and 400 m2/g. The 100 m2/g means that 1 g of this material is 100 m2. Nanoparticles can also be used as catalysts due to their high surface. However, the properties of the catalyst, as well as magnetic properties, occur in certain dimensions. In other words, nanoparticles typically have the properties of catalysts, with a specific surface area between 100 and 400 m2/g. Therefore among the nanoparticles with equal volume, nanoparticles of higher surface exhibit better catalytic properties. An example of nanoparticles acting as a catalyst is shown in Fig. 1.6, with different materials placed on their surface and chemical reactions are carried out.

1.2 Introduction In recent years, many studies have also been carried out on nanofluids in a variety of contexts such as thermal conductivity [28
30], forced convection heat transfer [31
34], natural convection heat transfer [35
37], combined convection [38], boiling heat transfer [39], heat exchangers [40], flat plat solar collectors [41], car radiators [42], sliding mechanisms such as bearings [43], electricity [44], and

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cooling electronic devices [45]. Studies have also been carried out on various properties of nanofluids such as viscosity [46
48]. Considering the significant properties of nanoparticles, nanofluids can be considered as one of the most suitable and effective choices in heat transfer. Small particles in the nanofluid reduce corrosion, pressure drop, etc. and make the fluid more stable in comparison to micro or larger particles. The high ability of nanoparticles to influence the thermophysical properties of fluids is one of the most important reasons for researchers and craftsmen to use these materials in various industries and applications. Growth of thermal conductivity, the high heat transfer in a phase, and the high critical thermal flux, can be considered as the main reasons for the researchers to welcome the use of nanofluids.

1.2.1 Fundamental of conduction Heat transfer by conduction is the dominant mechanism of heat transfer in solids. When the body heats up, the average speed of its molecules increases rapidly. High-energy molecules encounter adjacent molecules and force them to move, in this way heat energy is transmitted in solids. Of course, thermal conductivity also occurs in liquids and gases, but due to differences in molecular structure, conductivity in solids is greater than fluids and in liquids is more than gases. In other words, conduction heat transfer is not the dominant mechanism of heat transfer in liquids and gases, although it is an effective parameter in the heat transfer of fluids. The amount of heat transferred from an object by conduction method depends on the following factors: 1. Difference between hot and cold surface temperature The difference in temperature is the cause of the heat transfer, so the higher the temperature difference gives the higher the heat transfer. 2. Cross section of body Obviously the larger the surface, the more molecules that transmit the heat will be more. 3. Thickness of the body The conductivity of the heat has an inverse relationship with the thickness of the object between the hot surface and the cold surface. This means that the lower the thickness of the body, the more heat conduction will be. 4. Thermal conductivity capability (K) All materials cannot conduct the heat with the same intensity. The relationship of the heat transfer rate with temperature difference, surface, length, and physical properties of the solid (thermal conductivity coefficient) is calculated as follows (Eq. 1.2): q_ 5

Q_ dT 52k A dx

(1.2)

1.2 Introduction

where Q_ is the heat transfer rate and A is the cross section. The coefficient k is known as the heat conduction coefficient and is the physical property of any material. Metals are stronger conductors (higher heat conduction coefficient) than fluids and it is the reason of fabrication of nanofluids in recent years.

1.2.2 Fundamental of convection Convection heat transfer takes place if a fluid moves over a solid surface or in the vicinity of it, given that there is a difference in temperature between the fluid and the solid surface. In fact, the convective heat transfer is a kind of energy transfer between a solid surface and the moving fluid in its vicinity, which combines the effects of conductivity and fluid motion. The main and fundamental relationship between heat transfer in this way is the Newton’s cooling law, which is expressed as follows (Eq. 1.3): qv 5 hðTs 2 TN Þ

(1.3)

where qv is the flux of heat transfer, h is the heat transfer coefficient, Ts is the ambient temperature (fluid), and TN is the solid surface temperature. In addition to convention different heat transfer methods, boiling heat transfer is also one of the methods of heat transfer. Since boiling heat transfer is accompanied by fluid movement, it is classified as a type of convection heat transfer but has its own specific characteristics. In boiling (and condensation), a high heat transfer rate can be obtained from a low temperature difference. The latent heat of evaporation, surface tension, and density difference of the two phases are the effective parameters in the boiling process. Due to the effects of buoyancy force and latent heat evaporation, the boiling heat transfer coefficients are far greater than the values for convection without phase change. Adding nanoparticles to the base fluid can change many of the above parameters based on the concentration and characteristics of the nanoparticle, such as size, shape, and chemical coating of the particle, compared with boiling of pure fluid.

1.2.3 Fundamental of radiation In general, the thermal heat transfer which is carried out by electromagnetic waves is called radiation. Since these waves are transmitted at the speed of light, so the energy transfer rate in this case equals the speed of light. After nanofluids appeared in the scientific community, the strong absorption behavior of nanofluids, especially in the solar spectrum, was discussed. It is a different concept of using the small absorption capacity of small particles in the fluid flow. Fig. 1.7 shows the structure of an electromagnetic wave. At first time, concept of energy transfer through electromagnetic waves was introduced by Scottish scientist James Clerk Maxwell. He showed that energy transmission occurs at light speed. Usually electromagnetic waves are classified

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CHAPTER 1 History and introduction

FIGURE 1.7 Structure of an electromagnetic wave.

based on their frequency and wavelength. The relationship between wavelength and frequency is as follows (Eq. 1.4): λ5

c ν

(1.4)

where λ and ν are wavelength and frequency, respectively. Moreover, c shows the speed of light in the vacuum. The above equation proves that wavelength and frequency have a tradeoff. In fact, if one of them increases, the other one decreases. The speed of light varies in different environments. Consequently to obtain the speed of light in an environment other than the vacuum, Eq. (1.5) is used. c5

c0 n

(1.5)

where n is the environmental refractive index in which we want to find the speed of light. For air, this coefficient is approximately equal to 1 and for water equal to 1.5. It should be noted that the frequency of an electromagnetic wave depends only on its source of emission and is not related to the atmosphere in which the wave is released. At the beginning of the 20th century, Einstein presented a new theory of the propagation of radiated waves. Based on this theory, energy transfer is the transfer of energy packs, called photons. For each of these packages, you can define a frequency equal to ν. With regard to the frequency assigned to them, the energy of each of these packets is equal to the following value (Eq. 1.6): e5h3ν 5

hc λ

(1.6)

where h has a constant value, equal to 6.626176 3 10234 and is called Planck’s constant. Note that in this assumption, the values of c and h are constant numbers. Hence, it can be said that the energy of the packs, or the photons, depends only on their wavelength. From the above, it can be seen that the lower wavelength

1.2 Introduction

FIGURE 1.8 Wavelengths of different energy spectra.

means more photon energy. For example, X-rays or gamma rays have very low wavelengths while they have high energy and can be very destructive. Fig. 1.8 shows a spectrum of different wavelengths. As it can be seen, a wavelength can be a micrometer variable. It is interesting to know that the cosmic waves have the shortest wavelengths, whereas electric waves have the longest wavelengths. The main reason of heat transfer through radiation is by rotational and vibrational movements of molecules, atoms, and electrons. In fact, the temperature is the result of these movements. Hence, increasing the temperature increases the radiation heat transfer rate. The concept we know as the “light” is, in fact, the visible part of the electromagnetic spectrum. Fig. 1.8 shows that the optical wavelength is a subset of the thermal wavelength. Radiation heat transfer is a volumetric phenomenon. Of course, for matte objects such as metals, the radiation is superficial. Note that the radiant properties of a surface can be introduced by covering it with new layers. One of the ways to improve the properties of fluids in the radiative base systems is to improve the absorption properties of fluids using nanoparticles. Researchers have done extensive research on the use of nanoparticles in fluids to improve the absorption coefficient of surfaces in equipments such as solar collectors and so on.

1.2.4 Fundamental of viscosity Viscosity is the resistance of a fluid to the shear stress or the friction resistance of a liquid or gas against flux or slippage of the liquid layers. Viscosity measurements are performed to determine the quality and efficiency of a product related

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to fluid science. Any researcher who is in some way involved in the determination of flow characteristics with the aim of research or development, quality control, or fluid transfer, to analyze the properties of fluids in the performance of a product, it is necessary to measure the viscosity parameter. The viscosity of a fluid reveals some of the rheological relationships of a fluid. In fact, rheological relationships (related to the flow and reformation of an element) provide a good understanding of the fluid flow for the researchers to better understand fluid behavior and, if necessary, implement their own changes. For example, to understand the behavior of the data and to be aware of the Newtonian or non-Newtonian state of the fluids, usually the shear stress curves are studied in terms of shear rates at different temperatures. The existence of the power unequal with 1 (n , 1) in the equation in the general format presented in Eq. (1.7) indicates the non-Newtonian behavior of the fluid. Eq. (1.8) also shows the viscosity of non-Newtonian fluids, also known as apparent viscosity. In contrast to the power with a value of one (n 5 1) in Eq. (1.7), it shows that the fluid is Newtonian. τ 5 mγ_ n

(1.7)

μ 5 mγ_ n21

(1.8)

In Newtonian fluids, fluid viscosity is not a function of a shear rate and its amount does not change. However, in non-Newtonian fluids, viscosity is a function of the shear rate. Fluids in which the viscosity decreases with increasing shear rate are quasiplastics and fluids, in which viscosity increases with the increase in the shear rate, are called dilatant fluids [49].

1.2.5 Fundamental of density The density is defined as mass in volume unit, which is represented by the abbreviation ρ and is obtained from the following equation (Eq. 1.9): ρ5

m V

(1.9)

where ρ is the material density, m is the mass of the object, and V is the volume occupied by that material. In fact, the density indicates how much the mass of an element is condensed. For example, Plumbum is a dense material, since its mass is denser in a smaller volume while the density of the air is very low. Measuring and controlling the density of fluids can be critical in industrial processes. Density measurement provides useful information about compounds, chemical concentration, or suspended solids in the liquid.

1.2.6 Fundamental of heat capacity The amount of heat required for 1 degree temperature enhancement is known as heat capacity. The higher the amount of material, the more heat is required to

1.3 Nanofluid and hybrid nanofluid

increase its temperature (mass dependent). To have a mass-independent criterion for heat capacity, specific heat capacity is introduced. q 5 mCΔT

(1.10)

where C is the heat capacity, q is the amount of heat exchanged, m is the mass of the object, and ΔT is the difference in temperature.

1.3 Nanofluid and hybrid nanofluid Hybrid nanofluid is a very new type of nanofluids that contains two or more various nanoparticles. Turcu et al. is one of the first researchers who have begun studies on hybrid nanoparticles [50]. But the main step in the way of introducing hybrid nanofluids taken by Hemmat Esfe research group [51
53]. Also they worked on a new field about controlling the viscosity of hybrid nanofluids in comparison to pure base fluids [54
56]. The use of hybrid nanofluids is aimed at simultaneously using the physical and chemical properties of two or more different types of nanoparticles, while improving fluid properties, such as water. Studies show the growth of thermophysical and rheological properties of hybrid nanofluids compared to conventional nanofluids [57,58]. The composition of the nanoparticles used to make the hybrid nanofluids can be divided into three different categories, depending on their type: 1. metal compounds such as Al2O3/Cu, Al2O3/Ni, MgO/Fe, and Al/CNT; 2. ceramic compounds such as Al2O3/Cu, Al2O3/Ni, MgO/Fe, and Al/CNT; and 3. polymer compounds such as polymer/CNT and polymer/TiO2. Obviously the issue of choosing the right combination of nanoparticles and their relative proportions has a significant effect on the efficiency and enhancement of the thermophysical properties of nanoparticles, and this issue can be considered as one of the considerations that need to be studied. In composite of results of many studies, the results of some studies show a decline in the thermal properties of hybrid nanofluids compared to conventional ones [59] that could be because of the following reasons: 1. 2. 3. 4. 5.

noncompatibility of the used nanoparticles with each other; the size of the used nanoparticles; base fluid type; fluid temperature and working temperature of fluid; and stability.

Providing a stable nanofluid is a necessary condition for optimizing nanofluid properties. The accumulation of nanoparticles and their agglomeration increases the probability of sedimentation and thus reduces the stability. The rate of

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sedimentation of spherical particles in static fluid can be obtained from the Stokes rule: v5

2R2 ðρ 2 ρ1 Þg 9μ p

(1.11)

Eq. (1.11) comes from balancing the forces of gravity, buoyancy, and drag, which act on particles. According to this law, the sedimentation rate of particles decreases with decreasing the particle size. When the particle size reaches a critical radius (Rc), no sedimentation will occur due to the Brownian motion of the particles. Despite the fact that particles with a radius below the critical radius will not be sediment, smaller particles will have a higher energy level and more likely to accumulate. The nanofluid stability means that the nanoparticles do not accumulate and sediment at a considerable rate, and thus the concentration of floating nanoparticles is constant. According to the Derjaguin
Landau
Verwey
Overbee theory, the stability of nanoparticles in a fluid is calculated from the sum of attraction and repulsion forces. In general, there are four intermolecular forces between the particles, the attraction forces between the particles are 1. van der Waals forces and 2. magnetic bipolar forces while the particles be magnetic. The repulsive forces between the particles are due to electrostatic repulsive forces of the surface of nanoparticles coated with electric charge, as well as the steric forces of the surface of nanoparticles coated with polymers or surfactants. If the repulsive force of particles overcomes attraction force, the nanofluid is in a steady state; otherwise, the two particles will collide and stick to each other. Therefore for stable nanofluids, repulsive forces must prevail between the particles. As stated, fundamental mechanisms that are effective on the stability of colloids are divided into two groups based on the repulsion types: steric repulsion and electrostatic repulsion. In Fig. 1.9, a schematic representation of these two types of repulsion is presented.

FIGURE 1.9 Steric repulsion and electrostatic repulsion.

1.3 Nanofluid and hybrid nanofluid

Stability is one of the critical factors determining the performance of hybrid nanoparticles. The lack of stability of hybrid nanoparticles can greatly affect the performance of these nanofluids. Researchers use various methods to control the stability. Some of these methods are as follows: 1. Surfactant agents Adding active surfactant in a nanofluid is a simple and cost-effective way to increase nanofluid stability. Surface-active agents greatly affect the system surface characteristic. These materials contain a hydrophilic polar head and a hydrophobic head (usually a hydrocarbon chain). Surface-active agents are classified into four categories based on the hydrophilic head composition: a. a nonion that the charged group does not exist in the hydrophilic polar head; b. an anion with the negative charged group; c. a cation with positive charged group; and d. an amphoteric that the hydrophilic head can have positive or negative charge. To select the appropriate surface-active agent, it should be noted that whether the fluid is a polar base, the surfactant with the hydrophilic head is suitable and otherwise the surface-active materials that are soluble in oil. It should be noted that excessive presence of these materials in the nanofluid may change the properties of the nanofluid and affect the transfer of mass and heat process. The major surfactants used by the researchers are sodium dodecyl sulfate, sodium dodecyl benzene sulfate, cetyl trimethyl ammonium bromide, oleic acid, dodecyl trimethyl ammonium bromide, and polyvinyl pyrrolidone [60]. Although the use of surfactants is one of the common ways to improve the stability of nanofluid, adding these materials to the nanofluid can cause problems such as foaming and reducing the thermal conductivity of the nanofluid. Also because of the destruction of the bond between the surfactant and the nanoparticle at temperatures above 60 C, the stability of nanofluid is eliminated. 2. The procedure of producing nanoparticles (single-stage or two-stage) To prevent the accumulation and agglomeration of nanoparticles within the fluid, Eastman et al. [61] initially invented a one-step method for the production of copper-ethylene glycol nanofluid. Using this method, nanoparticles containing metal nanoparticles were prepared using direct evaporation method. During a one-stage method, the metal container under vacuum conditions is evaporated and the density of the nanoparticle agglomeration reaches its minimum. It should be noted that low vapor pressure is one of the disadvantages of this process; however, various single-step chemical methods have been developed for the preparation of nanofluids, including the recovery of metal salts and the preparation of their suspensions in different solvents for the preparation of metals nanofluids. The main advantage of the one-stage method is the very good control over the

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size and distribution of particle size. The disadvantages of this method are the impossibility of producing nanofluid on a large scale and also its high production costs. In addition, in this method, some of the reactants remain in the nanofluid, which are difficult to separate and reduce their concentration in the fluid because of the stability of the suspension. On the other hand in two-step process, nanoparticles, nanotubes, nanofibers, or other nanomaterials that are supposed to be dispersed in the fluid as dry powders. Methods such as magnetic vibrators, ultrasonic vibrations, homogeneous shear mixes, or surfactants are recommended to minimize the formation of accumulated nanoparticles and to improve dispersing nanoparticles in the fluid. The two-stage method is suitable for metal oxide deionized in water, but not good enough for nanofluids containing heavy metal nanoparticles. This method has many economic benefits; for example, one of the advantages is the ability to produce nanopowders at the industrial and large scales. Important issues and penalties in the production of nanoparticles by two-stage method are the stability of the suspension and accumulation of nanoparticles and their agglomeration. Surfactants are usually prevented from accumulation of nanoparticles; however, there are concerns about the performance of surfactant at high-temperature that should be taken into account in high-temperature applications.

1.3.1 Unique characteristics of hybrid nanofluid Fluids that simultaneously host two types of nanoparticles are called hybrid nanofluids. One of the reasons why researchers have been attracted to the use and study of this kind of nanofluids can be the further improvement in the thermal and thermophysical properties of the hybrid nanofluids compared to conventional and traditional fluids and nanofluids also contain single nanoparticles. In general, the materials used for metal base nanocomposites, ceramic base and carbon base are as follows: 1. Ag (silver), Al (alumina), Au (gold), Cu (copper), Fe (iron), nanodiamond (ND), Ni (nickel), and Mg (magnesium); 2. Al2O3, Fe2O3, Fe3O4, SiC, and TiO2; and 3. SWCNTs, MWCNT, and graphite (G).

1.3.1.1 Comparison of hybrid nanoparticles and conventional nanoparticles Normal nanofluids, although have the desired thermophysical properties, in some cases are unable to provide all the characteristics and thermophysical properties of the equipment and industries as working fluids. In fact, it is sometimes necessary to inject the properties of two or more nanoparticles simultaneously into the host fluid such as conventional fluids, or motor and other industrial oils, so that the base fluid simultaneously benefits from the properties of all the added

1.3 Nanofluid and hybrid nanofluid

nanoparticles. In some cases, in addition to improving thermophysical properties, this will improve the cost-effectiveness of nanofluid production as well. Each nanoparticle has its own useful properties. For example, metal oxide nanoparticles such as aluminum oxide, which after suspension in the host fluid, show a remarkable and very beneficial chemical stability and diffusion, is not an attractive option in improving thermal properties such as thermal conductivity. On the other hand, metal nanoparticles such as aluminum, copper, and silver improve the thermal conductivity considerably, but they are not a good option in achieving a stable nanofluid. Thus by combining metal nanoparticles with metal oxide nanoparticles and ceramic nanoparticles, a stable solution can be obtained, while having improved thermal properties. As stated before the combination of nanoparticles and the production of hybrid nanofluids is not always a good option for improving the thermal properties of nanofluids. For example, Jana et al. [59] studied the effect of simultaneously adding Cu-CNT and Au-CNT nanoparticles to the host water fluid, which according to their results showed that the heat transfer conduction of conventional nanofluids was higher than the heat transfer conduction of the produced hybrid nanofluids. They predicted the following reasons for this result: 1. The inappropriateness and lack of interaction of the two types of nanoparticles with each other and, in fact, the disparity in their chemical behavior with each other. 2. Adding nanoparticles of carbon nanotubes will increase the growth rate of metallic nanoparticles agglomeration, which will have a negative effect on the thermal conductivity of the nanofluid. 3. Carbon nanotubes are less tendency to follow the natural flow of heat transfer, so adding them to metal nanoparticles may reduce the natural displacement of metal nanoparticles. In another study, Madhesh and Kalaiselvam [62] studied the effect of adding TiO2-Cu nanoparticles simultaneously in the base water fluid, and according to the results of the experiments, they were faced with improving the thermal properties of the prepared nanofluid. They explained the reason for this increase and improvement in the thermal properties of the copper nanoparticles as a nanolayer on the surface of the titanium oxide nanoparticles which produces a better and stronger thermal network between the nanoparticles that are combined with the host fluid layers. This will further improve the thermal properties of nanofluids. As stated, extensive research has been done to compare the thermal properties of hybrid nanoparticles with nanofluids containing single nanoparticles and traditional heat transfer fluids. In many of these studies, researchers have pointed to improvements in the thermal properties of hybrid nanofluids. For example, Sundar et al. [63] compared the water-based hybrid nanofluid containing NDFe3O4 nanoparticles with thermal properties of water base containing Fe3O4. The results showed the increase of about 15% of the thermal conductivity of the hybrid nanofluid in comparison to the thermal conductivity of the water.

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The increase of 10% of the normal thermal conductivity of the normal nanofluid in comparison to the water was another result. However, in another review of the thermophysical properties of nanoparticles, which is the viscosity, Sundar et al. [64] achieved interesting results. According to the results, the viscosity of the hybrid nanoparticles increased compared with conventional nanoparticles and ordinary fluids, such as water, ethylene glycol, and the like. Moreover, the apparent growth of the heat transfer coefficient and also the frictional factor growth for hybrid nanofluids were other observations of Sundar et al. [64], which are positive and negative parameters, respectively. It should be pointed out that improving the parameters of heat transfer conduction and convection depends on various parameters such as the size of the nanoparticles, the stability, the base fluid type, and the operating temperature of the fluid and it is generally not possible to use hybrid nanofluids as the sole factor for improving thermal properties. The effect of some of these parameters on improving the stability and thermal properties will be discussed in the next section.

1.3.2 Microscale heat transfer The flow of fluid inside the channels exists in many natural and man-made systems. Heat and mass transfer occurs in the channels’ walls of human body such as the brain, lung, kidney and also in engineering instruments such as heat exchangers, atomic reactors, and so on. Microchannels are used in a variety of devices with single-phase liquid flow. The development of microelectromechanical devices requires miniaturized heat exchangers. For example, cooling the mirrors used in high-power laser systems, require cooling systems that cover very small surfaces. Advances in genetic engineering and biomedical engineering require precise control of the transfer of heat and fluid in channels with micrometer dimensions. An appropriate understanding of fluid flow and heat transfer in these microscale systems is needed to design and exploit them. The use of smaller-sized channels, although having a higher pressure drop, can increase heat transfer for temperature controlling goals such as transmitting and carrying live and coarse biological molecules that need for appropriate storage conditions [65]. Over the past two decades, extensive studies have been carried out on microchannels due to their ability to remove excessive heat from small surfaces. A microchannel consists of a plurality of parallel channels in the diameter of a microscope with a diameter of 10
1000 μm. The cooling fluid passing through these channels, transfers the heat from the hot surface (Fig. 1.10). Laboratory studies have shown that the microchannel has several superior properties compared to conventional heat transfer devices, including the ability to generate a very high heat transfer coefficient, very small size, and requiring a low amount of coolant fluid [66]. As it has been stated, the phenomenon of flow and heat transfer in micro and nanodimensions during the past two decades has attracted considerable attention and due to its importance in small equipments, a branch of computational fluid

1.3 Nanofluid and hybrid nanofluid

FIGURE 1.10 An outline of a microchannel.

dynamics is allocated to microflows and nanoflows. This is due to the remarkable development of the concept of microelectromechanical systems (systems with a characteristic length less than 1 mm and more than 1 μm with mechanical and electrical parts). The main advantages of microstructures are greater chemical achievement, lower consumption, higher sensitivity, better operating time and, most importantly, better performance, and higher efficiency, which cannot be achieved by the large-scale counterparts of these devices. These small devices are often used as sensors for pressure, temperature, mass flow rate, velocity, sound, and accelerometers for vertical and horizontal movement as well as simple parts of the heat engine and microwave heating pump. Given that the geometric dimensions of these systems are within the range of intermolecular distances, the governing equations of fluid flow is different from the ordinary governing equations, and fluid behavior depends strongly on the scale of geometry. In addition, in the dimensions of microeffects such as dilution, compressibility, viscosity diffusion, friction, intermolecular forces, and other nonconventional phenomena are especially important. By decreasing the geometric flow dimensions, the assumption of the fluid continuity is obscured, and continuous models such as the Navier
Stokes and Fourier equations are not established. Therefore the performance of the basic components of microelectromechanical devices such as micronozzles, valves, ball bearing, motors, and micropumps cannot be analyzed by using the abovementioned models and also by using of no slip and no temperature jump boundary condition on walls that are in larger scale geometries. The phenomena such as no slip condition and jumping of temperature on solid surfaces, nonlinear changes in density over the microchannel, and the phenomenon of thermal creeping in microflows are among the outstanding phenomena in small-dimensional flows, and conventional numerical solutions in fluid dynamics are unable to model them. In addition, the difficulty in providing laboratory environments and their cost-effectiveness has limited the use of empirical methods to consider such phenomena. Hence, in recent years, simulation of flow and heat

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transfer in micro and in different flow regimes has been carried out using numerical methods such as direct simulation using Monte Carlo method, molecular dynamical method, and direct integration method of Boltzmann equation. But it should be considered that the computational cost of Monte Carlo methods and molecular dynamics (MD) is very high, and because of the difficulty of the integration process in the Boltzmann equation, the use of such methods in all microflow regimes is not feasible. To clarify the subject, it is worth mentioning that in the microscale, the Knudsen number as a criterion for the determination of flow regimes, that is the ratio of the mean free path of molecules, λ—the free path of gas molecules before collision with each other or to the solid wall—to geometric characteristic of H. For Knudsen numbers greater than 0.01, slipping phenomena and temperature jump occur on the walls, and using the Navier
Stokes
Fourier equations with common boundary conditions is not allowed. Hence, different slip and jump models for solving these equations in the slip regime and simulation of the abovementioned phenomena are presented. However, with the increase in the number of Knudsen up to the amount of flow in the transient regime (0.1 , Kn , 10), the condition of continuity for the fluid cannot be considered. On the other hand, in free molecular streams whose geometric dimensions are smaller than the mean molecular collision distance (Kn . 10), molecular methods such as MD and direct Monte Carlo method are used as a powerful tool for the simulation of microorganisms. However, in the transition region, the cost of computing these methods is very high and in practice they are not very efficient.

1.3.3 Nanoscale heat transfer As stated, nanofluids are a new form of improvement in heat transfer that are produced by suspending nanoscale metal and nonmetallic particles in commonly used fluids in heat transfer. These particles are dispersed by Brownian motion, and when there is no flow of fluid, nanoparticles disperse through the balance between buoyancy and thermal turbulence [67]. Naturally the nanofluid is a multicomponent fluid, even if the dispersed particles are very small. In multicomponent mixtures such as nanofluid flow, three basic movements such as sedimentation, shear movements, and wave motions may be available. It is difficult to provide a theoretical formulation that can predict multicomponent material flow, and the result of such an investigation may not be applicable to increasing the heat transfer rate in practical applications of nanofluid [67]. Keblinski et al. [68] presented his theory about the possible mechanism of nanofluid heat transfer and stated that the clustering of nanoscale particles, surface absorption, and Brownian motion of particles would be the main reasons for increasing heat transfer by nanofluid. Table 1.2 also highlights some of the advantages of nanoparticles on microparticles.

1.3 Nanofluid and hybrid nanofluid

Table 1.2 Comparison of microparticles and nanoparticles. Examined parameters

Microparticles

Nanoparticles

Stability Surface-to-volume ratio

Sedimentation 1

Thermal conductivity coefficient (in a given volume fraction) Blocking the path in the microchannel Corrosion Required pumping power

Low

Stable (too long) Thousands of times larger than particles in the microscope High

Yes

No

Yes High

No Low

In the following, the reasons of superiority of nanofluid in comparison to conventional fluids is stated and explained.

• high thermal conductivity of particles in comparison with the base fluid; • high variations in the thermophysical properties of the fluid at the • •

solid
liquid interface and the formation of a solid layer at the interface surface; movement of Brownian particles; and formation of masses and chains that create high-conduction pathways in nanofluids or contribute to the development of these pathways.

1.3.3.1 Higher thermal conductivity of the particles than the base fluid The thermal conductivity of solid particles is generally higher than the base fluid. According to the theory of mixtures and based on the experiments, adding minor values of nanoparticles has big effect on thermal properties improvement. This thermal properties improvement may affect different physical and chemical properties of various nanoparticles, but the positive effect of adding nanoparticle is undeniable for all cases according to the literature.

1.3.3.2 Formation of a solid layer at the interface surface The liquid molecules around the nanoparticles form a layered structure that has a higher conductivity coefficient than the fluid. Therefore this high thermal conductivity layer can also be a reason for abnormal increase in the thermal conductivity of the nanofluid (Fig 1.11). It is important to note that in fact, no experimental work has been done on the measurement of this layer and its conduction coefficient, and all existing models have only used the hypothesis from a theoretical point of view. Yu et al. [69] have assumed the conductivity coefficient of this layer and its thickness as a constant value. Others also assumed that the conduction coefficient varies linearly from the amount of conductivity of the nanoparticle on its wall to the amount of conductivity of the fluid at the end of the layer [70].

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CHAPTER 1 History and introduction

FIGURE 1.11 The formation of a solid layer by liquid molecules at the interface surface.

Moreover, some other researchers have considered the effect of temperature on changing the conductivity coefficient of this region [71]. Yu and Choi [72] argued that liquid layering on the surface of nanoparticles is the most important reason for increasing the thermal conductivity of nanofluids. Keblinski et al. [73], who have considered this mechanism, have deduced that, based on the actual values of the radius and fluid layer for various nanofluids, the solid-state shape can be an effective factor in increasing the thermal conductivity. However, this mechanism alone cannot explain a significant increase in the conductivity. It should be noted that the theory of surface layer formation with completely different properties with the base fluid is a simple and elegant theory but empirical evidence does not support it. Also MD simulations, which examines the properties of this molecular layer, does not support this theory [74] .

1.3.3.3 Electrical charge on particle surface The electric charge on the particle surface and the zeta potential affect the structure of the solids in the nanofluid. Lee et al. [75] made extensive empirical research on the effect of the surface charge of nanoparticles on the thermal conductivity of suspensions and concluded that surface charge strongly influences effective conduction through the structure of nanoparticles. They also concluded that exiting the electrical neutrality for nanoparticles that show a higher zeta potential would result in greater stability of the nanoparticle groups and more stability throughout the suspension. This, in turn, increases the thermal conductivity of the nanofluid.

1.3 Nanofluid and hybrid nanofluid

1.3.3.4 Brownian motion of the particles The random motion of nanoparticles into the fluid refers to the Brownian motion. This motion is the main difference of nanofluids in comparison to other suspensions and is considered as one of the nonconducting factors of increasing heat transfer and thermal conductivity coefficient. There is no consensus among researchers about the effect of Brownian motion and its importance. Jang and Choi [76], Koo and Kleinstreuer [77], and Prasher et al. [78] considered the Brownian motion as the major nonconducting cause of the increase in thermal conductivity of nanofluids and accordingly presented different models to estimate the thermal conductivity coefficient of nanofluid. On the other hand, some researchers consider the effect of the Brownian motion to be negligible. Evans et al. [79], using molecular simulations, concluded that the mobility of nanoparticles was so slow due to the Brownian motion, which was negligible in terms of heat transfer through the nanofluid. Of course, the Brownian motion plays an indirect role in the formation of nanoparticle clusters, which in its turn is very effective in increasing the heat transfer coefficient. Totally the vast majority of researchers believe that Brownian motion itself is a collaborative mechanism to increase the effective thermal conductivity of nanofluids. A large number of researchers have stated the Brownian motion of particles is important for nanofluids. The relation of this motion with its temperature and its effect on the conductivity coefficient has been specifically studied. Brownian force is a periodic force with the following spectral intensity (Eq. 1.12), in which S0 5 216γkB T=π2 ρdp5 ðρp =ρÞ2 CC Si;j 5 S0 δi;j

(1.12)

The Brownian force is as follows (Eq. 1.13): rffiffiffiffiffiffiffiffi πS0 Fbi 5 ζ i Δt

(1.13)

1.3.3.5 Thermophoresis Thermophoresis or the Soret effect appears in suspended mixtures of particles and fluids. This phenomenon is caused by the temperature gradient, so that the movement of fluid molecules in the hot zone and high energy levels in this region displaces the nanoparticles toward the cold region. Thus the heat transfer process is accelerated by moving the hot particles from the hot zone to the cold zone. Due to the size of the molecules of the fluid and the particle, this force is important only at very low fluid velocities, especially in natural convection [80]. In Fig. 1.12, the mechanism of thermophoresis is shown schematically. The components of Soret and Dufour effects will be separated after temperature gradient applies to a liquid mixture and a concentration gradient will be created according to the temperature gradient. The salt solution within a pipe that its

25

26

CHAPTER 1 History and introduction

FIGURE 1.12 Schematic of the thermophoresis mechanism.

two ends are at different temperatures is not uniform in terms of composition. The salt at the cold end of the tube has a higher concentration than the hot end of the tube. The mass flux in the x direction for a reference chemical compound in a two-phase mixture is as follows (Eq. 1.14): Jx 5 2 ρD

@c @T 2 ρDT ð1 2 C0 Þ @x @x

(1.14)

In fact, the first term on right is the Fick’s laws of diffusion, where C represents the mass fraction of the reference composition. The second term is the effect of thermal diffusion or the effect of Soret. The coefficient of Soret is defined as (Eq. 1.15): ST 5

DT D

(1.15)

Some researchers have suggested the use of a two-phase mixture instead of a pure liquid as the base fluid to create a nanofluid. Such a mixture may be beneficial in absorption cooling. The effect of a Dufour phenomenon is in contrast to the effect of a Soret and creation of thermal flux is due to chemical potential gradient.

1.3.3.6 Diffusiophoresis Diffusiophoresis or osmophoresis occurs by moving particles from a low concentration region to a high concentration region. This phenomenon is not at all desirable and increases the probability of accumulation and nonhomogeneity in the distribution of nanoparticles. Despite the fact that Buongiorno [81] has proved in his paper that the effect of this parameter will be irrefutable in the laminar flow, due to the lack of theoretical foundations about this parameter and its lesser impact than other factors, this factor has been neglected in most studies.

1.3.3.7 Special characteristics of particle flow Apart from the effects of fluid
particle interaction, particle
particle incidence, and particle
wall collisions, and under special circumstances, some of the

1.3 Nanofluid and hybrid nanofluid

specific effects of particle flow are important. These effects can also be important for nanofluids. Thermophoresis of suspended solid particles is to apply a force in reverse direction of temperature gradient. Many studies [82,83] have interpreted this phenomenon. The thermophoresis force on a particle is calculated as follows (Eq. 1.16): FT 5

6πμ2 CS ðKr 1 2:18Kr Þ 1 @T ρð1 1 3 3 1:14Kr Þð1 1 2Kr 1 4:368Kr Þ mp T @x

(1.16)

This equation can be written similar to a diffusion equation (Eq. 1.17): FT 5 2 DT

1 @T mp T @x

(1.17)

where DT is the coefficient of thermophoresis diffusion, mp is the particle mass, Kr is the ratio of the thermal conductivity of the fluid and particle, Cs 5 1.17, and μ is the viscosity of the fluid. Since this equation is obtained for solids suspensions in ideal gases, modifications of nanofluids may be required for using in solid
liquid suspensions such as nanofluids. The shear lift force, which is the force resulted from shear reported by Li and Ahmadi [84], was generalized by Saffman [85], which is why this force is called the Saffman lift force (Eq. 1.18). -

F 5

2Kv1=2 ρdij ρp dp ðdid dld Þ1=4

-

ð v 2vp Þ

(1.18)

Here K 5 2.594 and dij is the deformation tensor. This force is important only for particles smaller than micrometers and as a result can be important in nanofluids.

1.3.3.8 Shape of the particle, distribution, size, and formation of the masses Thermal conductivity of suspension could be affected by particle distribution and also clusters and agglomeration. Even when the nanoparticle volume fraction does not change, the particles and clusters form the structures and layers that increase the thermal conductivity of the nanofluid. This follows the relevant theoretical studies that model particles in spheres or in long fiber. It is obvious from Fig. 1.13 that the conductivity of the sample (B) is significantly higher than the thermal conductivity of sample (A). This is because long nanoparticles always rotate in the direction of the temperature gradient and hence create a conductive path that generates heat transfer. Many numerical and experimental studies about particle density and the formation of paths or conductive bridges support this mechanism [86].

1.3.3.9 Clustering of nanoparticles The clustering of nanoparticles is also considered as an important factor in the distribution of nanoparticles within the fluid, which generally increases thermal

27

28

CHAPTER 1 History and introduction

FIGURE 1.13 Different distribution of particles in the base fluid. (A) before nanoparticles formation, (B) after nanoparticles formation.

FIGURE 1.14 Accumulation effect on the improvement in nanofluids thermal conductivity.

conductivity. Factors such as the shape and direction of the bulks, along with the possibility of settling, are the things must be considered. The nanoparticles can be combined with each other after collision and create a larger particle that is known as clustering phenomenon. Evans et al. [79] showed that clustering can cause the heat to move relatively longer distances along the attached particles with higher velocity compare with velocity of fluid flow (Fig. 1.14). Recently some researchers have investigated the effect of particle accumulation on thermal properties. They introduced a dual effect for the accumulation phenomenon in such a way that, in addition to the possibility of increased thermal conductivity, the possibility of sedimentation is likely to increase, resulting in a decrease in the thermal conductivity of the nanofluid. This

1.3 Nanofluid and hybrid nanofluid

possible penalty needs to be considered next to positive effects of nanoparticles clustering.

1.3.3.10 Analysis of convection in nanofluids The experimental results presented in the previous sections indicate that in most cases, researchers observed the gradual improvement in forced convection, which depends on the type of particle, particle size, volume fraction, and flow properties. However, heat transfer in natural convection is reduced. Many attempts were simultaneously made to theorize on the process of convection in nanofluids.

1.3.3.10.1 Diffusion model Xuan and Roetzel [87] were probably the first to present a concept for the reasoning of convection in nanofluids. Although their presented concept was summary and without sufficient evidences for confirmation, but it led to the development of nanofluid convection modeling process. They proposed a diffusion model that their concept is based on Taylor’s mass dispersion theory [88], Aris [89], which was sponsored by Danckwerts [90]. In this study, researchers looked at how to change (or diffuse) the concentration profile of a two-phase fluid when passing through the tube. Later, this concept was used for porous media [91] and suspensions [91]. Different path of heat transfer and fluid flow in a suspension because of adding solid particles to the fluid is known as diffusion. To model a fluid with considering this concept, the diffusion term should be added to the energy equation. Nonetheless, in this model, the thermal conductivity coefficient is not equivalent with a real coefficient (or the property of the environment), rather is a particle and flow property. The amount of diffusion is due to factors such as the interaction of the particle and particle as well as the interaction of the particle and surface, which depends on the particle size, particle concentration, fluid speed, and so on. Therefore in brief, it is assumed that due to all these features and phenomena, some additional heat transfer occurs that corresponds to an additional optional conduction coefficient for modeling. This conduction coefficient is called thermal diffusion coefficient. Xuan and Roetzel [87] stated that Kaviany [91] presented the basic thermal diffusion equations. They considered the turbulence of the velocity and heat generated by the particle in the nanotube as u0 and T 0 , respectively. So “T” can be written as follows (Eq. 1.19): T 5 hT if 1 T 0

u 5 huif 1 u0

(1.19)

Here, the average volume temperature and velocity vector are given in Eq. (1.20): hT if 5

1 Vf

ð

TdV Vf

huif 5 1 Vf

ð udV Vf

(1.20)

29

30

CHAPTER 1 History and introduction

Then we can write the fundamental equation (Eq. 1.21) of displacement in vector u for fluid f: @T 1 ruT 5 rUðaf rTÞ @t

(1.21)

By inserting Eq. (1.19) in Eq. (1.21) and simplifying by means of Kaviani method:  ðρCp Þnf

  f @hT if 1 huif rhT if 5 rðknf rhT if Þ 2 ðρCp Þnf r u0 T 0 @t

(1.22)

Here the subscript nf represents the nanofluid. In the diffusion model, the additional term in (1.22) is due to velocity and temperature fluctuations, and the last term is modeled like a conductive flux. Another form of above equation is as follows (Eq. 1.23): ðρCp Þnf rhuT if 5 2 kd rhT if

(1.23)

where kd tensor is the thermal conductivity coefficient (or diffusion coefficient). Therefore Eq. (1.22) can be solved, but the amount of diffusion coefficient in kd must be specified. As an example of this kind of analysis, they considered the flow of nanofluid inside a pipe, thus we have Eq. (1.24). @T @T 1@ 1u 5 @t @x r @r

"

# " # ! kd;r @T @ kd;x @T anf 1 1 anf 1 r @r @x ðρCp Þn;f ðρCp Þn;f @x

(1.24)

Here the mark h:if is replaced with the average volumetric values of T and u. kdr and kdx are the parameters of the diffusion coefficient in a radial direction and the diffusion coefficient in the axial direction, respectively. Now values of this diffusion coefficient should be determined. This is still a challenge in this kind of modeling. Probably extensive set of experiments will be able to determine the diffusion coefficient and the nature of its change with factors such as particle charge, Reynolds number, geometric shape, and particle size. The method used by Roetzel et al. [92] is an interesting laboratory test to determine the diffusion coefficient in the tube. In this method, a periodic temperature profile is used at the pipe inlet, which occurs after heat transfer and diffusion, reduction of amplitude, and phase transfer. By using available quantities, heat transfer coefficient and thermal diffusion could be obtained. Xuan and Roetzel [87] presented several constructive proposals for the diffusion coefficient (Eq. 1.25) from a similar study kd 5 CðρCP Þnf udp Rεp or C ðρCP Þnf uR

(1.25)

where R is the radius of tube and C and C are constant values. These relationships are completely intuitive, and determining the diffusion coefficient and predicting its value in different situations requires more research.

1.3 Nanofluid and hybrid nanofluid

Xuan and Li [33] developed the concept of using the diffusion coefficient by solving Eq. (1.24) with the assumption that the axial diffusion was negligible, so the new face of equation is as follows (Eq. 1.26): "

@T @T 1@ 1u 5 @t @x r @r

! # kd @T r anf 1 ðρCp Þn;f @r

(1.26)

Considering the constant temperature at inlet and wall, the boundary conditions are (Eq. 1.27) Tr5R 5 Tw

Tx50 5 T0

(1.27)

By using separation of variables (Eq. 1.28) the equation could be solved. The flow is considered laminar and fully developed: a X 2 T 2 Tw J0 ðβ m rÞ 5 2 e2β m x=Pe T0 2 Tw J1 ðβ m rÞ n51

Pe 5

r5

Nu 5

hð2RÞ  knf

uL  aeff

Pe 5 Pe ðRLÞ2

r x R;x5 L (1.28)



Here keff 5 knf 1 kd and β m are the terms of the positive roots of the following equation (Eq. 1.29): J0 ðβ m Þ 5 0

(1.29)

For this temperature profile, you can write the Nusselt number as follows (Eq. 1.30): a P

e2βm x=Pe 2

n51

Nu 5 P a

e2β m x=Pe =β 2 m

(1.30)

2

n51

Although this relation is similar to pure fluid, but here the conduction coefficient used for Nusselt number is equal to the sum of the effective conductivity coefficient of the nanofluid and the conduction diffusion coefficient. If the axial diffusion is not neglected, an axial boundary condition is required, and it should be ensured that the heat transfer starts from the input. As shown in Fig. 1.15, the temperature drop occurs at the flow inlet. This is due to the famous boundary condition of Danckwerts [90] (Eq. 1.31): 

2keff

@T 5 uACp ðT0 2 TÞ at x 5 0 @x

(1.31)

The output of the pipe can be derived from the derivative boundary condition (Eq. 1.32): @T 5 0 at x 5 L @x

(1.32)

31

32

CHAPTER 1 History and introduction

FIGURE 1.15 The temperature drop at the flow inlet according to the boundary condition of Danckwerts.

Under these conditions, the Nusselt number is as follows (Eq. 1.33): a P

Nu 5

  XðxÞ= Xð0Þ 2 X 0 ð0Þ=Pe

m51 a P m51

  XðxÞ= Xð0Þ 2 X 0 ð0Þ=Pe =β 2m

(1.33)

where XðxÞ 5 m2 em2 1m1 x 2 m1 em1 1m2 x m2 1m1 x XðxÞ 5 m1 m2 ðe 2 em1 1m2 x Þ ffi pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2  Pe 6 Pe 1 4β m ðL=RÞ2 m1;2 5 2

(1.34)

This answer was depicted by Kim and Lee [75], as shown in Fig. 1.16, using Beckman et al. [93], distribution coefficient ratio is as follows (Eq. 1.35): pffiffiffiffiffiffiffi 8 10:LRupfffiffiffiffiffiffiffi =2 1 5:03Ru > < kd 10:LRu f =2 1 5:03Ru For a large temperature gradient 5 pffiffiffi For adiabatic materials ρCp > : 1 1 1= 2f

(1.35)

where f is the coefficient of friction. They showed that the diffusion coefficient expresses the effects of Brownian diffusion, sedimentation, diffusion, and so on.

1.3.3.10.2 Particle migration effect While the diffusion model discusses the general modeling strategies, it is important to identify the mechanisms that give clear view about the beyond of diffusion

1.3 Nanofluid and hybrid nanofluid

FIGURE 1.16 Nusselt number according to Eq. (1.33) [33].

behavior. It is a fact that the exact contribution of these mechanisms can only be determined by complex experiments that have not been performed yet. An analytical review of these effects and comparing the results with the available data can indicate the importance of these mechanisms. It seems that the mechanism of particle immigration is logical and may play a key role in convection. Ding and Wen [94] investigated the effect of particle immigration in nanofluids. They used the well-known mass equilibrium method called the combined equation provided by Philips et al. [95]. The basic concept of this model is that the particles under the influence of a shear force immigrates from a region with a greater shear to a lower shear region, and from a lower viscosity to a greater viscosity, that is due to the Brownian diffusion of a region with a higher particle concentration to a region with a lower particle concentration. Now, considering the mass equilibrium on the control volume shown in Fig. 1.17, we have Eq. (1.36): J 1r

dJ 50 dr

(1.36)

where J is the total flux of the particle in the direction of r (radial). In Eq. (1.36), the particles continuous phase is considered. The flux of the particle immigration consists of three parts that are derived from three mechanisms (Eq. 1.37): J 5 Jμ 1 Jb 1 Jc

(1.37)

33

FIGURE 1.17 Control volume considered by Ding and Wen for mass flux equation [94].

1.3 Nanofluid and hybrid nanofluid

where flux due to viscosity, flux due to nonuniform shear and flux from Brownian motion are as follows (Eq. 1.38): 0 1

dp2 Jμ 5 2 Kμ rε _ 2p @ A

dμ rεp dεp

Jb 5 2 Kc dp2 ε2p rγ_ 1 εp γrεp JC 5 Db rεp μ

(1.38)

where Kμ and Kc values are constant, γ_ is the shear rate, μ is the viscosity, and dp is the diameter of the particle. Db is the Brownian diffusion coefficient which is obtained as follows (Eq. 1.39): Db 5

kb T 3πμdp

(1.39)

Here kb is Boltzmann’s constant. By replacing Eq. (1.37) and applying the symmetrical boundary condition (at J 5 0, r 5 0), Eq. (1.40) is obtained for the onedimensional state: _ 2p Kμ rε

dp2 μ

!

dμ dγ_ dεp dεp 1 Kc dp2 εp γ_ 1 Dp 50 rεp 1 Kc dp2 ε2p dεp dr dr dr

(1.40)

In addition, in Fig. 1.17, the momentum equilibrium shown in the control volume gives the following equation (Eq. 1.41): 

drτ dp 52 dr dz

(1.41)

Because of the symmetry, the shear stress in the axis is zero (at τ 5 0, r 5 0), thus τ is as follows (Eq. 1.42): τ52

 r dp 2 dz

(1.42)

To obtain an explicit answer in this equation, the relationship of the shear stress, which depends on the fluid viscosity, should be determined. Since most researchers suggest Newtonian behavior for nanofluid, a linear relationship between shear stress and cutting rate can be assumed (Eq. 1.43). τ 5 2 μγ_

(1.43)

Therefore the momentum equilibrium decreases as follows (Eq. 1.44): γ_ 5

 1 dp r 2μ dz

(1.44)

where the shear rate is obtained from γ_ 5 du=dr. Ding and wen [96] used the Bachler formula as viscosity model. Therefore the equations can be represented as follows (Eqs. 1.45
1.46):

35

36

CHAPTER 1 History and introduction

r du 5 dr μ

KC 1 1 dμ μ d r 1 Kμ γ _ d γ_

dε dε dr 1 KKCμ ε1p drp 5 Kμ1Pe ε21r drp γ_ 5

(1.45)

(1.46)

p

where (Eqs. 1.47
1.51): μ5 γ_ 5 γ_

2μf ðdp=dzÞR

(1.47)

(1.48)

r R

(1.49)

2μf u ðdp=dzÞR2

(1.50)

3πdp3 ð2 dp=dzÞR 2kB T

(1.51)

r5 u5 Pe 5

μ μf

By solving the above equations, particle concentration profiles are obtained along with the fluid. The important parameter in this equation is the particles Pe´clet number. In particles of 90
500 nm, the change in the Pe´clet number with the change in the particle diameter, dp, is shown in Fig. 1.18. Also distribution of particles in a radial direction in different Pe´clet numbers is shown in Fig. 1.19. It is clear that the larger the Pe´clet number, the greater change in concentration of the particle will be happened. This result also shows that the possibility of accumulation in the central region is high due to the high particle concentration and the possibility of its diffusion due to the shear rate in the central region is very low. These results are for Newtonian behavior of fluid and might change considering the shear thinning behavior due to non-Newtonian behavior. Another interesting result was the large changes in viscosity from core to wall due to changes in particles concentration. It should be kept in mind that this change in viscosity (Fig. 1.20) is not due to the shear thinning (which is not considered here) but rather because of the particle immigration. They showed that the particle distribution in the higher concentration of particles is more nonuniform. This shows that in the analysis of heat transfer in nanofluids, it should be considered that the concentration of particles in the vicinity of the wall may be lower, and it might result in a lower thermal conductivity coefficient near the wall, and lower heat transfer (and also less shear stress). Therefore Ding and Wen [96] predicted that there might be an optimal nanoparticle size for heat transfer and a suitable pressure drop. Buongiorno [81] advanced the process of considering more excess hide mechanisms fluid flow. He first considered all possible mechanisms for slipping particles and fluid during the displacement of nanofluids that were Gravity,

FIGURE 1.18 Effect of temperature and particle size on Pe´clet number [94].

38

CHAPTER 1 History and introduction

FIGURE 1.19 Effect of Pe´clet number on distribution of particles [94].

FIGURE 1.20 Effect of Pe´clet number on viscosity [94].

Brownian diffusion, thermophoresis, diffusiophoresis, Magnus effect, and inertia. By comparing all the time scales of these processes, he concluded that during the laminar flow (and also in viscous sublayer of turbulent flow), the thermophoresis and Brownian diffusion are important mechanisms, while in the turbulent region

1.3 Nanofluid and hybrid nanofluid

of the nanofluid, high diffusion mechanisms can be neglected in this case. Based on these assumptions, the continuity equation for nanofluids and nanoparticles are as follows (Eqs. 1.52 and 1.53): rUυ 5 0

(1.52)

@εp rT Þ 1 υUrεp 5 rUðDB rεp 1 DT T @t

(1.53)

The momentum equation was presented by Brad et al. as follows (Eq. 1.54): ρ

  @υ 1 υUrυ 5 2 rP 2 rUτ @t

(1.54)

The term of tension assuming the incompressible Newtonian flow is as follows (Eq. 1.55):   τ 5 2 μ rυ 1 ðrυÞt

(1.55)

Because of viscosity dependency to solid volume fraction of nanoparticles, Eqs. (1.53)
(1.55) are dependent. Assuming the effects of thermophoresis and Brownian diffusion, the energy equation will be (Eq. 1.56): ρC

  @T rTUrT 1 υUrT 5 r:ðkrTÞ 1 ρp Cp DB rεp rT 1 DT @t T

(1.56)

On the right hand side of the above equation, the last term defines Brownian diffusion and thermophoresis. Also below equations have been used to reach the dimensionless form of equation. These equations can be dimensionless as follows (Eqs. 1.57
1.61): rUV 5 0  @εP 1 r2 θ 2 1 VUrεP 5 r εp 1 Re Sc NBT @ξ @υ r2 V 1 VrV 5 2 rψ 1 @ξ Re  @θ 1 rεp Urθ rθUrθ 1 VrV 5 r2 θ 1 1 @ξ RePr Le LeNBT

(1.57) (1.58) (1.59) (1.60)

where V5 ψ5

υ υ

P ρυ2

εP εPb r R5 D

εP 5

T 2 Tb ΔT t ξ5 D=υ

θ5

(1.61)

Here υ, εPb , ΔT, and D are reference values for these quantities, and the dimensionless numbers are Re 5 ρυD=μ, Sc 5 μ=μDB , NBT 5 εPB DB TB =DT ΔT, and Le 5 k=ρp Cp Db εPB that are Reynolds number, Schmidt number, Brownian thermophoresis diffusivity, and Lewis number, respectively.

39

40

CHAPTER 1 History and introduction

FIGURE 1.21 Structure of flow near the wall.

Assuming that the axial transmission is small compared to the radial term, the turbulent transfer equations will be as follows (Eqs. 1.62
1.64):   d dεp DT dT 1 ðDB 1 DP Þ 50 dy T dy dy   d dυ μ 1 ρDM 50 dy dy   d dT k 1 ρcDH 50 dy dy

(1.62) (1.63) (1.64)

Here, according to Fig. 1.21, y is a radial component, and Dp, Dm, and DH are the particles vortex diffusivity, momentum, and heat in the turbulent sublayer, respectively. Due to the turbulence of the vortex, they assumed that DP  D and εP  εpd . By removing the temperature gradient in the above equations for the laminar sublayer, the equations can be solved to achieve the distribution of the particle concentration, so that we have Eq. (1.65): ε 5 εb e1=NBT ð12y=δc Þ

(1.65)

1.4 Conclusion Developments in various fields of science and technology make it very clear for scientists that future world surely need more and more compact devices with the

Nomenclature

high level of performance, best functioning, and also brilliant long life. So the first need to have devices with mentioned characteristics was having high rates of heat transfer, especially in heat transfer devices. The limited thermal properties of conventional fluids such as water and EG and superior thermal properties of solids than fluids made a spark in the scientists mind to combine these two materials to reach more conductive working fluid. They first introduced microfluids containing microsized particles, then because of stability problems of microfluids, they proposed adding nanosized particles to the fluid and called it “nanofluid.” Nanofluids performed well enough and represented brilliant results that encouraged scientists to think about study on the effects of suspending various combinations of particles in conventional working fluids which were later developed and named “hybrid nanofluids.” Hybrid nanofluids are the new high-level class of working fluids in heat transfer applications. However, many studies are needed to make them adaptable with domestic and commercial applications and today study results on hybrid nanofluids are not strong enough for presented goal. In fact there are lots of problems in hybrid nanofluid preparation like stable and large-scale synthesize, etc. that needed to resolve. Despite many unsolved questions and problems about nanofluid and hybrid nanofluids, there are few researchers that have taken this responsibility and devoted all of power and equipments to answer the open questions about nanofluid and hybrid nanofluids. Along with common used nanoparticles in mono nanofluids, CNTs, graphene, ceramic oxides, etc. can be used next to them as second nanoparticle to reach desired properties by hybrid nanofluids. Based on the informations available in important scientific metrics until 2019, one of the most energetic research groups in the world that is fully expert in hybrid nanofluids science is Hemmat Esfe group [51
53] which focused on thermal and rheological properties of hybrid nanofluids and also optimization process on synthesized hybrid nanofluid to reach a cost and thermopysical optimized effective nanofluids [54
56] with lowest amount of side effects such as pressure drop in cycles, instability of prepared nanofluids in hot and cold working conditions, and high cost. The Hemmat Esfe group is one of the pioneers in hybrid nanofluids science. But there are many other unsolved problems about having a clear view on the effects of particle Brownian motion, microconvection, and pH values on thermophysical properties of hybrid nanofluids that need to be studied by other strong research groups in the world.

Nomenclature A area, cross-sectional area C0 speed of light in vacuum C speed of light in various environments C heat capacity Cc Cunningham correction factor for the Stokes drag force

41

42

CHAPTER 1 History and introduction

Dp vortex diffusivity Dm momentum Dh heat in the turbulent sublayer D molecular diffusion coefficient Db Brownian diffusion D molecular diffusion coefficient DT coefficient of thermophoresis diffusion dij deformation tensor δi;j Kronecker delta f coefficient of friction γ_ shear rate h heat transfer coefficient, Planck’s constant J total radial flux of the particle k coefficient of heat conduction kB Boltzmann’s constant Kr the ratio of the thermal conductivity of the fluid and particle kdr diffusion coefficient in a radial direction kdx diffusion coefficient in the axial direction kd tensor is the thermal conductivity coefficient or diffusion coefficient ζ i random Gaussian number Le Lewis number λ wavelength mp particle mass m consistency index μ viscosity n power law index, environmental refractive index Nu Nusselt number NBT Brownian thermophoresis diffusivity ν frequency of wave Pe Pe´clet number Q_ heat transfer rate qv flux of heat transfer Rc critical radius R particle radius ρ density ⍴l density of fluids ⍴p density of particles Re Reynolds number S specific area of catalyst ST coefficient of Soret Sc Schmidt number T 0 turbulent temperature term TN ambient temperature TS solid surface temperature τ shear stress u0 turbulent velocity term V volume

References

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864.

CHAPTER

Hybrid nanofluids preparation method

2

Masoud Afrand1 and Ramin Ranjbarzadeh2 1

Department of Mechanical Engineering, Islamic Azad University, Najafabad, Iran Department of Civil, Constructional and Environmental Engineering, Sapienza University of Rome, Rome, Italy

2

Chapter Outline 2.1 Introduction ................................................................................................... 49 2.2 Methods of nanoparticles synthesis ................................................................. 50 2.2.1 Bottom-up ....................................................................................50 2.2.2 Top-down ......................................................................................64 2.3 Nanoparticles ................................................................................................. 75 2.3.1 Properties of nanoparticles .............................................................75 2.3.2 Effect of nanoparticles volume fraction ...........................................77 2.4 Choosing an appropriate base fluid ................................................................. 78 2.5 Nanoparticle combination ............................................................................... 83 2.6 Hybrid nanofluid preparation ........................................................................... 83 2.6.1 Single-step method .......................................................................83 2.6.2 Two step method ...........................................................................85 2.7 Conclusions and future direction ..................................................................... 88 References ............................................................................................................ 91

2.1 Introduction In recent years, many efforts have been performed to produce nanoparticles due to their special optical, chemical, electrical, and photoelectric properties, indicating their diverse applications in the fields of catalysts, optics, biopharmaceuticals, mechanics, magnetic, and energy. Different methods of nanoparticle production in terms of particle size and composition, proper distribution, energy consumption, and ease of work are still being developed. Based on the significant developments in nanotechnology in recent decades, numerous nanostructures have prepared that have favorable properties for a wide range of biomedical and

Hybrid Nanofluids for Convection Heat Transfer. DOI: https://doi.org/10.1016/B978-0-12-819280-1.00002-1 © 2020 Elsevier Inc. All rights reserved.

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medical applications. Among the developed nanostructures, nanofluids can be mentioned. Nanofluids derived from the distribution of nanoparticles in ordinary fluids are a new generation of highly potential fluids in industrial applications. These particles are of metallic and nonmetallic particles. Suspension of nanoparticles in ordinary fluids improves the heat transfer properties (increases thermal conductivity of the fluids).

2.2 Methods of nanoparticles synthesis Synthesis is the composition or decomposition of materials to produce new materials. Nanoparticle synthesis is referred to nanoparticle preparation methods. Nanoparticles can be produced from bottom-up or top-down approaches, such as forming and growing particles from the fine molecular distribution in the liquid or vapor phase. Synthesis can also involve the operation of combining bioactive molecules. The synthesis of nanomaterials has been a major challenge in terms of its high performance and low cost from the beginning of nanomaterial development. Application of nanoparticles depends on the ability to synthesize particles of various shapes, integrity, chemical composition, and size. There are many methods to produce nanoparticles, including sol
gel solution method, neutral vapor condensation, mechanical alloying, or collision with high-energy pellets, plasma, and electrochemical methods (Fig. 2.1) [1
4].

2.2.1 Bottom-up In this method, materials are made of molecules based on the fundamental principles of science. In other words, the molecules (and the main blocks) stack up together until a larger structure is generated. To illustrate this method, one can imagine a toy car made from a number of logos that each piece of Legois a basic element. It is worth noting that nature has used this method for thousands of years in the construction of natural nanostructures [4,5].

2.2.1.1 Sol
gel method Sol
gel process is a wet chemical method for the synthesis of various nanostructures, especially metal oxide nanoparticles. In this method, the molecular precursor, usually metal alkoxide, is dissolved in water or alcohol and is converted to a gel by heating and stirringusing hydrolysis/alcoholization. The gel is dried now that can be done by burning alcohol. After drying, the gel is powdered and heated immediately for calcination. The sol
gel method is chip and it is possible to control the chemical composition of the products due to the low reaction temperature. Sol
gel can be used in the ceramics manufacturing process as casting mold or as thin films of metal oxides for various processes. Materials derived from sol
gel preparation method can be used in various optical applications such as

FIGURE 2.1 Some nanoparticle synthesis methods.

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CHAPTER 2 Hybrid nanofluids preparation method

electronics, energy, surface, biosensors, pharmaceutical biosensors, and separation technology such as chromatography (Fig. 2.2) [6
8]. The sol
gel method is a chip and affordable production method in industrial scales. Its steps can be seen in Fig. 2.3. As mentioned, in this method by making a good transparent and stable soluble solution and converting it to gel during the hydrolysis process and then condensation, the wet gel is produced. Then, one of the methods available to dry the wet gel is used to dry. The method depends directly on the type of product and their properties. The final product, which is a porous solid structure, is produced. Sol
gel can now produce high quality nanoparticles (producing the same size particles) in high volume. This method is capable of producing two or more types of nanoparticles simultaneously. This means that one can synthesize alloy products in one step by mixing synthetic precursors with two or more metals or different metal oxides with certain ratios. There are, of course, other methods that can do this, such as plasma, electrochemical, and phase condensation methods. But, it should be noted that none of them can compete with the sol
gel method at the industrial scale (Fig. 2.3). The sol
gel method can also provide very homogeneous composites with 99.99% purity. It is also capable of producing ceramic and metallic nanomaterials at much lower temperatures of about 70 C
320 C compared to conventional methods with a very high temperature range of 1400 C
3600 C [9
14].

2.2.1.1.1 The sol
gel process steps To prepare the product by sol
gel method, it is necessary to first provide the necessary conditions for the reaction. The sol
gel process steps are as follows: [15
17] 2.2.1.1.1.1 Preparation of a homogenous solution. To do this, first the water, alcohol, organic solvents, and precursor are dissolved in a container to obtain a homogeneous solution. It is sometimes necessary to use a mixture of two solvents with certain ratios to completely dissolve the precursors and to obtain a homogeneous solution. 2.2.1.1.1.2 Formation of the sol. After preparation of a homogeneous solution, it must be converted to sol. It can be said that the hydrolysis reaction is the basis of this step. The word hydrolysis is basically a combination of the two words hydrolysis and its meaning is decomposition by water. The term decomposition refers to any case that transforms a complex state into a simpler one. In chemistry, sometimes water can break down the molecule into simpler molecules. The hydrolysis occurs when a group of reactions in which water breaks down molecular water by a chemical reaction into simpler molecules. The hydrolysis reaction is not complicated. To initiate the process when water is added to the reaction medium, a homogeneous solution is prepared in a water-free solvent. The presence of water will cause the hydrolysis reaction on the precursor and activates it to create metal oxide particles to form fine and solid particles that are dispersed in the solvent. This combination is called sol as an intermediate product of the process. The most important thing to say about good and acceptable sol is that the resulting sol must be prepared in such a way that it can be stable for months

FIGURE 2.2 Sol
gel method applications.

54

CHAPTER 2 Hybrid nanofluids preparation method

FIGURE 2.3 Different types of sol
gel process and their products.

with no deposition. In other words, the particle size must be small enough so that the Brownian motion overcomes the gravitational force of the particle. Hence, the particles do not settle and remain homogeneous for a long time. If the resulting sol has such a characteristic, one can hope to produce a homogeneous, pure, and high efficiency product. 2.2.1.1.1.3 Formation of the gel. It is enough to stimulate the made solution to disperse fine particles, each containing several molecules. Some of the initiators are starting to accumulate. By forming physical and chemical interactions between suspended particles dispersed in the sol, they are accumulated into units of several thousand molecules and form an extremely large threedimensional molecule, typically have a lot of pores and trap the solvent atom inside it. It is called wet gel. One of the characteristics of gels is that they can take the shape of the container in which they are made. Depending on the strength of the gel structure, a single piece with large holes can be obtained. Since the solvent is one of the internal components of the gel in this situation, it holds the network. It is very difficult to maintain the structure of the holes by removing the solvent. It is usually advisable to allow the gel structure remains before drying to strengthen the bonds between the particles. This stage can take several hours to several days. This process is called aging. During the

2.2 Methods of nanoparticles synthesis

aging process, the gel continues to change to form new bonds and to increase the strength of the gel structure (Fig. 2.4).

2.2.1.2 Chemical vapor deposition Chemical vapor deposition (CVD) is a method to produce nanostructured materials and form coatings on the substrate. In this method, the precursors evaporate and enter the reactor. In this reactor, the precursor molecules are absorbed bysubstrate surface. The temperature of the substrate is usually set within a certain range. The adsorbed molecules either decompose by heat or react with other gases and vapors to form a solid film on the substrate. The reactions occurring on the substrate surface are heterogeneous reactions. The process has high flexibility and is used to make many materials such as metals, semiconductors, and ceramics. Solid films can be amorphous, polycrystalline, or single crystal. Solid films with unique properties can also be produced by adjusting growth conditions [18,19]. The formation of solid particles in the gaseous phase should usually be avoided, since in this case, in addition to the waste of raw materials, the layers will not have a uniform thickness. In addition, unwanted particles are also formed in the solid film. However, the formation of solid particles in the gas phase can be useful under certain laboratory conditions. For example, for the manufacture of nanoparticles or nanopowders, gas-phase germination and particle growth control are the most important aspects of growth processes. The particle size range is controlled by the number of buds formed in the reactor and the rate of particle compaction. Thermodynamically CVD in most systems requires high temperatures and low pressures. Under such conditions, the Gibbs free energy of the chemical system rapidly reaches its lowest value, resulting in solid products. The first step in understanding this process is the use of the concepts such as thermodynamics, gas transfer, reaction kinetics, germination and particle growth. This information can be very valuable in choosing the correct system for the reaction. The CVD process consists of five steps: 1. 2. 3. 4. 5.

reactive gases entering the reactor; the penetration of gases through a boundary layer; contacting the gases with the substrate surface; deposition on the substrate subsurface; and penetration of by-products of reaction into the boundary layer.

The second and fifth steps are interdependent because the penetration rate of the reactants affects the penetration rate of by-products. The two steps are linked by the relations of stoichiometric reaction. The third and fourth steps are very complex and may include surface or gas reactions, simultaneous adsorption and desorption (chemical adsorption and physical desorption) and germination processes. The slowest step determines the overall reaction rate. If the substrate

55

FIGURE 2.4 Different stages of sol
gel and the position of the aging process in it.

2.2 Methods of nanoparticles synthesis

temperature is kept well above the reactant decomposition temperature, the rate of decomposition of the initial material on the substrate is increased and the growth rate is controlled by the mass transfer rate of the reactant onto the surface control [20,21].

2.2.1.2.1 Types of chemical vapor deposition methods Many sources such as heat, plasma, lasers, and photons are used to form thin films by CVD. Therefore many techniques result in the production of thin films using CVD. According to Fig. 2.5, some of them are briefly described in the following [22,23].

2.2.1.2.2 Thermal chemical vapor deposition Heat energy is used in this process to activate gas and solid gas reactions. This process can be performed at high or low temperatures, high or low pressures, and hot or cold walls. In all these cases, the reactive gases are transferred to the reactor and the substrate is heated to increase sediment efficiency. Also by-products are removed from the reactor [24
28]. 1. Atmospheric pressure chemical vapor deposition (APCVD) (Fig. 2.6). 2. Low-pressure chemical vapor deposition (LPCVD) (Fig. 2.7).

FIGURE 2.5 Types of CVD methods. CVD, Chemical vapor deposition.

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FIGURE 2.6 Atmospheric pressure chemical vapor deposition (APCVD).

2.2.1.2.3 Metal organic chemical vapor deposition In this process, organic
metallic raw materials such as tetrakisdimethylaminotitanium are used to produce titanium oxide coatings and to provide titanium nitride. The reactants are volatile at relatively low temperatures. In this method, highquality epitaxial thin films can be created at the nanoscale (Fig. 2.8). Both reactants and by-products can be hazardous [29
34].

2.2.1.2.4 Plasma-enhanced chemical vapor deposition In this method, RF or DC plasma is created near the substrate. Like sputtering method, high-energy ions transfer the momentum and their energy to reactive gas molecules and atoms. This energy transfer causes the molecules to break down and chemical reactions to improve. The transferred momentum also contributes to better uniformity of the coating (Fig. 2.9). On the other hand, plasma improves the quality of the thin film at lower temperature and pressure [35
37].

2.2.1.2.5 Atomic layer chemical vapor deposition In ALCVD process, two raw materials [for example, water and Al3(CH)3] enter alternately into the reaction chamber. One of these substances is absorbed in the absence of the second one on the surface of a wafer (the surface on which the deposition is formed on it). The absorption is continued until the surface is saturated. Then, the second material is added into the environment and the reaction

FIGURE 2.7 Low-pressure chemical vapor deposition (LPCVD).

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CHAPTER 2 Hybrid nanofluids preparation method

FIGURE 2.8 Schematic of a MOCVD reactor. MOCVD, Metal organic chemical vapor deposition.

begins. The film thickness is controlled by the magnitude of inlet material in the reaction chamber (Fig. 2.10). In this method it is possible to precisely control the film thickness and their uniformity [38
41].

2.2.1.3 Hydrothermal The hydrothermal method has attracted much attention compared to other advanced nanoparticle production methods. The term hydrothermal has a geological origin (it was first used by an English geologist to describe the action of water at high temperatures and pressures, which creates various rocks and minerals). The origin of the largest single crystals found in nature and many of the synthetic single crystals made in laboratories are hydrothermal. Originally hydrothermal referred to chemical reactions (homogeneous or heterogeneous) in the presence of solvents at high temperatures and pressures. At the end of the 20th century, an international conference on the topic of the hydrothermal process was held. The result of this conference was the dissemination of information on the thermodynamics of this process, which led to a dramatic reduction in the temperature and pressure conditions of the process and its conversion to green chemistry. Today the hydrothermal production method has a share of approximately 6% in the production of advanced materials. Fig. 2.11 shows the steps of the hydrothermal method. A wide range of metal oxides, hydroxides, silicates, carbonates, phosphates, sulfides, nitrides with nanostructures such as nanotubes, nanowires, and

2.2 Methods of nanoparticles synthesis

FIGURE 2.9 Plasma-enhanced chemical vapor deposition reactor (MOCVD). 1. chamber walls, 2. electrode bodies, 3. electrode meshes, 4. plasma zone, 5. water cooling system of electrode bodies, 6. discharge downstream area, 7. substrate, and 8. substrate holder. MOCVD, Metal organic chemical vapor deposition.

nanorods are prepared using this method. Hydrothermal is a method based on the formation and growth of crystals by chemical reactions and changes in the solubility of substances in an aqueous solution under appropriate temperature and pressure. In the past, hydrothermal synthesis was carried out at critical temperatures and pressures, but nowadays, this method is used at low temperature and pressures by identifying suitable solvents for each reaction and using new techniques to energize the system (such as using macrowaves or magnetic fields). Generally the reactants are first dissolved in the appropriate solvent. Ultrasonic waves are used to dissolve or disperse the precursors in solution if needed. Then, the raw material solution is poured into the autoclave. Then the autoclave containing the reactant solution is heated to the appropriate temperature. As a result, the pressure inside the autoclave increases and the conditions for the reaction of the precursors are provided. After sufficient time to complete the chemical reaction within the autoclave, the heating is stopped and the products come out. They are heated if needed for drying or calcination [42
51].

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FIGURE 2.10 Schematic of the operation of ALCVD. ALCVD, Atomic layer chemical vapor deposition.

2.2.1.3.1 Types of hydrothermal methods Reaction system conditions and environmental conditions greatly affect the reaction development and its products. To control the morphology of products made from various materials as additives, molds or substrates can be used. Based on these different materials and various states of the system and environment conditions, several methods of hydrothermal synthesis have been reported in the literature. In the following, we examine the effect of using different materials and different heating methods on hydrothermal production method [45,52
54]. 2.2.1.3.1.1 Methods based on the use of organic additives. Organic additives can be used to control the morphology of the produced particles and to monitor the reaction progress in the hydrothermal process. Depending on the chemical nature of the additives and the solution, these additives can participate in the chemical reaction between the reactants as either a reducing agent or an absorbing agent. Surfactants, biosimilar, ionic liquids, organic acids, and organic solvents are the most commonly used organic additives in this process. 2.2.1.3.1.2 Methods based on the use of mold. In some hydrothermal methods, particles are added to the reaction system for precise control of the size and shape of the nanoparticles. Theoretically the desired nanoparticles can be precisely printed using molds. This practically faces challenges. The molds must be selected to be compatible with the materials in addition to providing a suitable substrate for the formation of the nanoparticles and to be easily separable from the nanoparticles upon completion of the reaction.

2.2 Methods of nanoparticles synthesis

FIGURE 2.11 Steps of the hydrothermal method.

2.2.1.3.1.3 Substrate-based methods. The hydrothermal method can also be used as a low cost alternative to CVD- or PVD-coating methods. To produce nanostructured arrays, the appropriate substrate is selected and placed in the reaction chamber. 2.2.1.3.1.4 Heating methods in hydrothermal method. One of the main environmental conditions of the reaction is the way the system is energized. In the hydrothermal method, the furnace was usually used to heat the system. The use of furnace and conductive heat transfer causes high temperature gradient in different parts of the reaction chamber and nonuniform reaction conditions, resulting in

63

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large-scale particle production. Hence, other methods are used today for more uniform heating. These methods include microwave heating and magnetic field heating.

2.2.2 Top-down In this method, the material is separated from the bulk object using a series of tools. It decreases to the nanometer size. In fact, in this method, nanostructures are made without atomic control, so that the high-dimensional structure can be scaled down to nanometer dimensions using special tools such as nanotechnology microscopes [4,55,56].

2.2.2.1 Nanolithography As technology is evolved, the need to develop and fabricate small-scale electronic devices, faster speeds, better specifications, and better performance is increased. In this regard, a lot of research has been done to develop nanotechnology-based manufacturing methods. Lithography is one of the most popular methods of making electronic circuits that has been developed with the advent and development of tools such as scanning electron microscopes and probe microscopes. Nowadays structures of up to 10 nm are manufactured using this method. Researchers are working to convert new lithography techniques to industrial methods and reduce the cost of producing parts using this technique. Lithography is a Greek word composed of two parts: Lithos meaning stone and Graphia meaning writing and engraving [57,58]. This method involves forming a lithographic design of a pattern on an electronic material and transferring the pattern to another material to produce an electronic or optical instrument. Lithographic techniques can be categorized in a variety of ways. Over time, however, with the advent of tools and new technologies, these techniques have been developed as highly sophisticated methods called nanolithography for molecular and nanostructured architecture, so that in recent decades this technique has been developed. It is widely used for the manufacture of integrated circuits, information storage devices, miniature sensors, microelectromechanical systems and nanoelectromechanical biochips [59
63]. Lithographic techniques are divided into two methods based on the required tools, image transfer method, and patterning strategy, which include writing direct engraving or transferring the pattern using optical mask with conventional radiation techniques and some developed methods. The first method is known as serial writing and the second one is parallel replication. Parallel replication techniques include methods such as optical lithography, contact printing, and nanoseal lithography, which are used to produce high-efficiency and large-scale productions. However, the designs cannot be customized. For example, the Yak microcontact printing method is a well-known method of transferring molecules from the material to the substrate to cause physical contact. An example of this method is shown in Fig. 2.12. Row engraving, such as scanning probe lithography (SPL),

FIGURE 2.12 Schematic image of alkanethiol molecules from an elastomeric seal to the substrate [64].

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allows for the production of arbitrary patterns with high resolution and accurate recording with limited output. SPL refers to techniques based on scanning probe microscopy (SPM) that create a pattern on the substrate using various techniques such as scraping, writing, and radiation. The structure resulting from this manipulation has dimensions ranging from 18 to 188 nm [60,65
67]. There are three main types of SPL techniques include:

• atomic force microscopy (AFM), • scanning tunneling microscopy, and • scanning near-field optical microscopy. By improving the resolution obtained by the lithography to a few nanometers. This method is also used to characterize the surfaces. This process requires advanced tools and technology to create patterns on surfaces such as a nanopen with molecular inks. Another point to note is that transfers performed by lithography may lead to an increase in the temperatures more than 188 C. However, biomaterials are deactivated at this temperature. SPL techniques do not require temperature gradients and are therefore suitable for manipulating biological and soft materials.

2.2.2.1.1 Optical lithography The oldest method for designing is optical lithography, so the semiconductor industry depends on ultraviolet lithography. In this process, the pattern is formed into an image layer called resist. This light-resistant layer is placed on a substrate of semiconductor material such as silicon wafer. To cover the surface with a refractory material, a small amount of it is distributed as a liquid solution on the substrate surface. The substrate is then rotated at high speed around its axis, during which the excess material is removed from the system and the solution evaporates. As a result, a thin layer of solid material of microns forms on the substrate surface. To compress the resistant material and removal of the residual solvent, the substrate coated with the resistant material is subjected to a heat treatment as a baking (Fig. 2.13). After this step, the substrate coated with the resistant material is ready for design [60,61,65]. Fig. 2.14 provides a schematic of optical lithography. To create the design, areas of resistant material are selectively placed under radiation. During the radiation process, ultraviolet rays usually pass through an optical quartz mask that allows light to pass through the resistant material based on the design of the circuit. The reactions created in resistant material due to the radiation alter its molecular junctions. Then, the substrate coated with the resistant material is exposed to the radiation, washed in a suitable solvent and the desired design is created. It is possible to form complex designs on the surface by repeating this process. In this method, the resistant material forms a layer of the image on the substrate surface. In the lithography process, a chemical change occurs during the local radiation in the radiative-sensitive material.

2.2 Methods of nanoparticles synthesis

FIGURE 2.13 Substrate surface coverage by resistant material.

Commercial resistors are polymeric materials that are easily places on the substrate. They are also flexible and highly sensitive. The polymer molecular weight and its solubility change due to the radiation effect. The solubility change is due to positive resistant chain shear or negative cross resistant bond in the polymer. In the case of positive resistance, dissolution increases with the shear created by the radiation. In the case of negative resistance, the solubility decreases with the radiation. For example, polymethyl methacrylate is a positive resistant species. However, negative resistors have less resolution and contrast than positive ones. Inorganic resistant materials such as metal halide salts, metal oxides, and semiconductor oxides are also present.

2.2.2.1.2 Electron beam nanolithography One of the new technologies in the field of lithography is the use of electric microscopes to produce electron beams. Electron beam lithography (EBL) is a very precise and high resolution method for drawing (Fig. 2.15) to create a design. In this method, a well-focused electron beam with a power of 388 keV

67

FIGURE 2.14 Schematic of optical lithography [68].

2.2 Methods of nanoparticles synthesis

FIGURE 2.15 Schematic of EBL system based on scanning electron microscope. EBL, Electron beam lithography.

produced by scanning electron microscopy is used to create fine linear designs on semiconductor material coated with resistant material. Due to the extremely low mass of the electrons and their high charge-to-mass ratio, it is possible to concentrate and conduct those using relatively low magnetic and electric fields. As the beam energy increases, its wavelength decreases. This improves the final resolution. However, the resolution, or dimension of the structure achievable by the electron beam method is limited to about a few nanometers, which is mostly due to the limited material resistance. For example, if it is possible to concentrate the electron beam to reach a resolution of about 8.5 nm, the resistor alone will limit the final resolution to about 5 nm. An important characteristic of resistant material for high resolution design is contrast, because it is possible to make small changes in the thickness of the areas under the radiation using high-contrast positive materials. EBL is often used in indirect radiation, scheme transfer, and direct writing electron beam [69
72].

2.2.2.1.3 Scanning probe microscope lithography Scanning probe microscopes, such as STM and AFM (Figs. 2.16 and 2.17) have been identified as powerful methods for visualizing material surfaces with the

69

FIGURE 2.16 Active nanocharacterization using STM. (A) In the “seeing is creating” type, nanofabrication and nanocharacterization are merged. (B) The “seeing is discovering” type involves dynamic characterization in externally applied fields or environments.

2.2 Methods of nanoparticles synthesis

FIGURE 2.17 Schematic visualization of the lithographic process when amylase immobilized to a cantilever tip is used.

highest spatial resolution. In the case of structural analysis, AFM has a resolution ˚ in horizontal and 8.85 A ˚ in vertical states, while STM resolution is sevof 8.1 A eral times higher than AFM. This image resolution is related to crystalline systems, which cannot be achieved at the soft and sticky surfaces with high resolution. Among the available methods for making the nanostructures, SPL is one of the most promising methods for nanoscale production. SPM can be used to manipulate atoms on metal surfaces and produce nanopatterns on metal surfaces and semiconductors using sharp needles to create strong and localized interactions between the needle and surface. However, SPL cannot quickly produce patterns such as optical lithography and electron lithography. This method has received much attention because of its ability to create and produce images simultaneously with high accuracy [60]. High resolution image acquisition is the basis of molecular manipulation and SPM-based nanolithography. In principle, it is possible to selectively break chemical bonds by increasing local interactions such as atomic

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force, tunneling electron density, or electric field strength. The details of this method are the basis for achieving sharp designs with spatial accuracy to control the local interactions [73
76].

2.2.2.2 Milling process Milling is one of the traditional methods of powder preparation that can be used in mechanical alloying operations. The tools used in this method are usually ball mills. There are generally different types of mills, which differ in terms of capacity, efficiency and additional heating, and cooling equipment. In the material production process using this method, the properties and quality of the work are directly related to the equipment and working conditions of the mill. Therefore selecting the type of mill and knowing its features is one of the first steps in a grinding process. This indicates the importance of studying and identifying the types of mills and their capabilities in material processing. This method is an example of top-down methods and is based on the disintegration of the coarsegrained structure. Mechanical alloying technique is a method of grinding and mixing different powders at the atomic level using a high energy ball mill. This technique uses in addition to pure elemental powders, alloys, and ceramics such as oxides, nitrides, etc., are used to form alloys and composites. The mechanism that is actually used is the mechanism of mechanical wear along with crushing. The failure of the grains is due to the energy being transferred to them, which depends on the rotational velocity (or vibration), size and number of balls, ballto-particle mass ratio and the duration of wear during the abrasion process. One of the most important methods of processing powders is grinding, which has found many applications in various industries. These devices can be used in grinding and other processes such as mechanical alloying. In this paper, different milling methods and their advantages, limitations and applications will be discussed [77,78].

2.2.2.2.1 Vibratory ball mill One of the high-energy mills is vibrating ball mill. The volume of the chamber in this type of mill is very low (18 mL) and its contents are powder and pellet fluctuate in three directions perpendicularly at a very high speed, about 1288 rpm. Fig. 2.18 schematically illustrates how this type of mill is performed [79,80].

2.2.2.2.2 Attritor ball mill As shown in Fig. 2.19, this mill contains a chamber and stirrer. The vertical stirrer with a number of blades has rotational motion. The blades transfer energy to the balls and reduce the particle size of the powder due to the collision between the balls, the ball and the chamber wall, the center axis and the blades with the balls. The center axis speed of the mill is about 258 rpm at 7.2 Hz. In some cases, the speed is as high as 588 rpm. This mill has a capacity between 8.5 and 78 kg and is used to process a wide range of materials including intermetallic, ceramics, noncrystalline materials, and composites.

FIGURE 2.18 Vibrating ball mill.

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FIGURE 2.19 Attritor ball mill.

FIGURE 2.20 Tumber horizontal ball mill.

2.2.2.2.3 Tumber horizontal 2.2.2.2.3.1 Tumber horizontal ball mill. In this type of mill, steel balls, or tungsten carbide are used as abrasive components (Fig. 2.20). The capacity of these mills depends on various factors such as the ratio of the length to the diameter of

2.3 Nanoparticles

the mill, rotational speed of the mill, the ball size, and the particle size. Although the use of these low-energy mills prolongs the grinding time, the powder produced in this method is more homogeneous and uniform. In addition, using this type of mill requires lower cost, easier setup, and lower maintenance cost. 2.2.2.2.3.2 Tumber rod mill. Studies show that the powder is usually contaminated with iron due to mechanical alloying. In 1558 Aleskandarani et al. used a mill containing stainless steel 387 cylinder and 18 rods for grinding. To prevent the rods from getting stuck together, rods with the length of 288 mm and a diameter of 128 mm were used in a cylinder with a length of 258 mm.

2.2.2.2.4 Plantarry mill Another mill used in the mechanical alloying process is planetary mill where only a few hundred grams of powder is milled in one step and is suitable for experimental researches. The volume of the container is between 75 and 588 mL. An example of this type of mill is shown in Fig. 2.21. The mill consists of a rotating plate with one, two, or four chambers.

2.3 Nanoparticles 2.3.1 Properties of nanoparticles Nanoparticles are made from different materials, including metals, nonmetals, and metalloids. The nanoparticles are less than 100 nm in size and have their own properties. The small size of the particles causes the nanoparticles to change with the properties of the nanoparticles, so it is necessary to remeasure the properties of the nanoparticles. These properties include the size of the nanoparticles, their shape, their thermal conductivity, etc. Some of the more popular properties of the nanoparticles are presented in Table 2.1. These properties can be applied in their own domain. For example, electrical conductivity is very important in the development of nanoscience. The shape of the nanoparticles can also be important in discussing the stability of nanofluids. On the other hand, very important properties of nanoparticles can be attributed to the specific heat. This property is very important in the transportation and maintenance of heat. The density of nanoparticles can also be important in various topics such as pumping. Table 2.1 presents some of the nanoparticles and their properties. In most papers, it has been considered that an increase in thermal conductivity of nanoparticles can lead to an enhancement in nanofluid thermal conductivity. In general, this is the reason for the use of nanofluids. Thermal conductivity of the nanofluids increases by adding metal nanoparticles that have higher thermal conductivity than the fluids [81,82]. Table 2.2 presents the nanoparticles which are more commonly used. Each nanoparticle has its own properties include thermal conductivity, viscosity, electrical conductivity, specific heat, and density. Due to the importance of thermal conductivity, this coefficient is separately explained.

75

FIGURE 2.21 Types of plantarry mill.

2.3 Nanoparticles

Table 2.1 Thermophysical properties of pure fluids and nanoparticles number of studies that used this material. Cp J=kg K Al2 O3 CuO TiO2 Cu Ag Fe3 O4




765 540 686.2 385 235 670

ρðkg=m3 Þ 3970 6500 4250 8933 10,500 5200

σðΩ mÞ21 212

10 2.7 3 1028 2.7 3 10212 5.96 3 107 3.6 3 107 2.5 3 104

β(K)21 0.85 3 1025 0.85 3 1025 0.9 3 1025 1.67 3 1025 1.89 3 1025 1.3 3 1025

Table 2.2 Thermal conductivity of some nanoparticles. Num

Nanoparticle

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Al2O3 CuO Fe2O3 MgO SiO2 TiO2 ZnO Ag Al Au Cu Fe SiC MWCNT

Thermal conductivity [83] [84] [83] [85] [84] [86] [86] [87] [88] [87] [87] [88] [89] [90,91]

40 76.5 6 54.90 B1.34 8.4 29 429 238 310 401 B75 490 2000
3000

This makes each researcher use their own nanoparticles for their own needs. Some researchers consider electrical properties and use metallic nanoparticles and others consider high specific heat. But most researchers consider higher thermal conductivity. Hence, they combine different nanoparticles and different fluids.

2.3.2 Effect of nanoparticles volume fraction Hwang et al. [92] studied the thermal conductivity of SiO2, MWCNT, and CuO nanoparticles in the base fluid of water. They found that by adding these nanoparticles with the volume fraction 1%, their thermal conductivity increases 3%, 11%, and 5%, respectively. Zhu et al. [93] investigated thermal conductivity of Fe3O4,

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TiO2, and Al2O3 in water. Thermal conductivity coefficients of Fe3O4, TiO2, and Al2O3 are 9, 15, and 35, respectively. They found that by adding these nanoparticles with the volume fraction 4%, their thermal conductivity increases 38%, 30%, and 30%, respectively. Thermal conductivity coefficient of Al2O3 and TiO2 in the water base fluid has been studied by Yoo et al. [94] Their results showed that by adding these nanoparticles with the volume fraction 1%, their thermal conductivity increases 3% and 14%, respectively. Sinha et al. [95] investigated thermal conductivity of iron and copper nanoparticles in ethylene glycol base fluid. Thermal conductivity of iron and copper is 9 and 386, respectively. They found that by adding these nanoparticles with the volume fraction 1%, their thermal conductivity increases 27% and 60%, respectively, indicating that the addition of nanoparticles with higher thermal conductivity leads to an increase in the nanofluid thermal conductivity. Angayarkanniand Philip [96] added SiO2 and TiO2 nanoparticles into the water base fluid and compared their thermal conductivity. Thermal conductivity coefficient of nanoparticles is considered to be 1.4 and 15, respectively. They found that by adding these nanoparticles, their thermal conductivity increases 9% and 15%, respectively. This means that the higher thermal conductivity of the nanoparticles results in higher thermal conductivity of the nanofluid. Shima and Philip [97] studied the effect of nanoparticle changes on thermal conductivity coefficient by adding Fe3O4 and Ag nanoparticles into kerosene base fluid. They measured thermal conductivity coefficient of the nanofluid with the volume fraction of 0.01%. They found that thermal conductivity of the nanoparticles is 9 and 429, respectively. They eventually found that by adding these nanoparticles, thermal conductivity coefficient increases by 2% and 4%, respectively. Balla et al. [98] investigated thermal conductivity of Cu and Zn in water and found that as the thermal conductivity of the nanoparticles increases, thermal conductivity of nanofluid increases (Fig. 2.22). In another work, the effect of three different nanoparticles for ethanol base fluid has been investigated by Mostafizur et al. [100] (Fig. 2.23).

2.4 Choosing an appropriate base fluid Fluid selection is very important for nanofluid preparation. Fluid properties are a major part of the nanofluid properties so it is necessary to select the best fluid according to its application. For example, the nanofluid viscosity is highly dependent on the fluid. As a result, the pumping power, which is dependent on the shear stress, is highly dependent on the fluid viscosity. Thermal conductivity of the nanofluid also depends on the thermal conductivity of the base fluid. The fluid type is also important for the thermal conductivity of the nanofluid. But the type of fluid depends more on the application of nanofluid in the system. Certainly the most important and widely used fluid is water that is widely available and has better thermal properties than other fluids. Its viscosity at the room conditions is

2.4 Choosing an appropriate base fluid

Effective thermal conductivity (Knf / (Kbf)

1.3 Al2O3-EG CuO-EG Al2O3/CuO-EG

1.25 1.2 1.15 1.1 1.05 1

0

0.01

0.02

0.03

ϕ(%)

0.04

0.05

0.06

FIGURE 2.22 Effect of particle species on thermal conductivities of EG-based alumina, copper oxide, and 1:1 mixture of alumina and copper oxide nanofluids by Raghu et al. [99].

Thermal conductivity enhancement (%)

35 Al2O3-Methanol SiO2-Methanol TiO2-Methanol

30 25 20 15 10 5 0

0

0.05

ϕ(%)

0.1

0.15

FIGURE 2.23 Thermal conductivity enhancement for different volume fraction at 20 C by Mostafizur et al. [100].

about 0.001 kg/m s. In cold areas where water can be frozen, researchers have used ethylene glycol as a working fluid. Many researchers have used water and ethylene glycol to improve the thermal properties. In some nanofluid applications, the need for noncooling lubrication has led some researchers to use a variety of

79

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oils to make their nanofluids [101]. The use of fluids that can provide higher thermal conductivity for nanofluids has been the subject of many researches in the past [92,102
105], which are discussed below. In Table 2.3, thermal conductivity of some fluids is presented. It can be found that water is the most commonly used fluid to prepare the nanofluids. Wang et al. [112] investigated the thermal conductivity of alumina and copper oxide nanoparticles in different base fluids of water, EG, vacuum pump oil, and EO. They found that the highest thermal conductivity coefficient corresponds to alumina with the base fluids of water, EG, EO, and pump oil, respectively. It shows the importance of base fluid selection. In Fig. 2.24, the effect of four base fluid is shown. It can be seen that the amount of nanofluid thermal conductivity increases by increasing the fluid thermal conductivity. But another important point is which fluid can obtain a greater increase in thermal conductivity by adding a specific volume percentage of the nanoparticles. Hence, Figs. 2.25 and 2.26 present thermal conductivity of nanofluid relative to that of the base fluid. Maximum thermal conductivity coefficient for the volume fraction of 4.5% is related to EO, EG, water, and pump oil, respectively. This is not consistent with the increase in the thermal conductivity coefficient. The effect of copper oxide nanoparticles in the two different fluids of water and ethylene glycol can also be seen here, where the more conductive fluid makes the nanofluid with higher thermal conductivity. In another work, the effect of alumina nanoparticles on various fluids has been studied. The comparison is shown in Fig. 2.27. Xie et al. [113] investigated thermal conductivity coefficient of nanofluids include MWCNT nanoparticles in three base fluids of water, EG, and Decene. Ruan and Jacobi [114] studied the thermal conductivity of MWCNT nanoparticles with the volume fraction of 0.24% in water and EG base fluids. They found that for both base fluids the thermal conductivity increases by about 9% by adding Table 2.3 Thermal conductivity of some base fluids. Num

Nanoparticle

1 2 3 4 5 6 7 8 9 10

EG EO Ethanol Glycerol Kerosene Toluene Water 20:80% EG/W 40:60% EG/W 60:40% EG/W

Thermal conductivity [88] [106] [107,108] [88] [107,109] [89] [110] [111] [111] [111]

0.257 0.14 0.161
0.171 0.285 0.145
0.168 0.133 0.608 0.492 0.404 0.334

2.4 Choosing an appropriate base fluid

0.8

Pump fluid Engine oil Ethylene glycol Water

k (W/mK)

0.6

0.4

0.2

0

0

2

4

ϕ(%)

6

8

10

FIGURE 2.24 Thermal conductivity as a function of volume fraction of Al2O3 powders in different fluids by Wang et al. [112].

Thermal conductivity ratio (Keff)

1.6 Pump fluid Engine oil Ethylene glycol Water

1.4

1.2

1 0

2

4

ϕ(%)

6

8

10

FIGURE 2.25 Thermal conductivity ratio as a function of volume fraction of Al2O3 powders in different fluids by Wang et al. [112].

nanoparticles. Liu et al. [115] investigated the thermal conductivity of MWCNT in EG and synthetic engine oil. They found that in EG-based nanofluid, thermal conductivity coefficient increases by about 30% by adding nanoparticles with the volume fraction of 2%, and it increases by 12.4% for EO-based nanofluid by

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Thermal conductivity (W/mK)

1

0.8

0.6

Ethylene glycol Water

0.4

0.2

0

0

5

ϕ(%)

10

15

FIGURE 2.26 Thermal conductivity ratio as a function of volume fraction of CuO powders in ethylene glycol and water by Wang et al. [112]. 0.6 Al2O3-PO Al2O3-EG Al2O3-Gly Al2O3-Water predicted

0.4

λ/λ0

82

0.2

0

0

0.2

0.4

λ0(W/mK)

0.6

0.8

FIGURE 2.27 Enhanced thermal conductivity ratio of α-Al2O3 nanoparticle suspensions with different base fluids by Xie et al. [104].

adding nanoparticles with the volume fraction of 1%. In this study, it was found nanofluid thermal conductivity increases with the thermal conductivity of fluid. Agarwal et al. [116] compared thermal conductivity of Al2O3/DW and Al2O3/EG nanofluids. They found that the rate of change of thermal conductivity coefficient

2.6 Hybrid nanofluid preparation

of water-based nanofluid is often consistently related to the nanoparticles volume fraction and temperature and increases with time. However, in EF-based nanofluids, thermal conductivity coefficient is more dependent on the volume percentage of nanoparticles than the temperature. This suggests that water-based nanofluids play a more effective role in heat transfer where temperature is more pronounced. EG-based nanofluids are more appropriate in heat transfer where the volume fraction is more pronounced. Li et al. [117] investigated the thermal conductivity of aluminum nanoparticles in water and EG base fluids and found that thermal conductivity of nanofluid decreases with that of base fluid.

2.5 Nanoparticle combination Combination of nanoparticles requires special consideration to prepare a nanofluid. One of the most important parameter is nanofluid stability. Hybrid nanofluid is obtained when several nanoparticles are combined and homogenized in a fluid. The nanoparticles do not interact with each other. It is more important that they do not accumulate. The issue of stability in hybrid nanofluids is very important and worth considering. Hydrophilic or hydrophobic nanoparticles are important to select uniform nanoparticles. Due to the high thermal conductivity of carbon nanotubes (CNTs; MWCNTs), it is usually one of the nanoparticles used for preparing hybrid nanofluids. Other nanoparticles are selected due to other important properties in the researches.

2.6 Hybrid nanofluid preparation The researchers have found that two or more nanoparticles can be used instead of a nanoparticle to make nanofluids. Two or more nanoparticles are used instead of a single nanoparticle for preparation of hybrid nanofluids. The use of two or more nanoparticles makes the nanofluid have better properties than mono nanofluids. Therefore the use of hybrid nanofluids and related articles has greatly expanded in recent years. The hybrid nanofluid is very similar to the mono nanofluids. There are generally two ways to prepare nanofluids. These two methods include single-step and two-step ones. The explanations are presented in the following.

2.6.1 Single-step method The preparation of nanofluids is a very important subject in experimental articles. The nanofluid preparation methods can have a significant impact on important parameters such as production cost and stability. There are generally two types of nanofluid preparation method include single-step and two-step ones. Each of these methods has its own advantages or disadvantages that have made each researcher

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use one of them. In the single-step method, nanoparticles and nanofluids are prepared in one step completely [118]. The single step method can be performed by various methods of direct evaporation, physical vapor deposition (PVD), liquid chemical direct evaporation method, PVD technique and liquid chemical method [118
120]. Very good stability, nanofluid homogenization and no particle aggregation are the advantages of this method. The main reason is the production of nanoparticles and nanofluids at the same time, which makes it unnecessary to carry and maintain nanoparticles. Interactions in the transport and storage of nanoparticles may cause the nanoparticles to adhere to each other and eventually avoid nanofluid homogeneity. The most important disadvantage of this method is the low nanofluid production. The reason is the slow process of nanofluid production in a one-step method. It also brings more cost to researchers. It can only synthesize low-pressure liquids. Also the nanofluids have low volume fractions. This method cannot be used to produce the nanofluids with high volume fractions. In Fig. 2.28, a schematic of a device uses single-step method is shown [121]. References [121
123] are among the papers presented on one-step physical method to prepare nanofluids. Another one-step nanofluid production method is the chemical one, which is faster but more difficult than the previous one. References [120,124
127] refer to the articles that have used this method.

FIGURE 2.28 Schematic diagram of the ultrasonic-aided submerged arc nanoparticle synthesis system [121].

2.6 Hybrid nanofluid preparation

2.6.2 Two step method Another method to prepare the nanofluids is the two-step one. This method is much more useful than the previous one. The main reason for this is the lower cost of this method than the previous one. In this method, unlike the single-step method, nanoparticles, and nanofluids are produced in two separate parts. In Fig. 2.29, the nanofluid preparation steps using two-step method and the reason for naming it are presented. Most researchers use premade nanoparticles and make their own nanofluids. This leads to that the cost of this preparation method is lower than that of singlestep one. It also has a lower production time and the ability to produce nanofluids in large volumes. Another advantage of this method is the production of nanofluids with different volume fractions. In the single-step method it was not possible to produce nanofluids with high volume fractions but it was possible using two-step one. In the two-step method, the nanoparticles must be preproduced. Nanoparticle production methods or available nanoparticles obtained from the factories can be used. At the nanofluid preparation step, the nanoparticles must be combined with the liquid to produce the nanofluid. The main problem of this method is appeared at this step. It is difficult to prepare a homogeneous nanofluid with proper stability without particle aggregation. Due to the adhesion of nanoparticles to each other during the transport and storage of nanoparticles as well as the high surface energy of nanoparticles, homogenous, and stable nanofluid preparation is an important challenge in the two-step method. To reduce this defect and produce nanofluids with better stability conditions, researchers have used a variety of methods, including high-pressure homogenizer, mechanical stirrer and shaker, andultrasonic sonicator [128
130]. In Figs. 2.30 and 2.31 schematic

FIGURE 2.29 Preparation of nanofluid.

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FIGURE 2.30 Schematic diagram of the high-pressure homogenizer for producing nanofluids.

diagram of a modified magnetron spray system for nanofluid preparation is shown [131]. The following methods can be used to enhance nanofluid stability and to create a homogeneous fluid. Some researchers have used all three methods to improve stability and others have used one or two ones. Each method is briefly described below.

2.6.2.1 Addition of surfactants Adding a surfactant to the nanofluid is a simple and economical technique to increase the stability of nanofluids. Surfactants significantly affect the surface characteristic of the system. These materials contain a hydrophilic polar head and a hydrophobic head (usually a hydrocarbon chain). They are divided into four categories based on their hydrophilic composition: 1. 2. 3. 4.

nonionic with no charge on hydrophilic tail; anion with negative charge; cation with positive charge; and amphoteric that can have positive or negative charge on hydrophilic tail.

FIGURE 2.31 Schematic diagram of the modified magnetron sputtering system for producing nanofluids [131].

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To select the appropriate surfactant, it should be noted that if the base fluid is polar, a hydrophilic surfactant should be selected. Otherwise, the surfactant soluble in oil is selected [132]. The use of these materials should also be considered because the presence of these substances in the nanofluid modifies the nanofluid properties and affects the mass transfer and heat transfer. The major surfactants used by the researchers are sodium dodecyl sulfate, sodium dodecyl benzene sulfate, cetyltrimethyl ammonium bromide, oleic acid, dodecyl trimethyl ammonium bromide, and polyvinyl pyrolidone [133]. Although the use of surfactants is one of the common methods to improve nanofluid stability, adding these materials to nanofluids may cause problems such as foaming and reducing the thermal conductivity of nanofluids. Also nanofluid stability is lost due to the destruction of the bond between the surfactant and the nanoparticles at temperatures above 60 C [133].

2.6.2.2 Nanofluid pH control The stability of a nanofluid is directly related to its electrokinetic properties. If the nanoparticles have a high charge density, the nanoparticles will be stable in the fluid due to the electrostatic repulsive force. Therefore optimum stability can be achieved by adjusting the nanofluid pH [133].

2.6.2.3 Ultrasonic vibration Ultrasonic vibrators can be used to enhance nanofluid stability. The two previously mentioned methods improve the nanoparticle stability by modifying the nanoparticle surface, but in this method, the ultrasound eliminates weak surface bonds between the nanoparticles and thereby breaks the agglomeration and enhances the nanofluid stability. A schematic example of an ultrasonic device is provided in Figs. 2.32 and 2.33. References [134
140] are some instances of the articles that have used this method to prepare the nanofluids.

2.7 Conclusions and future direction In the papers focusing on hybrid nanofluids, new nanofluids are made from different nanoparticles. Much attention was paid on CNTs because of their high thermal conductivity. Unfortunately making a uniform suspension of CNTs is difficult. A large number of researchers used a method which is so-called the two-step method. One of the most important advantages of the method, in comparison to the single-step method, is its efficiency in high-volume nanofluids production. Another eye-catching advantage is its low-cost. Making a production with uniform dispersion of Nano powder is the only advantage of the single-step approach, which does not meet in two-step method. Therefore (1) material selection, (2) synthesis of nanocomposite materials, (3) bonding of composite species, and (4) the usage of enough surfactant should be considered while preparing

FIGURE 2.32 Schematic example of (left) direct sonication and (right) indirect sonication.

FIGURE 2.33 Representation of nanofluid preparation by using an ultrasonic probe.

References

hybrid nanofluids. Adding nanoparticles has a negative effect of increasing the viscosity which leads to an increase in pressure loss and, subsequently, increasing of pumping power. Based on their physical and chemical properties, nanoparticles could be formulated in different ways. There are numerous ways for the synthesis of magnetic nanoparticles, including synthesizing in liquid, in solid and in gas, among which, in-liquid synthesis method is more applicable. In the past decade, most efforts have focused on the development of methods that lead to shape-controlled and stable nanoparticles production. In-liquid synthesizing method for the production of nanoparticles has many types such as coadsorption methods, microemulsions, thermal decomposition, hydrothermal, sonolysis and microwave methods, among which both coadsorption and hydrothermal are the most widely used in nanoparticles, respectively. Increasing the solid volume fraction of hybrid nanoparticles can increase its thermophysical properties including thermal conductivity, viscosity, heat capacity, and density. Increasing the temperature increases both the heat capacity and the thermal conductivity, also it decreases both the viscosity and the density. It should be noted that increasing the temperature and solid volume fraction do not have an ever-increasing effect on the favorable parameters. In fact, optimum values exist which discovering those is still under investigation. To date, the presented classical models cannot provide an accurate approximation for the calculation of thermal conductivity and viscosity. On the other hand, although several empirical models have been proposed to predict these two properties, they are still not sufficiently accurate. Most of the studies in the field of hybrid nanofluids have focused on providing relationships to predict thermal conductivity and viscosity, however, few of them have been performed to calculate other properties of nanofluids. Thus it is necessary to conduct a comprehensive study on parameters such as density and heat capacity. It is worth noting that material selection and finding optimum values of each component for mixing is still an unanswered problem. Researches should be continued with more emphasis on the reduction of production costs. For design purposes, the development of theoretical models for predicting thermophysical properties such as thermal conductivity and viscosity for hybrid nanofluids should be considered as an important research priority.

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535.

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CHAPTER

Thermophysical and rheological properties of hybrid nanofluids

3 Hatice Mercan

Mechatronics Engineering Department, Faculty of Mechanical Engineering, Yildiz Technical University, Istanbul, Turkey

Chapter Outline 3.1 Thermal conductivity........................................................................................101 3.1.1 Measurement techniques ................................................................103 3.1.2 Theory ...........................................................................................104 3.1.3 Experimental results .......................................................................113 3.2 Viscosity .........................................................................................................117 3.2.1 Measurement techniques ................................................................117 3.2.2 Theory ...........................................................................................119 3.2.3 Experimental results .......................................................................123 3.3 Heat capacity ..................................................................................................127 3.3.1 Measurement techniques ................................................................127 3.3.2 Theory ...........................................................................................128 3.3.3 Experimental results .......................................................................129 3.4 Density ............................................................................................................130 3.4.1 Measurement techniques ................................................................130 3.4.2 Theory ...........................................................................................131 3.4.3 Experimental results .......................................................................131 3.5 Wetting ...........................................................................................................132 3.6 Comparison of unitary and hybrid nanofluids .....................................................132 3.7 Challenges and conclusions .............................................................................135 References .............................................................................................................136

3.1 Thermal conductivity The most important thermophysical property of any working fluid in a thermal system is the thermal conductivity. A working fluid with a higher value of thermal conductivity enhances the overall heat transfer rate and thus increases the Hybrid Nanofluids for Convection Heat Transfer. DOI: https://doi.org/10.1016/B978-0-12-819280-1.00003-3 © 2020 Elsevier Inc. All rights reserved.

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overall efficiency of the thermal system. Thermal conductivity is a measure of the ability of a material to conduct heat. Thermal conductivity varies significantly with temperature and composition of the working fluid. Traditional thermal systems have utilized working fluids made from conventional base fluids such as water and ethylene glycol (EG). With the advent of nanotechnology, newer thermal systems began utilizing working solutions that comprise nanoparticles. Some working solutions comprise one type of nanoparticle known as nanofluids, while other working solutions comprise hybrid nanofluids, that is, nanofluids that are made up of nanoparticles from two or more nanomaterials. Addition of nanofluids, especially hybrid nanofluids, to traditional base fluids has been found to significantly improve thermal conductivity of the working solution. Thermal conductivity of a hybrid nanofluid depends on multiple factors including mass fraction of the nanoparticles, type of nanoparticles, base fluid or base fluid compositions, and volume concentration of the nanoparticle. The improved thermal conductivity of a hybrid nanofluid is a result of increased Brownian motion within the working solution with nanoparticles. In turn, increased Brownian motion and kinetic energy change with increased molecular collision rate increases the probability of chain formation and thus the interaction rate between the base fluid and the nanoparticles therein. Increased interaction between the base fluid and the nanoparticles increases the frequency of the lattice vibration because of the reduced particle distance [1]. By increasing molecular interactions within the working solution, nanoparticles enhance the thermal conductivity of the working solution significantly. As a result, compared to the base fluids they were made from, hybrid nanofluids have notably high thermal conductivity. The concentration of nanoparticles in a working fluid significantly affects the thermal conductivity of the working fluid. In most instances there is a direct correlation between the concentration of nanoparticles and the thermal conductivity. However, the increase in thermal conductivity based on nanoparticle concentration is not linear. Beyond a saturation point, the increase in thermal conductivity reaches a plateau. Beyond that saturation concentration, the effect can even be reversed due to clustering effects. The increased concentration reduces the stability of the hybrid nanofluid which reduces the thermal conductivity in longer operation periods. Some of the negative effects of high concentration nanoparticles on the stability of hybrid nanofluids can be remedied by using different techniques for preparing the hybrid nanofluids. For instance, a singlestep method of hybrid nanofluid preparation improves the stability and reduces the preparation time considerably compared to a two-step method. Alternatively stability, and thus the thermal conductivity, of a hybrid nanofluid can be increased by optimizing the sonication time and the ultrasonic vibration of the nanoparticles during preparation. Another possible way to increase the stability of a hybrid nanofluid is by surfactant addition, which affects the thermal conductivity in different ways and should be considered separately. In this section, the measurement techniques used in thermal conductivity of hybrid nanofluids, the theoretical background, and experimental results are discussed in detail.

3.1 Thermal conductivity

3.1.1 Measurement techniques The thermal conductivity of a material depends on the grain size, grain boundary, surface interaction, temperature, and the additives. The thermal conductivity of the nanoparticles and the hybrid nanofluids can be measured using a variety of techniques, which can be summarized as follows. T-type probe method is widely used to measure the thermal conductivity of nanoparticles such as nanotubes, nanowire, and carbon nanotubes (CNTs) [2,3]. In the T-type probe method, a suspended probe wire, often made up of platinum, is used as a heater. In some embodiments of the method, the same probe wire is also used as a thermal sensor. The probe wire is heated by a low-frequency alternating current source. At the same time, a lock-in amplifier is used to measure a third harmonic voltage across the wire. The thermal conductivity of the nanomaterial is calculated using an analytic model which relates the drop in spatially averaged temperature of the wire to that of the sample [4]. Thermal conductivity values for the nanoparticles and base fluids mostly used in hybrid nanofluids are listed in Table 3.1 [5]. The thermal conductivity of hybrid nanofluids can also be measured by the steady-state parallel plate method [6,7], the 3ω method [8
10], or the transient hot wire method [11
18]. In the steady-state plate method, the fluid sample is heated in all directions to maintain a steady temperature and wellknown simple and reliable governing equations are used to evaluate the thermal conductivity. Maintaining the steady-state conditions is time consuming and at high temperature levels the natural convection is inevitable in nanofluids. For these reasons, the steady-state parallel plate method is not preferred by many researchers. The 3ω method is used to measure the thermal conductivities of liquids and solids in thin layers. This procedure involves a metal filament which acts like a heater and thermometer. The heating of the thin layer is done periodically with an AC current. The measured response of the temperature oscillations and the frequency response are used to determine the thermal conductivity of the specimen. The most reliable thermal conductivity measurement technique for viscous fluids is the transient hot wire method, which is also used in majority of the experimental studies for unitary and hybrid nanofluids discussed in this chapter. The technique is based on recording the temperature change of a wire submerged in a hybrid nanofluid container where the bowl is enclosed by a constant temperature bath. During the measurement, the wire acts like a warmer and a thermometer at the same time. This technique is very precise and fast. In the literature, the KD2-pro thermal property analyzer with single needle (KS1—1.3 mm diameter 3 6 cm long, 6 5% to 6 0.01% accuracy in thermal conductivity) is used by many researchers to measure the hybrid nanofluids thermal conductivity [11
18]. During calibration, the base fluid is used, and the results are compared with the values from theoretical studies [19,20].

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Table 3.1 Thermal conductivity values of commonly used nanoparticles, metal oxides, carbon materials, and working fluids at room temperature. Nanoparticle

Thermal conductivity (W/m K)

Ti Zr B Pb Pt Fe Zn Si Mg W Al Au Cu Ag SiO2 TiO2 Al2O3 BeO SiC Si3N4 C CNT Diamond Engine oil Ethylene glycol Glycerin Water

21.9 22.7 27 35.3 71.6 80.2 116 148 156 174 237 317 401 429 1.38 8.4 36 272 490 16 1.6 2000
6000 2300 0.145 0.252 0.286 0.613

3.1.2 Theory Thermal conductivity of hybrid nanofluids depends strongly on the type and the composition of the base fluid, the type, the combination and the composition of the nanoparticles, the temperature, the volume concentration, the particle size, and the particle shape. The most common base fluids for hybrid nanofluids are water, EG, water and EG mixture, vegetable oil, transformer oil, diathermic oil, 10 W40 engine oil, and SAE oil [1]. Most common hybrid nanoparticles used in hybrid nanofluids include: Ag/GNP, Ag/WO3, Ag/Si, Ag/MgO, Ag/ ZnO, Al/Zn, Al2O3/Cu, Al2O3/CNT, Al2O3/CuO, Al2O3/graphene, TiO2/SiC,

3.1 Thermal conductivity

TiO2/Cu, TiO2/ZnO, TiO2/SiO2, TiO2-CuO/C, TiO2/Ag, TiO2/CNT, TiO2/multiwall carbon nanotube (MWCNT), MWCNT/Al2O3, MWCNT/graphene oxide (GO), MWCNT/Si, MWCNT/ZnO, MWCNT/Ag, MWCNT/SiO2, MWCNT/ Fe3O4, MWCNT/MgO, SiO2, GNP, DWCNT/ZnO, CNT/Fe3O4, Ni/ND, GNP/ Pt, and Co3O4/ND [1]. In early studies, thermal conductivity of hybrid nanofluids was approximated using a modified form of the thermal conductivity models proposed for the unitary nanofluids. The thermal conductivity of the hybrid nanofluids can be written as a function of particle volume fraction, temperature, shape of the particles (e.g., spherical, cylindrical, platelets, or blades), pH value, nanolayer thickness, and Brownian motion of the randomly moving particles. The Maxwell model considers the effect of volume fraction for spherical particles and modified Maxwell model for hybrid nanofluids can be written as [14,20]: 2


ðφnp1 knp1 1 φnp2 knp2 Þ 1 2kbf 1 2 φnp1 knp1 φ khnf 5 kbf 4 ðφ knp1 1 φ knp2 Þ
np1 np2 1 2kbf 2 φnp1 knp1 φ

3  1 φnp2 knp2 2 2φkbf 5  1 φnp2 knp2 1 φkbf

(3.1)

where φ is the solid volume fraction, φ 5 φnp1 1 φnp2 , and k is the thermal conductivity. The subscripts hnf is the hybrid nanofluid, np1 and np2 are the nanoparticles, and bf is the base fluid. The Hamilton and Crosser model [21] defines a shape factor n 5 3=ϕ, where sphericity ϕ is 1 for spherical particles, and defined as the ratio of the surface area of the sphere and the surface area of the nanoparticle with equal volume. The sphericity of 1:1/8 aspect ratio platelet is ϕ 5 0:52, the sphericity 1:8 aspect ratio cylinder is ϕ 5 0:62; and the sphericity 1:1:1 aspect ratio brick is ϕ 5 0:81. The modified hybrid nanofluid Hamilton and Crosser model [22
25] is represented as:
 knp2 1 ðn 2 1Þkbf 2 ðn 2 1Þφ2 kbf 2 knp2 khnf
 5 ; kbf knp2 1 ðn 2 1Þkbf 1 φ2 kbf 2 knp2
 knp1 1 ðn 2 1Þkf 2 ðn 2 1Þφ1 kf 2 knp1 kbf
 5 kf knp1 1 ðn 2 1Þkf 1 φ1 kf 2 knp1

(3.2a)

(3.2b)

The Yu-Choi model [26] considers the ratio of nanolayer thickness to the nanoparticle radius, where the nanolayer thickness has a significant impact on the thermal conductivity with smaller particle radius, such as r , 5 nm. The thermal conductivity with clustering effect taken into account can be represented as [18,23]:
 knp2 1 2kbf 2 2φ kbf 2 knp ð11βÞ3 khnf
 5 kbf knp2 1 2kbf 2 φ kbf 2 knp ð11βÞ3

(3.3)

where β is the clustering effect. However, the modified classical models for hybrid nanofluids considerably miscalculate the thermal conductivity,

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particularly for higher concentration values. In addition, these models are for mixtures in thermal equilibrium and do not consider the strong effect of temperature on thermal conductivity. The thermal conductivity comparison of Al2O3-Cu/EG hybrid nanofluid for a ratio of 50:50 and at 0.125
2.0 vol.% at 25 C
50 C revealed that the classical models underestimate the thermal conductivity for increasing temperature and concentration values compared to experimentally measured data [27]. The comparison of theoretical values and experimental observations for Al2O3-CuO/water hybrid nanofluid reports similar trends for increasing concentrations [22]. The thermal conductivity increases with increasing molecular diffusion, the frequency of lattice vibration, and the kinetic energy, which are the consequences of temperature increase and concentration level. Majority of thermal conductivity relations for hybrid nanofluids available in the literature makes use of the curvefitting technique, which generates a function of concentration and temperature. The fundamental limitation of functions obtained through curve-fitting is that they are accurate for only a specific type of hybrid nanofluid, a specific concentration and temperature interval. On the other hand, curve-fitting methods and experimental observations from the same hybrid nanofluids usually show a rather good agreement. A representative list for the thermal conductivity relations from the literature is given in Table 3.2. Thermal conductivity is affected by the nanoparticle size and the shape of the nanoparticles used. Depending on the manufacturing techniques of the nanoparticles the average particle size and shape can differ even for the same type of nanoparticle. For instance, Ag can have 90
210 nm diameter with a spherical morphology as well as 80, 40, 35, and 20 nm diameters. Another frequently used nanoparticle Si can have 30
50 and 50
100 nm diameter measures. It has been observed that smaller size nanoparticles enhance the thermal conductivity more significantly. The thermal conductivity behavior of Al2O3CuO nanofluid is investigated for 21 C
51 C temperature range [42]. The temperature rise enhanced the thermal conductivity for every concentration and nanoparticle selection. The size of the nanoparticle Al2O3 (38.4 nm) is greater than CuO (23.6 nm). The nanoparticles with smaller size enhanced the thermal conductivity more at both high temperatures and high concentrations. On the other hand, for bigger nanoparticle sizes an increase in the concentration exhibits a reverse effect, where the thermal conductivity does not increase as the concentration increases. The Hamilton and Crosser model which is initially defined for unitary nanofluids and generalized to hybrid nanofluids (Eq. 3.2) takes into the account the nanoparticle shape effect by introducing a shape factor (n) and sphericity (ϕ). However, the modified version of Hamilton
Crosser model failed to estimate the thermal conductivity of hybrid nanofluids in an accurate manner. In the study by Sahoo et al. [43] the effects of shape and surface factors on thermal conductivity are investigated for Al2O3-CuO/EG
PG (propylene glycol) hybrid nanofluids with binary base

Table 3.2 Thermal conductivity relations from the literature. Hybrid nanoparticles, concentrations, ratios, and temperature range CNT-Al2O3/water, 0.02%
1% [11]

CNT-Al2O3/water, 0.02%
1%, 303K
332K [11] Zn-TiO2/EG, 0%
3.5%, 25
50 C [28] MgO-FMWCNT/EG, 0.05%
0.6%, 25 C
50 C [29] Al2O3-MWCNT/oil, 0.125%
1.5%, 25 C
50 C [30] Al2O3-Cu (50:50) /EG, 0.125%
2%, 25 C
50 C [27] SiC-TiO2/diathermic oil, 20 C, 0.1%
1% [31] SiO2-TiO2 (20:80, 40:60, 50:50, 60:40, and 80:20) /water, 1%, 30 C
80 C [12] ZnO-Ag (50:50)/water, 0.125%
2%, 25 C
50 C [13] TiO2-SiO2 50:50/water
EG, 60:40, 30 C
70 C, 0.5%
3% [14] CuZn 50:50/vegetable oil, 0.1%
0.5%, 30 C
60 C [15]

Thermal conductivity of the hybrid nanofluids khnf 5 1 1 Aφ 1 Bφ2 1 cφ3 1 Dφ4 kf T (K)

A

B

C

D

303 314 323 332

0.1767 0.2037 0.3606 0.4252

20.1365 20.255 20.5755 20.8242

20.024 0.1386 0.2676 0.6995

0.1058 0.0507 0.1138 20.1201

khnf 2 214:83 1 T 227:69 1 5 346:58 1 106:98φ T kf khnf 0:8717 0:7972 5 1 1 0:004503φ T kf khnf 5 0:8341 1 1:1φ0:243 T 20:289 kf khnf 5 0:1534 1 0:00026T 1 1:1193φ khnf 9:6128 1 φ 0:0041099 5 2 9:3885 2 0:00010759T 2 φ kf khnf 2 kf 5 6:06φ 1 2:72 kf  0:0437 khnf T , where R is the volume fraction of TiO2 in the mixture 5 1:17ð11RÞ20:1151 80 kf khnf 5 1 1 0:0008794φ0:5899 T 1:345 kf     khnf φ 5:5 T 0:01 5 11 0:11 100 80 kf khnf 5 0:7054 1 0:009896T 1 0:8717φ 2 6:479 3 1025 T 2 1 0:09749Tφ 2 4:714φ2 2 0:0002718T 2 φ kf 2 0:1174Tφ2 1 10:09φ3 (Continued)

Table 3.2 Thermal conductivity relations from the literature. Continued Hybrid nanoparticles, concentrations, ratios, and temperature range CuZn 75:25/vegetable oil, 0.1%
0.5%, 30 C
60 C [15] CuZn 25:75/vegetable oil, 0.1%
0.5%, 30 C
60 C [15] TiO2-CuO/C
EG, 0%
2%, 313.4K [16] MWCNT-MgO 20:80/water
EG 50:50, 0.015%
0.96%, 30 C
50 C, modified Jang-Choi model [17] AlN-Al2O3/water, 1%
4% [32] Ag-MgO (50:50)/water, 0%
0.03% [33] MWCNTS-Al2O3/EG 0.02%
0.8%, 25 C
50 C, [34] Alumina-silica/water 75:25, 0.2% [35] MWCNTS-Al2O3/EG 0.02%
0.8% [36]

Thermal conductivity of the hybrid nanofluids khnf 5 0:9842 2 0:0008376T 2 2:121φ 1 2:677 3 1025 T 2 1 0:1497Tφ 1 2:653φ2 2 0:0006927T 2 φ kf 2 0:1386Tφ2 1 2:1φ3 khnf 5 1:321 2 0:01661T 2 4:723φ 1 0:000199T 2 1 0:2473Tφ 1 3:689φ2 2 0:001766T 2 φ 2 0:1222Tφ2 2 0:1045φ3 kf     φ 0:9371 T 10:2685 khnf 5 1 1 6:2299 100 333

 
 2 2 1 0:000183φ0:5 khnf 5 cos θ βkfiber φfiber 1 1 2 φfiber kbf 1 0:0026log φ0:5 particle T particle knp T 2 0:002157 ,  2 where cos θ 5 1, 1.3, 1 corresponds the best direction, 1.3 corresponds the random direction for MWCNT, and β is the Kapitza resistance and for water
EG mixture β 5 0:0012 " #        khnf φ 1:37 Tnf 0:2777 dp 20:036 αp 0:1737 5 0:8938 11 11 11 100 kbf 70 150 αbf khnf 0:1747 3 105 1 φ 5 5 kbf 0:1747 3 10 2 0:1498 3 105 φ 1 0:1117 3 107 φ2 1 0:1997 3 108 φ3 khnf 5 0:00281 1 5:28956 3 1024 T 1 0:17384φ 1 5:31721 3 1023 Tφ 2 0:23762φ2 2 5:06549 3 1023 Tφ2 kf 1 0:19937φ3 khnf 5 2 15:554φ2 1 2:0513φ 1 1:0091 kf khnf T 5 25 C 5 1 1 0:1499φ0:5 kkhnf f  T 5 30 C 5 1 1 0:1549φ0:5 kkhnf f  T 5 35 C 5 1 1 0:1593φ0:5 kkhnf f  T 5 40 C 5 1 1 0:1706φ0:5 kkhnf f  T 5 45 C 5 1 1 0:1879φ0:5 kkhnf f  T 5 50 C 5 1 1 0:1929φ0:5 kf

Al2O3-TiO/water [18] Al2O3-TiO/water [18] 0.5 vol.% Al2O3-TiO/water [18]

Al2O3-TiO/water, 273.15K
323.15K [18] CuO-MgO-TiO2/water, 15 C
60 C,0.1%
0.5% [37] MgO-MWCNT/EG, 0.05%
0.6%, 25 C
50 C[38] Al2O3-Fe2O4/10 W40 oil, 0.25
4 wt.%, 25 C
65 C [39] Al2O3-SiO2/water, 1%
3% [40] Al2O3-SiO2/water, 20 C
50 C [40]

SiO2-oleic acid/liquid paraffin, 0.005
5 wt.%, 25 C
75 C [41]

khnf 5 1:74φ 1 1:11 kf khnf 5 0:995 1 10:097φ1 2 120:835φ21 1 023:227φ2 2 43:648φ22 1 22380:35φ32 kf 0.5%TiO k 5 0:0032T 2 0:3063 1.0%TiO k 5 0:0033T 2 0:3343 1.5%TiO k 5 0:0034T 2 0:3538 2.5%TiO k 5 0:0034T 2 0:3538 khnf 5 2 0:347 1 0:003T 1 6:639φtot 2 109:024φ2tot 2 9:6816854 283:69209 2 4718:8713 43232:493 2 175433:68 1 khnf 5 0:72768391 1 1 1 1 1 274:276φ T T2 T3 T4 T5 2 159781:42φ2 1 41691000φ3 2 3:6405833 3 109 φ4
 khnf 5 0:9787 1 exp 0:3081φ0:158 2 0:002T kbf khnf 5 0:113 1:011T  w0:376 1 0:921 kbf 20 C , T , 50 C, khnf 5 0:474 1 0:006T 2 0:00005T 2 1 0:041φtot T 5 25 C, khnf 5 0:607 2 0:005φ1 1 0:0009φ21 1 0:109φ2 2 0:059φ22 1 0:013φ32 0.5% Al2O3 1 0.5% SiO2 khnf 5 0:3105 1 0:0018T 0.5% Al2O3 1 1.0% SiO2 khnf 5 0:5963 1 0:0031T 0.5% Al2O3 1 1.5% SiO2 khnf 5 0:5945 1 0:0036T 0.5% Al2O3 1 2.5% SiO2 khnf 5 0:6114 1 0:0034T khnf 5 0:756951 1 0:00735396w 2 8:26715 3 1025 T 2 1 0:0123973T , where w is mass concentration (wt.%) kbf

EG, Ethylene glycol; MWCNT, multiwall carbon nanotube.

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CHAPTER 3 Thermophysical and rheological properties

fluid. The thermal conductivity functions for the hybrid nanofluids with binary base fluid for different particle shapes are provided as [43]: Platelets with 1:1/8 aspect ratio: khnf 5 1 1 ð2:61Þφ kbf

(3.4)

Blades with 1:6:1/12 aspect ratio: khnf 5 1 1 ð2:74Þφ kbf

(3.5)

Cylindrical with 1:8 aspect ratio: khnf 5 1 1 ð3:95Þφ kbf

(3.6)

Bricks with 1:1:1 aspect ratio: khnf 5 1 1 ð3:37Þφ kbf

(3.7)

where φ is the total concentration of the nanoparticles. The nanoparticles can be ordered by shape from higher to lower thermal conductivity as spherical, cylindrical, bricks, blades, and platelets shape [43,44]. The difference between the thermal conductivity of spherical nanoparticle and platelet-shaped nanoparticles nanofluid is around 1.8% [43]. In the numerical simulations, for the thermophysical properties of the hybrid nanofluids, both classical models [45,46] and empirical relations [33,47
50] are used. The complicated physical problems such as the effect of nanoparticle shape [44], the boundary layer [45], the effects of magnetohydrodynamics (MHD) [33] on the heat transfer characteristics are extensively studied through numerical simulations. For instance, in the numerical study by Dinarvand and Rostami [44], the modified Hamilton
Crosser model for thermal conductivity is used to investigate the effects of the nanoparticle shape for the ZnO-Au/ water hybrid nanofluid under von Karman’s swirling flow. They reported a successful prediction for the heat transfer characteristics of the hybrid nanofluids. In the existence of the free convection, Kumar et al. [45] numerically investigated the Blasius and Rayleigh
Stokes flow for Fe2O3-Se/water hybrid nanofluid, where the thermal conductivity is defined using the modified Hamilton and Crosser model. The numerical investigation reported by Ghalambaz et al. [46] for the flow of Cu-Al2O3/water hybrid nanofluids in an equally divided cavity under MHD natural convection effects, where the classical Maxwell model and the classical Bruggeman model are used for the thermal conductivity. Both models failed to predict the real values of the hybrid nanofluid. For that reason, in the study by Ghalambaz et al. [46] the experimental measurements are used for the thermal conductivity. In the numerical study by Kaska et al. [47], the heat transfer enhancement of AlN-Al2O3/water hybrid nanofluid

3.1 Thermal conductivity

is investigated. A good agreement with the literature is reported. The empirical relations for the thermophysical properties are adopted from the experimental study by Sharma et al. [32]. The MHD effects on Ag-MgO/water hybrid nanofluid are investigated numerically in terms of heat transfer and entropy generation for a low concentration mixture [33]. Another numerical study is carried out by Ghalambaz et al. [48] for the same Ag-MgO/water hybrid nanofluid for conjugate natural convection flow in a square cavity. Both of the studies [35,36] used the correlations of Esfe et al. [51] for the same hybrid nanofluid and validated their results for a wide range of nondimensional parameters relevant to their analysis. Huminic and Huminic [49] simulated the GO-Co3O4/ water hybrid nanofluid in different cross-sectional ducts for laminar flow. In their analysis they implemented the thermal conductivity relation proposed by Sundar et al. [52]. In the numerical study by Alsarraf et al. [50], the effect of magnetic field on convective heat transfer for a laminar flow of MWCNTFe3O4/water hybrid nanofluid is considered for heated tube. The complicated physics of the considered problem is investigated for a large parameter range where the characteristics of the hybrid blend is introduced from experimental measurements for each case. The thermophysical properties for all combinations and concentrations are experimentally measured, tabulated, and used. In a series of studies, Esfe et al. [34,53
56] compared their experimental results with an artificial neural network (ANN) model for different types of hybrid nanofluid blends, concentrations, and temperature values where they showed a better agreement with the experimental observations and the ANN model. Similar observations are reported by Vafaei et al. [38] and Rostamian et al. [57]. The stability of the suspensions depends on preparation and choice of the nanoparticles and improves the thermal conductivity of the hybrid nanofluid significantly. The elongated stability is desired for a nanomixture. To prevent sedimentation and thus maintain the stability of the hybrid nanofluids, surfactants such as Oleic Acid, SLS, Gum Arabic, NanoSperseAQ, cetrimonium bromide (CTAB), sodium deoxycholate (SDC), sodium dodecylbenzenesulfonate (SDBS), and PEG are used as cheap and effective methods [1]. The surfactants can also be categorized based on their head compositions: nonionic, anionic, cationic, and amphoteric [58]. Additionally controlling the pH level and defining the most efficient or stable pH value help enhancing the stability. And finally ultrasonic vibration and sonication time enhance the mixing in the suspension and thus improve the stability of the hybrid nanofluid. The thermal conductivity of hybrid nanofluids is greater than unitary nanofluids. Only hybrid nanofluids from improper permutation of nanoparticles result in lower values of thermal conductivity. The kind of the base fluid also affects thermal conductivity of the final nanofluid. Water as a base fluid exhibits higher thermal conductivity compared to EG, and the mixed water
EG base fluids display higher thermal conductivity as the water ratio increases (see Table 3.3 [28]). The thermal conductivity of a nanofluid is higher when the average size of

111

Table 3.3 Thermal conductivity of GO/Co3O4 hybrid nanofluids at different temperatures and different base fluid combinations [52]. φ

Water

Temperature 5 20 C EG 20EG:80W 40EG:60W

0.0% 0.05% 0.10% 0.15% 0.20%

0.602 0.619 0.625 0.634 0.648

0.258 0.265 0.269 0.271 0.273

0.492 0.502 0.512 0.524 0.528

EG, Ethylene glycol; GO, graphene oxide.

0.404 0.409 0.419 0.428 0.431

60EG:40W

Water

0.334 0.340 0.345 0.348 0.356

0.653 0.709 0.734 0.756 0.778

EG

Temperature 5 60 C 20EG:80W 40EG:60W

60EG:40W

0.270 0.282 0.291 0.295 0.302

0.530 0.572 0.588 0.601 0.619

0.350 0.368 0.376 0.384 0.402

0.430 0.457 0.472 0.485 0.496

3.1 Thermal conductivity

FIGURE 3.1 Comparison of thermal conductivity for increasing temperature for different hybrid nanofluids [14].

nanoparticles is smaller. The small size enhances the kinetic energy and results a higher rate of collision. In terms of the shape, the cylindrical particles exhibit better performance compared to spherical particles [36]. Nanofluids commonly display higher thermal conductivity with increasing temperatures. Similarly nanofluids have higher thermal conductivity when the concentration of nanoparticles in the fluid is increased (see Figs. 3.1 [28], 3.2 [29] and Table 3.3 [28]).

3.1.3 Experimental results The experimental studies on thermal conductivity of hybrid nanofluids focus on parameters that affect thermal properties, such as temperature, concentration of the nanoparticles, the composition of the nanoparticles, the type of the nanoparticles, and the type of the base fluid. In the experimental study by Moldoveanu et al. [40], the simultaneous effect of volume fraction and temperature on thermal conductivity is shown in 3D analysis for alumina-silica hybrid nanofluid (see Fig. 3.3A). Furthermore the effect of composition is investigated and it is shown that the increase in the thermal conductivity is more sensitive to the fraction of silica when compared with alumina. The 3D analysis is shown in Fig. 3.3B. The authors concluded that the relation between temperature rise and thermal conductivity rise is linear thus enabling the estimation of thermal conductivity for a specific hybrid nanofluid as a linear function of temperature. The linear relation of temperature and thermal conductivity for hybrid nanofluids is shown in Fig. 3.4 [40].

113

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CHAPTER 3 Thermophysical and rheological properties

FIGURE 3.2 Change of the ratio of thermal conductivity of 10 W40/Al2O3-Fe2O4 hybrid nanolubricant oil for increasing weight concentration and temperature—comparison of experimental results and proposed correlation [39].

The stability of the hybrid nanofluid affects the long-term thermal conductivity performance significantly. Sedimentation, agglomeration, and low structural integrity are the unwanted consequences of an unstable blend. The samples are rested for 30 days and a naked eye observation shows the color change in the blend, which is used as a measurement technique for the hybrid nanofluid stability [59]. In the study by Shahsavar and Bahiraei [59], tetramethylammonium hydroxide is used to coat Fe3O4 and Gum Arabic is used to coat CNT in a water base hybrid nanofluid, where no sedimentation is observed after 30 days, indicating a stable suspension. The comparison of CTAB, SDC, and SDBS as stabilizing surfactant for TiO2-GNP/Dw-EG hybrid nanofluid revealed the considerable improvement of CTAB, being a stable mixture up to 40 days with minimum sedimentation [60]. The MWCNTs-iron (III) oxide (MWCNTs-Fe2O3)/water hybrid nanofluid reached 60 days of stability with NanoSperseAQ surfactant and 1 hour of sonication time [61]. On the other

3.1 Thermal conductivity

FIGURE 3.3 3D analyses of experimental results of the silica alumina hybrid nanofluid (A) the effect of temperature and total concentration and (B) the effect volume fraction of silica and alumina on thermal conductivity [40].

115

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CHAPTER 3 Thermophysical and rheological properties

FIGURE 3.4 Thermal conductivity variations with temperature for different hybrid nanofluids [53].

hand for Al2O3-Cu/EG hybrid nanofluid ended up with 3 days of stability after 7 hours of sonication without surfactant addition [27]. As mentioned previously the type of nanoparticles also affects thermal conductivity. In the experimental study by Arani and Pourmoghadam [36], the comparison of Fe2O3-MWCNT/EG hybrid nanofluid and Al2O3-MWCNT
EG hybrid nanofluid at the same volumetric concentration (0.8%) for increasing temperature was made, and Al2O3 blend showed significantly higher thermal conductivity performance. The good stability and dispersion of Al2O3 and higher thermal conductivity of MWCNT facilitated the combination to have better thermophysical qualities [36]. Bhattad et al. [62] investigated experimentally the hydrothermal properties of different alumina hybrid nanofluids. The comparison of deionized water hybrid blends of Al2O3SiC, Al2O3-AlN, Al2O3-MgO, Al2O3-CuO, and Al2O3-MWCNT was investigated experimentally for 4:1 ratio with 0.1% concentration for a temperature range of 10 C
25 C. They concluded that Al2O3-MWCNT/DI water hybrid nanofluid with a highest augmentation around 31.2% can be considered as a good candidate of hybrid nanofluid for a better thermal performance. Nabil et al. [14] compared the thermal conductivity of three different hybrid nanofluids using the same base fluid mixture of 50:50 water
EG. The compared

3.2 Viscosity

nanoparticle couples were TiO2-SiO2, Al2O3-G, and fMWCNT-Fe3O4 for increasing temperature values. For all three hybrid nanofluids a rise in thermal conductivity was observed with increasing temperature. The thermal conductivity placement was kTiO22SiO2 , kAl2O32G , kfMWCNT2Fe3O4 , see Fig. 3.1. This result is originated from the considerably high thermal conductivity of nanoparticles, CNT compared to TiO2, SiO2, Al2O3, and G (see Table 3.1).

3.2 Viscosity Viscosity of hybrid nanofluids plays a critical role in evaluation of the pumping power requirements due to frictional effects. Viscosity of hybrid nanofluids, similar to their thermal conductivity, strongly depends on temperature, concentration, shape, and size of nanoparticles. The rise in temperature decreases the viscosity, rise in particle concentration increases the viscosity and small spherical morphology reduces the viscosity. In Table 3.4, the change in viscosity values for GO-Co3O4 hybrid nanofluids with a water based, EG based, and mixture of water and EG at different ratios is tabulated. An increase in the concentration of nanoparticles increased the viscosity, while a temperature rise caused a reduction. Water-based mixture showed significantly low viscosity compared to EG as a base fluid. Similarly higher water ratios also resulted in lower viscosity values [52]. These results are typical observations for majority of hybrid nanofluid viscosity behavior.

3.2.1 Measurement techniques Different rheometers are used to measure the viscosity of hybrid nanofluids. While measuring viscosity, it is important to reveal whether the fluid behavior is Newtonian or non-Newtonian. A Newtonian fluid exhibits a linear relation between shear stress and strain rate at a given temperature, whereas a nonNewtonian fluid displays a nonlinear relation between these two values. The viscosity of a Newtonian hybrid nanofluid changes with temperature and concentration, whereas the non-Newtonian viscosity is mainly a function of strain rate and relaxation time. To assess whether a hybrid nanofluid displays Newtonian or non-Newtonian properties, measurements are done over a range of shear rate and temperature. Some commercial rheometers used in hybrid nanofluid measurements are Brookfield LVDV III Ultra Rheometer [12], Brookfield DV3T digital viscometer [14], Paar PhysicaMCR 300 [59], Anton Paar MCR92 with concentric cylinder (CC39) [60], SN634038, A&D vibro viscometer-Japan [17], and CAP 2000 cone and plate viscometer by Brookfield [63]. The accuracy of the measurements is calibrated using the base fluids and comparing the experimental deviation, typically 6 1%, with the data of American Society of Heating, Refrigerating, and Air Conditioning Engineers (ASHRAE) [20] handbook. In Fig. 3.5, the change in

117

Table 3.4 Viscosity of GO/Co3O4 hybrid nanofluids at different temperatures and different base fluid combinations [52]. Temperature 5 20 C 20EG:80W 40EG:60W

φ

Water

EG

0.0% 0.05% 0.10% 0.15% 0.20%

0.79 0.85 0.92 1.04 1.18

20.9 21.5 22.6 23.8 25.6

1.55 1.71 1.86 2.06 2.35

EG, Ethylene glycol; GO, graphene oxide.

2.94 3.02 3.21 3.45 3.56

60EG:40W

Water

EG

Temperature 5 60 C 20EG:80W 40EG:60W

60EG:40W

5.75 6.23 6.56 6.89 7.12

0.24 0.28 0.32 0.37 0.41

5.21 5.72 6.32 6.93 7.42

0.63 0.68 0.73 0.78 0.86

1.62 1.76 1.84 1.98 2.13

1.18 1.23 1.34 1.45 1.58

3.2 Viscosity

FIGURE 3.5 Comparison of dynamic viscosity of base fluid and increasing concentration for increasing temperature (TiO2-SiO2 50:50/water
EG) [14]. EG, Ethylene glycol.

dynamic viscosity with increase in the temperature is shown. The measurement of base fluid (water/EG) is compared and thus validated with ASHRAE handbook.

3.2.2 Theory Viscosity relation models that work well for suspensions do not precisely estimate the viscosity values for hybrid nanofluids. It is not possible to obtain a general relationship for viscosity that is valid across a family of hybrid nanofluids, for a range of concentrations and over varying temperatures. This is because the behavior of the hybrid nanofluid changes with different concentration and temperature values, and it may show some viscoelastic features. To overcome this problem, the viscosity relations are generated for smaller groups of blends, as a function of temperature, concentration, as well as some power of rate of deformation. The behavior of Fe3O4-Ag/EG hybrid nanofluid changes to non-Newtonian beyond a concentration of 0.3 vol.% [64]. ZnO-MWCNT/engine oil mixture is a nonNewtonian hybrid nanofluid [65]. MgO-MWCNT/EG behaves as a Newtonian blend for 0.8%
1% concentration [66]. The classical viscosity models for nanofluids and suspensions are Einstein [67] μhnf 5 μbf ð1 1 2:5φÞ

(3.8)

119

120

CHAPTER 3 Thermophysical and rheological properties

Brinkman [68]  μhnf 5 μbf

1 ð12φÞ2

 (3.9)

Pak and Cho [69]
 μhnf 5 μbf 1 1 39:11φ 1 533:9φ2

(3.10)

μhnf 5 μbf ð1 1 10:6φ 1 ð10:6φÞ2 Þ

(3.11)

μhnf 5μbf ð1 1 2:5φ 1 6:2φ2 Þ

(3.12)

Chen et al. [70]

Batchelor [71]

where the hybrid blend is considered to be Newtonian and the viscosity is assumed to be a function of concentration only. The model of Sharma is a typical example, where viscosity is a function of temperature and concentration. Sharma et al. [16] μhnf 5 μbf

!     φ 1:1558 T 0:6801 0:9653 1 77:4567 100 333

(3.13)

The classical viscosity models for suspensions do not accurately estimate the experimental data for hybrid nanofluids. Researchers try to come up with new relations for better accuracy. In a study by Sahoo and Kumar [72], the comparison of experimental observations of the viscosity of Al2O3-CuO-TiO2/water ternary hybrid nanofluid with the models available in the literature shows that classical models such as Einstein, Brinkman, Pak, and Cho and hybrid nanofluid model of Sharma underestimate the viscosity value. On the other hand, the model of Chen overestimates the viscosity value of Al2O3-CuO-TiO2/water ternary hybrid nanofluid with a significant discrepancy, where the error grows with increasing concentration (see Fig. 3.6) [72]. A similar observation is reported by Asadi and Asadi [63], for MWCNT-ZnO/engine oil hybrid nanofluid. The comparison is performed for 25 C and 35 C for 0.125 , φ , 1 vol.%. Again, classical models such as Einstein, Wang, and Batchelor fail to predict the experimental results for temperature alteration. The representative list of hybrid nanofluid viscosity relation is given in Table 3.5 and the empirical relations are in a good agreement with experimental observations. The Newtonian viscosity relations of the hybrid nanofluids are related to concentration and temperature values; on the other hand, the non-Newtonian case viscosity relations of the hybrid nanofluids are related to the rate of deformation using consistency and power law indices. Both of these are defined using temperature and/or concentration, as in the model of Eshgarf et al. for MWCNTs
SiO2/ EG
water non-Newtonian hybrid nanofluid [73] in Table 3.5.

3.2 Viscosity

FIGURE 3.6 Comparison of classical models and (A) experimental results and (B) proposed correlation of dynamic viscosity and relative viscosity for increasing concentration at T 5 45 C for Al2O3-CuO-TiO2/water ternary hybrid nanofluid [72].

121

Table 3.5 The viscosity relations for hybrid nanofluids from the literature. Hybrid nanoparticles, concentrations, ratios, and temperature range TiO2-Cu/water (0.02%
0.02%) [23] AlN-Al2O3/water, 1%
4% [32] Ag-MgO (50:50)/water, 0%
0.02% [33] SiC-TiO2/diathermic oil, (20 C, 0.1%
1%) [31] SiO2-TiO2/water (20:80, 40:60, 50:50, 60:40, and 80:20, 1%, 30 C
80 C) [12] TiO2-SiO2 50:50/water
EG, 60:40 C
30 C
70 C, 0.5%
3% [14] TiO2-CuO/C
EG, 0%
2%, 313.4K [16] MWCNT-SiO2/water, 0.1%
3%, 20 C
50 C [72]

Viscosity relation μf μhnf 5 2:5 ð12φ1 Þ ð12φ2 Þ2:5       μhnf φ 11:3 Thnf 20:038 dp 20:061 5 11 11 11 100 μbf 70 170 μhnf 2 3 5 1 1 32:795φ 2 7214φ 1 71400φ 2 0:1941 3 108 φ4 μbf μhnf 5 0:312φ 1 1:3194 μf  0:2321 μhnf T 5 1:42ð11RÞ20:1063 80 μf     μhnf φ 1:59 T 0:31 5 0:1 11 0:11 100 80 μf  1:1558   φ T 0:6881 μhnf 5 0:9653 1 77:4567 100 333 Model 1 μhnf 5 15:88φ0:8514 T 21:189 γ_ 20:5639 Model 2 μ 5 mγ_ n21 where   1:083 2 0:03327T , consistency index m 5 0:02048 1 2:189exp 2 φ n 5 0:6868φ20:090620:001474T 2 0:006267T, power law index

MWCNT-SiO2 (50:50)/water
EG (50:50), 0.0625%
2%, 27.5 C
50 C [73]

SiO2-oleic acid/liquid paraffin, 0.005
5 wt.%, 25 C
75 C [41] Al2O3-CuO-TiO2/water,35 C
50 C, 0.01%
0.1%, 30 nm , Dp , 50 nm, ternary hybrid nanofluid [72] MWCNT-ZnO/engine oil, 0.125%
1%, 5 C
55 C [63] MgO-MWCNT/EG, 0.05%, 25 C
50 C [66] EG, Ethylene glycol; MWCNT, multiwall carbon nanotube.

μ 5 mγ_ n21 where  
 38:19 2 0:3T 0:01138φ 1 0:5529φ2 2 0:3613φ3 1 0:07φ4 , m 5 0:01125 1 7:655 1 0:6953T consistency index    2 3:03 1 1:418T
2 0:7366φ 1 0:8519φ2 2 0:4552φ3 1 0:08871φ4 , n 5 0:8543 1 15:8 1 0:391T power law index μhnf 5 6:8376 1 15:2522w 1 0:038779 2 2:63029w2 , where w is rhe mass fraction (wt.%) μbf !   φ φ 1:223 1 705 μTHNF 5μbf 0:955 2 0:00271T 1 1:858 100 100 2 196:9T 2 16:54φT pffiffiffiffi T


20:342 20:473 
 5 0:91φ 1 0:240 T φ exp 1:45T 0:12 φ0:158

μhnf 5 796:8 1 76:26φ 1 12:88T 1 0:7695φT 1 μhnf μbf

3.2 Viscosity

The shape of the nanoparticles and the base fluid type and the fraction affect the viscosity significantly. In the study by Sahoo et al. [43], the Al2O3-CuO/EGPG the effect of shape of the nanoparticles and fraction of the binary base fluid is investigated and the viscosity relation for the hybrid nanofluid is Platelets μhnf 5 1 1 37:1φ 1 612:6φ2 μbf

(3.14)

μhnf 5 1 1 14:6φ 1 123:3φ2 μbf

(3.15)

μhnf 5 1 1 13:5φ 1 904:4φ2 μbf

(3.16)

μhnf 5 1 1 1:9φ 1 471:4φ2 μbf

(3.17)

Blades

Cylindrical

Bricks

As the EG mass fraction in a hybrid nanofluid increases the viscosity of the nanofluid linearly. At about 50% EG, the viscosity reaches a maximum. Beyond 50% EG, the viscosity of the hybrid nanofluid starts to drop. Increase in the mass fraction of PG increases the viscosity of the hybrid nanofluid significantly. However, the analysis reveals an optimum mass fraction for the EG
PG binary base fluid of around 30%. This value results in the lowest viscosity value, which can be considered as a candidate mixture for a real life application. The order of the shape of the particles from lowest to highest viscosity can be listed as spherical, brick, cylindrical, blade, and platelet. For the increasing PG fraction, the changes in viscosity become more pronounced. In Section 3.1.2 the spherical-shaped nanoparticles have been listed as having higher thermal conductivity properties. Additionally as discussed in Section 3.2.2 the same shape nanoparticles also result in lower viscosity. These are ideal attributes for a working fluid in a thermal system.

3.2.3 Experimental results One common observation for the dynamic viscosity of the hybrid nanofluids is that, the viscosity decreases with increasing temperature. This trend is observed for water-based hybrid nanofluids [52,58,61,74
78], EG-based hybrid nanofluids [58,64,66,79
81], oil-based hybrid nanofluids [40,41,58,65,66,81], and water
EG mixtures [14]. In Fig. 3.5, for increasing concentration of TiO2-SiO2 50:50/ water
EG hybrid nanofluid the decrease in dynamic viscosity is observed [14]. In Fig. 3.7, the decrease in dynamic viscosity for increasing temperature is observed

123

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CHAPTER 3 Thermophysical and rheological properties

FIGURE 3.7 Viscosity of hybrid nanofluids for increasing temperature and volume fraction [82].

for Al2O3-CuO-TiO2/water ternary hybrid nanofluid [72]. Another common observation is that the viscosity of the hybrid nanofluid decreases with decrease in the concentration. This trend is observed for water-based hybrid nanofluids [52,58,61,74
78], EG-based hybrid nanofluids [58,64,66,79
81], oil-based hybrid nanofluids [40,41,58,65,66,81], and water
EG mixtures [14]. In Fig. 3.8, the increase in dynamic viscosity with increasing concentration is shown for Al2O3CuO-TiO2/water ternary hybrid nanofluid [72]. In the experimental study by Eshgarf and Afrand [82], the COOH-functionalized MWCNTs
SiO2/EG
water hybrid nanocoolant is investigated rheologically. The base fluid is Newtonian, however, the hybrid nanofluid shows non-Newtonian behavior with a dramatic increase in dynamic viscosity (B20,000%) with increasing concentration ð0 , φ , 0:2Þ. Additionally the increase in shear rate caused a decrease in apparent viscosity, which results a power law index smaller than 1, a shear thinning hybrid nanofluid [82]. The power law index increases with decreasing temperature and concentration, and consistency index increased with increasing concentration and decreasing temperature. Another experimental study by Eshgarf et al. for MWCNTs
SiO2/ EG
water non-Newtonian hybrid nanofluid [73] reports similar trend for the consistency index and the power law with altering temperature and concentration. The nanoparticle combination affects the dynamic viscosity of hybrid nanofluid as well. In the study by Nabil et al. [14], the comparison of dynamic viscosity of three different hybrid nanofluids for increasing temperature is given; see Fig. 3.9 [14].

3.2 Viscosity

FIGURE 3.8 Viscosity of hybrid nanofluids for increasing volume fraction at constant temperature, T 5 35 C [72].

FIGURE 3.9 Comparison of thermal conductivity for increasing temperature for different hybrid nanofluid [14].

125

126

CHAPTER 3 Thermophysical and rheological properties

The hybrid nanoparticle combination TiO2-SiO3 resulted the highest viscosity compared to other nanoparticle combinations; the maximum viscosity is achieved in moderate temperatures. In Fig. 3.10, the effect of increasing shear rate under various temperature and concentration values on the apparent viscosity and shear stress is shown for the

FIGURE 3.10 Variation of apparent viscosity and shear stress with shear rate; under various temperature and concentration values for COOH-functionalized MWCNTs
SiO2/EG
water hybrid nanocoolant [82]. EG, Ethylene glycol; MWCNTs, multiwall carbon nanotubes.

3.3 Heat capacity

COOH-functionalized MWCNTs
SiO2/EG
water hybrid nanocoolant [82]. Even for the lowest concentration, the non-Newtonian effect of the nanoparticles is observed in the shear rate
shear stress curves, which are clearly sheer thinning. For increasing temperatures the apparent viscosity and shear stress decrease. For increasing concentrations the shear rate
shear stress relation becomes more nonlinear and the viscosity value increases significantly [82].

3.3 Heat capacity The heat capacity mainly characterizes the thermal storage capability of a material, and it is also helpful to estimate other correlated quantities such as diffusivity and dynamic thermal conductivity. Moreover, heat capacity is an important material property for relating the heat transfer performance of nanofluids in motion in terms of the convective heat transfer coefficient and the Nusselt modulus. In fluid dynamics, the Nusselt modulus (Nu) represents the ratio of convective heat to conductive heat transfer at a boundary of a fluid. There are fewer numbers of studies in the literature on the heat capacity characterization of the nanofluids in comparison to other thermophysical properties such as viscosity and thermal conductivity. The overall heat capacity of a nanoparticle blend is a function of the heat capacity of nanoparticles and the base fluid as well as the particle volume fraction and the temperature. Under constant temperature, the heat capacity of the hybrid nanofluids can be written using the first law of thermodynamics; however, under thermal effects the heat capacity should be investigated in detail. At constant nanoparticle concentration the heat capacity of hybrid nanofluids shows a nonlinear relation with the temperature. The heat capacity of the hybrid nanofluids decreases with increasing particle concentration and increasing temperature.

3.3.1 Measurement techniques The heat capacity of hybrid nanofluids can be measured using differential scanning calorimetry, at constant room temperature or for different constant heat flux conditions or using the law of cooling. In the calorimetry method, sensitive control of the temperature with low inertia and impermeability of the sample container are two essential conditions to obtain accurate experimental measurements. The standard measurement technique of heat capacity for the calorimetry method consists of three steps [83]. During the measurements, a calibration liquid and the sample liquids are used. In most cases the calibration liquid is chosen as water, because the properties of water are well documented for all temperature values. After measuring the mass of the calibration liquid (mcalibration liquid ) and the hybrid nanofluid (mhnf ), the first step is to determine the rate of the heat transfer for the empty sample container (Q_ empty ). The second step is the determination of the heat transfer rate for a calibration liquid (Q_ calibration liquid ), and the final step is to

127

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CHAPTER 3 Thermophysical and rheological properties

measure the heat transfer rate for the hybrid nanofluid (Q_ hnf ) [83]. The heat capacity of the hybrid nanofluid (chnf ) is then determined using the relation: chnf 5

Q_ hnf 2 Q_ empty mcalibration liquid ccalibration liquid mhnf Q_ calibration liquid 2 Q_ empty

(3.18)

The heat capacity of the hybrid nanofluid can also be determined by the cooling method [84]. In this test set up, there are three containers: the container for low temperature sample, the adiabatic container, and the container for the high temperature sample. The temperature of the each container is sensitively measured using a temperature sensor. The hybrid nanofluid sample mass mhnf is placed into a container with a known mass and specific heat, mc ; cc ; respectively, and heated up until they both reach to temperature After reaching the desired high temperature the hybrid nanofluid is moved into the adiabatic container. The standard sample mass and temperature are mbf ; cbf ; respectively, where the calibration liquid is mostly the base fluid (bf) and under a standard temperature Tbf which is typically lower than Thnf . In the final step, the sample liquid and the hybrid nanofluid are mixed and the constant final steady temperature of the mixture Tmixture is recorded. In this technique, the measured temperature values are related to the transferred heat during cooling, which can be written as follows [84]:

 Q1 5 chnf mhnf 1 cc mc Thnf 2 Tmixture
 Q2 5 cbf mbf Tmixture 2 Tbf

(3.19) (3.20)

where Q1 is the released heat from the hybrid nanofluid and the Q2 is the heat absorbed by the base fluid. Neglecting the heat transfer to the container and assuming very small amount of heat loss to the environment, the two quantities associated with the released and absorbed heat can be considered equal, thus the relation for the heat capacity of the hybrid nanofluid can be expressed as [84]: chnf 5

cbf mbf ðTmixture 2 Tbf Þ mhnf ðThnf 2 Tmixture Þ

(3.21)

3.3.2 Theory The heat capacity of nanofluids at constant temperature is widely modeled using two basic techniques, namely, the mixing theory (Model 1) and the thermal equilibrium assumption (Model 2). In the mixing theory, the heat capacity of the nanofluid chnf is related to the specific heat of the base fluid cbf , specific heat of the nanoparticles cnp , and the volume fraction φ. The relation for Model 1 [85] can be expressed as: chnf 5 φcnp 1 ð1 2 φÞcbf

(3.22)

3.3 Heat capacity

On the other hand, Model 2 is derived from the conjecture of thermal equilibrium in the nanofluid. After applying the energy balance between the base fluid and the nanoparticles, the equation can be written as: chnf 5 wcnp 1 ð1 2 wÞcbf

(3.23)

where w is the mass fraction of the nanoparticles [83]. Writing the mass fraction in terms of density and volume fraction, this model for hybrid nanofluids is widely used [23,30,86,69], as introduced by Takabi and Salehi [87]:





 ρhnf chnf 5 φnp1 ρnp1 cnp1 1 φnp2 ρnp2 cnp2 1 ð12φnp1 2φnp2 Þρbf cbf

(3.24)

Models 1 and 2 are the two widely used heat capacity relations for isothermal cases. Model 1 is a rather simple model; however, it fails to predict the unitary and hybrid nanofluid heat capacity precisely. In contrast, Model 2 predicts the isothermal heat capacity of the hybrid nanofluids correctly. In the study by Gao et al. [84] the Model 2 is validated for the Go
Al2O3/water hybrid nanofluid for 0.016%
0.047% and 20 C
70 C, and they reported a good agreement between theoretical values predicted by Model 2 with the values observed from actual experiments. The effects of temperature on heat capacity need to be studied in detail for nanofluids. For unitary nanofluids, the linear relations between the heat capacity and the temperature are studied in detail by Barbes et al. in a series of studies for Al2O3/EG, Al2O3/water, and CuO/EG nanofluids. Barbes et al. measure heat capacity for these nanofluids for a wide range of concentrations and temperatures [83,88]. In the study by Gao et al. [84] a new relation for the heat capacity as a function of temperature and concentration is proposed for the GO
Al2O3/water hybrid nanofluid. The maximum error is 0.86%. The proposed relation for heat capacity as a function of temperature (T) and concentration (φ) for the hybrid nanofluid is chnf 5 3:918 2 218:3φ 1 0:006596T 1 3:185 3 105 φ2 1 5:278φT 2 5:35 3 1025 T 2 (3.25)

3.3.3 Experimental results Heat capacity is a thermophysical property which varies mainly with concentration and temperature. The heat capacity of the hybrid nanofluids is studied by a limited number of researchers. One common observation is that the heat capacity of hybrid nanofluids decreases with increasing nanoparticle concentration and should be examined individually as a function of the temperature change. In the study by Yarmand et al. [74], heat conduction of the GNP-Pt/distilled water hybrid nanofluid is investigated experimentally. They investigated the heat capacity of the nanofluid for 0.02%
0.1% concentration and 20 C
45 C temperature interval. The increase in the concentration decreases the heat conduction, where

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the heat capacity of base fluid is the highest for all temperature values. The increasing temperature enhanced the heat capacity of the base fluid; on the other hand, the hybrid nanofluid showed a decrease for low and moderate concentration, whereas it showed a slight increase for high concentration cases. Gao et al. [84] studied the GO
Al2O3 (1:1)/water hybrid nanofluid experimentally and investigated the heat capacity for 0.05
0.15 wt.% concentration and 20 C
70 C temperature. The heat capacity of the hybrid nanofluid increased with decreasing concentration and it was lower than the base fluid for all temperature values tested. The hybrid nanofluid heat capacity is enhanced with increasing temperature; however, the relation is not linear.

3.4 Density Density is an important thermophysical property. The flow Reynolds number (used to help predict flow patterns in different fluid flow situations), pressure, stability, and the heat transfer performance of a hybrid nanofluid are significantly affected by the density of the hybrid nanofluid. In turn, the density of a hybrid nanofluid is significantly affected from changes in temperature and nanofluid concentration. The density of a hybrid nanofluid increases with concentration. The increase in density with increasing concentration might be the result of interface effects between the nanoparticles and the base fluid [76]. Furthermore the density of a hybrid nanofluid decreases with increasing temperature, as expected.

3.4.1 Measurement techniques The density of a hybrid nanofluid is measured using a density meter and a fluid temperature bath where an isothermal state is maintained within the bath. Some of the common density meters for fluids include process characterization devices, ultrasonic density meters, and Coriolis density meters. A process characterization device facilitates the evaluation of the density by precisely measuring the mass and the volume and using the definitive equation of the density. Ultrasonic density meters have different working principles. Some ultrasonic density meters measure the time, whereas others measure flow velocity or pipe diameter. The vibration density meters consist of a vibrating U-shaped thin-walled tube where the phase shifts are measured which can be related to the mass flow rate. The vibration density meters are highly accurate and reliable measurement devices with high reproducibility. In the study by Vajjha et al. [89], densities of different nanofluids are investigated. The densities of Al2O3/EG
water (60:40), Sb2O5SnO2/EG
water (60:40), and ZnO/EG
water (60:40) are measured using Anton Paar vibration density meter with Brookfield TC-500 temperature bath. The period of the oscillation and the device coefficients are used to evaluate the nanofluids. The device coefficients are evaluated for every temperature value using a

3.4 Density

well-known fluid in the calibration phase. In the study by Yarmand et al. [76], the density of GNP-Pt/distilled water hybrid nanofluid was measured using a Mettler Toledo DE-40 density meter which is a vibration density meter with accuracy of 1024 kg/m3.

3.4.2 Theory The theory for the density of multiphase isothermal mixtures with particles of nanometer size is introduced by Pak and Cho [69]. The density for hybrid nanofluids is predicted using the extended versions of the classical density models for the suspensions and they are surprisingly found to be in a good agreement with the experimental results. The density relation which can also be generalized to more than two nanoparticles is written as [87]:
 ρhnf 5 1 2 φ1 2 φ2 ρbf 1 φ1 ρnp1 1 φ2 ρnp2

(3.26)

where ρ is density, φ1 andφ2 are the concentrations of nanoparticles, and subscripts hnf is for hybrid nanofluid, bf is for base fluid, and np is for nanoparticle. The density relation for hybrid nanofluids is used and validated experimentally by several researchers [22,76,87,90]. In the study by Vajjha et al. [89], the experimental measurements of the density of Al2O3/EG
water (60:40), Sb2O5-SnO2/EG
water (60:40), and ZnO/ EG
water (60:40) hybrid nanofluids are compared with the models. Experimental measurements for the density values of the Al2O3 nanofluid and the Sb2O5-SnO2 hybrid nanofluid displayed very good agreement with the model. For ZnO nanofluid the difference was significant and the deviation increased with increasing concentration. A correction of the model enhanced the accuracy significantly where the new model for ZnO nanofluid is ρhnf 5

ð0:9848φ 1 0:7382Þ ð1 2 φÞρbf 1 φρnp 100

(3.27)

3.4.3 Experimental results As mentioned earlier, the density increases with increasing concentration and decrease with increasing temperature. Yarmand et al. [76] reported the density alteration of GNP-Pt/distilled water hybrid nanofluid for 0%
0.1% concentration and 20 C
40 C. The increase in concentration raised the density of the hybrid nanofluid. The increase in the temperature decreased the density of the hybrid nanofluid. Similar results are reported in [74] for GNP-Ag/water hybrid nanofluid. Moldoveanu et al. [91] studied the density of Al2O3-SiO2/water and Al2O3-TiO2/ water hybrid nanofluid for different compositions. The density of hybrid nanofluids increased with increasing concentration and changing compositions where the TiO2 enhanced the density slightly higher compared to SiO2.

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3.5 Wetting Another important thermophysical property of a hybrid nanaofluid is wetting. The measure of the wetting of a fluid is defined in terms of the contact angle. The contact angle is the angle between the tangent lines of the fluid droplet and the horizontal planar surface. The experimental measurement of the contact angle is done using a high-speed camera and an image processing software. The fluid with a contact angle higher than 90 degrees is called hydrophobic or nonwetting fluid, the fluid with a contact angle smaller than 90 degrees is called hydrophilic or wetting fluid. In the study by Septiadi et al. [92], the wetting characteristics of Al2O3-TiO2/water hybrid nanofluid is investigated experimentally for 0.1
0.7 concentration and composition of nanoparticles of 75:25, 50:50, and 25:75. The wetting characteristics of the hybrid nanofluids are compared with the distilled water which is the base fluid of the nanomixture. The base fluid contact angle is obtained as 107.4 degrees, 0.1% 25:75 Al2O3-TiO2 hybrid nanofluid contact angle is 102.65 degrees, and 0.7% 75:25 Al2O3-TiO2 hybrid nanofluid contact angle is 73.1 degrees. It can be observed that a volume fraction increase reduces the contact angle and enhances the wetting of a hybrid nanofluid. At low volume fractions (0.1% and 0.3%) the hybrid nanofluid is hydrophobic, where for higher concentrations (B0.7%) the hybrid nanofluid is hydrophilic. The size of the nanoparticle also has a significant effect on the contact angle. With increasing particle size, the contact angle decreases. The particle size of Al2O3 is greater than TiO2. Therefore increasing the ratio of Al2O3 in the hybrid nanofluid composition reduces the contact angle. The contact angle is further affected by the adhesive forces, the surface roughness, and the surface tension of the hybrid nanofluid. The increase in concentration enhances the surface tension and the contact angle decreases and thus the hybrid nanofluid becomes more hydrophilic. For every two-phase problem, there is an interface; and at the interface the surface tension becomes the central property which significantly affects the heat transfer performance. For the problems where the gravitational forces are negligible and buoyant forces are small, the transportation occurs at the interface under the sole effect of forces associated with the interface. Surface tension and how it changes with concentration, temperature, the nanoparticle type, and shape should be addressed properly because surface tension affects the thermocapillary properties and evaporation and condensation mechanisms of a hybrid nanofluid significantly.

3.6 Comparison of unitary and hybrid nanofluids A systematic analysis is necessary to clarify the thermophysical properties of hybrid nanofluids to facilitate their use as an alternative heat transfer fluid in real life applications. The hybrid nanofluids are extensively considered and important

3.6 Comparison of unitary and hybrid nanofluids

characteristics of thermophysical properties are discussed in this chapter. One common observation is that the thermal conductivity of hybrid nanofluids is higher than the unitary nanofluids [31,72,93
95]. However, unsuitable choices of nanoparticles of hybrid nanofluids result with equal or even lower thermal conductivity when compared with unitary nanofluids [18,40,60,96,97]. One reason is that the hybrid nanofluid composed of particles with large thermal conductivity gap tends to display lower thermal conductivity (see Fig. 3.11 [60]). The type of base fluid affects the thermal conductivity of both unitary and hybrid nanofluids. For hybrid nanofluids, water as base fluid results in a higher thermal conductivity compared to EG. The MWCNT
EG nanofluid exhibits higher thermal conductivity compared to Cu/MWCNT
EG hybrid nanofluid for increasing concentration and the MWCNT
water nanofluid exhibits lower thermal conductivity compared to Cu/MWCNT
water hybrid nanofluid [98]. The nanoparticle addition to the base fluid increases the viscosity and introducing more than one nanoparticle to the base fluid increases the viscosity even further. Increasing the nanoparticle concentration increases the viscosity for both unitary and hybrid nanofluids. The surfactants that are used to improve the stability of the hybrid nanofluids increase the viscosity even further. The elevated values of viscosity increase the friction factor, pressure drop, and result higher shear stresses at the wall. In the study by Xian [60], it is reported that at 40 C, 0.1 wt.% the unitary (GNPs
water
EG) nanofluid showed a higher viscosity compared to the hybrid nanofluid at the same concentration and temperature. The combined effects of concentration and temperature on viscosity should be investigated in detail for every hybrid blend to determine an appropriate hybrid nanofluid composition for a given application. The heat capacity of unitary nanofluids shows systematic characteristics: the heat capacity decreases with increasing concentration and increases with increasing

FIGURE 3.11 Thermal conductivity values for unitary (GNPs
water
EG) and hybrid (GNPs-TiO2/ water
EG) nanofluids for increasing temperature and concentration [60]. EG, Ethylene glycol.

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temperature. Additionally the temperature dependence of the unitary nanofluids can fit adequately to a linear curve. This observation is valid for different base fluids, such as water [83] or EG [83,88]. The fitted data should be evaluated for every individual nanoblend [83,88]. The heat capacity of unitary nanofluids changes with the nanoparticle size. In the study by Hu et al. [99], it is shown that for 20 nm SiO2 nanoparticle, the heat capacity enhancement reaches up to 26.7%. The heat capacity of hybrid nanofluids decreases with increasing concentration. However, for hybrid nanofluids, the temperature
heat capacity relationship is not only nonlinear but also shows different trends for different concentrations and different nanoparticle mixtures. Yarmand et al. [74] reported that the heat capacity of GNP-Pt/distilled water hybrid nanofluid decreased with increasing temperature at 0.02% and 0.06% concentrations, whereas at 0.1% concentration the heat capacity increased a little for increasing temperature. In the study by Gao et al. [84], the comparison of 0.1 wt.% Al2O3/water nanofluid, 0.1 wt.% Go/water nanofluid, and 0.1 wt.% Go
Al2O3/water hybrid nanofluid revealed that the heat capacity of hybrid nanofluid is higher than the two nanofluids at every temperature values studied. The Go/water nanofluid demonstrated higher heat capacity compared to Al2O3/water nanofluid [84]. The unitary and hybrid nanofluids display the same trends with regards to density. The density of nanofluids increases with increasing concentration. Conversely the density of nanofluids decreases with increasing temperature [69,76]. The contact angles between glass and different nanofluids are examined for increasing particle concentration and different nanoparticle sizes [100]. At the same concentration, for the bigger nanoparticle size the wetting of the nanofluid enhances. It is shown that the increasing concentration enhances the wetting of the nanofluid [100,101]. The wetting of hybrid nanofluids shows similar trends with the nanofluids. The increasing concentration and bigger nanoparticle size decreases the contact angle and thus the hybrid nanofluid becomes more wetting fluid [92]. In a series of studies, Dalkılıc¸ et al. [102
104] investigated the optimum operation conditions and carried out cost analyses. In one study [102], they addressed the effect of base fluid type with Ti and TiO2 nanoparticles. The base fluids were water, propane, motor oil, methanol, EG, glycerin, ethanol, and ammonia. The optimum operation condition and optimum cost are addressed for every nanofluid at a broad range of particle concentration. In the numerical study by Kayacı et al. [103], for a horizontal pipe flow, the TiO2/water nanofluid is investigated for different empirical models associated with the thermophysical properties of nanofluids readily available in the literature and the optimum combinations for the optimum cost and operating conditions are located. The optimization of finned double pipe heat exchanger is carried out for a wide range of nanofluids in terms of optimum operation condition and cost analysis where the most efficient model combinations are inherited from previous studies [104]. These types of optimization studies should be done for hybrid nanofluids as well.

3.7 Challenges and conclusions

3.7 Challenges and conclusions Hybrid nanofluids are relatively new heat transfer fluids that are good candidates for industrial applications as a result of their superior thermophysical properties. Specifically the superior thermal conductivity of hybrid nanofluids makes them unique heat transfer fluids. The thermal conductivity of hybrid nanofluids is increased with increasing particle concentration. On the other hand, the viscosity of nanofluids increases with nanoparticle addition to base fluid and the resulting rise in the viscosity is more pronounced when hybrid nanofluids are used. An increase in the particle concentration increases the viscosity, whereas an increase in the temperature results in a reduction in the viscosity. The viscosity rise for the hybrid nanofluid can still be considered as significant even for low concentration and high temperature values. The main consequence of viscosity rise is higher pressure drop which necessitates a higher pumping power. As a result the overall efficiency of a thermal system is reduced and the operational costs increase. The shape and size of the nanoparticle have appreciable effect on viscosity as well. One more parameter to be considered is the stability of the hybrid nanofluid, with increasing particle concentration the stability of the suspension reduces and sedimentation becomes more pronounced. The fouling is caused by the sedimentation of the working fluid in the piping network of a thermal system. A major reason for heat exchangers to work with a lower capacity is fouling and it increases the operational and maintenance costs simultaneously. The optimization of the concentration and the determination of the fraction of the nanoparticles in a hybrid nanofluid are very challenging problems where multiaspects need to be carefully considered to make full use of hybrid nanofluids. The thermophysical properties of a hybrid nanofluid is affected from the particle concentration, the temperature, the size and the shape of the nanoparticles, the duration of the mixing time, the stability of the blend and the type, and the combination of the base fluid. The most important challenges can be listed as follows: 1. The classical models for thermal conductivity and viscosity fail to predict accurate values for majority of the nanofluids. Similarly these models cannot accurately predict the thermophysical properties of hybrid nanofluids. The empirical models are specific only for a given hybrid nanofluid and are valid for a very narrow concentration and temperature range. Within these limitations, however, these empirical models can provide very good estimates that are in agreement with experimental observations. Nevertheless, there is a significant amount of dissimilarity among the experimental observations for the same kind of nanofluids which may rise from the lack of standardized classification of the nanoparticles. This discrepancy increases the number of empirical relations in the literature, which makes it harder to improve numerical modeling of these discrepant experimental observations. 2. The type of nanoparticles as well as the preparation technique of the suspension affects the stability of the blend and thus the thermophysical

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properties of the hybrid nanofluid. The cheapest method to improve the stability is addition of surfactants, which significantly improves the thermal conductivity but the resulting increase in dynamic viscosity raises the need for increased pump power and friction coefficient significantly. Ultrasonification, pH control, better particle grouping, and synthesis extend the stabile duration of the mixture, which would enable the hybrid nanofluids to become a candidate for real life applications. 3. To have the proper mixture for a given application, the effect of each combination should be studied in detail. For commercial application of hybrid nanofluids, a detailed analysis should be performed to understand the thermophysical properties together with the analyses for the production, experimentation, and application costs. 4. Additional experimental and theoretical studies are needed to have more general models that describe the thermophysical properties accurately for a wide range of hybrid nanofluids. Additional investigations for the properties of hybrid nanofluids to better understand their density and the heat capacity are necessary.

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20.

CHAPTER

Hybrid nanofluids as a heat transferring media

4

Hamza Babar1, Muhammad Usman Sajid2 and Hafiz Muhammad Ali3 1

Mechanical Engineering Department, University of Engineering and Technology, Taxila, Pakistan 2 Division of Sustainable Development (DSD), College of Science and Engineering (CSE), Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF), Education City, Doha, Qatar 3 Mechanical Engineering Department, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, Saudi Arabia

Chapter Outline 4.1 Introduction .................................................................................................143 4.2 Natural convection heat transfer ...................................................................145 4.3 Forced convection heat transfer ....................................................................158 4.3.1 Single-phase and two-phase forced convection heat transfer ...........163 4.4 Heat transfer in porous media .......................................................................166 4.5 Theoretical studies and models for prediction of heat transfer ........................167 4.6 Concluding remarks ......................................................................................167 Nomenclature ......................................................................................................170 Greek letters .......................................................................................................171 Subscript ............................................................................................................171 References ..........................................................................................................172

4.1 Introduction In the past few years, hybrid nanofluids stand out as promising heat transfer medium. Hybrid nanofluid which is extension of binary nanofluid contains two or more types of nanoparticles in the base fluid (water, ethylene glycol (EG), vegetable oil, transformer oil, paraffin oil, diathermic oil, and naphthenic mineral oil). Sajid and Ali [1] mentioned hybrid nanoparticles being used in experimental studies include: Ag
GNPs, Ag
WO3, Ag
Si, Ag
MgO, Ag
ZnO, Al
Zn, AlN, Al2O3
Cu, Al2O3
carbon nanotubes (CNTs), Al2O3
CuO, Al2O3
graphene, TiO2
SiC, TiO2
Cu, TiO2
SiO2, TiO2
CuO/C, TiO2
Ag, TiO2
CNTs, TiO2
multiwalled carbon nanotubes (MWCNTs), MWCNTs
Al2O3, MWCNTs
GO, MWCNT
Si, MWCNTs
ZnO, MWCNTs
Ag, MWCNTs
Hybrid Nanofluids for Convection Heat Transfer. DOI: https://doi.org/10.1016/B978-0-12-819280-1.00004-5 © 2020 Elsevier Inc. All rights reserved.

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CHAPTER 4 Hybrid nanofluids as a heat transferring media

SiO2, FMWCNTs
Fe3O4, and FMWCNTs
MgO. The heat transfer applications of hybrid nanofluid incorporate micro- and minichannel heat sinks, tubular and plate heat exchanger, shell and tube heat exchanger, helical coiled heat exchanger, air conditioning systems, heat pipes, solar PV-T systems, solar collectors, solar thermal energy storage systems, and solar desalination [2,3]. Natural convection attracted the attention of investigators due to enormous advantages such as: low noise, operating cost, and energy conservation. Cooling of electronic components, solar collectors, energy efficient buildings, double pane windows, nuclear reactors, solar collectors, and heat exchanger are the industries demanding natural convection. That is way, investigators putting their efforts to study the natural convection inside open and closed cavities of different geometrical configurations with or without blocks that are either isothermal or adiabatic. Notable enhancement in natural convection was observed for the fluids having metallic nanoparticles suspensions. In forced convection heat transfer (CHT) fluid continuously removes or transfers heat flowing on the surface of the body. For the case of nanofluids a pump is used to transport the fluid, one of the advantages of forced flow is that the rate of heat transfer can be controlled by adjusting the flow rate of fluid. However, in parallel of heat transfer augmentation penalty in the form of pumping power is also an important factor needed careful consideration. The suspension of metallic nanoparticles in base fluid also caused the enhancement in pumping power. In other words, while dealing with forced convection of nanofluids no one can decide the effectiveness of unitary and hybrid nanofluids on the basis of heat transfer only. It is the trade-off of advantages (heat transfer enhancement) and disadvantages (cost and pumping power), as shown in Fig. 4.1. One of the advantages of hybrid nanofluid is that the rate of heat transfer can be controlled by varying the particle concentration or altering the combination of nanoparticles. Qin et al. [4] investigated the performance of direct absorption solar collector employing plasmonic nanofluid. According to the results, the value of absorption coefficient can be tuned by varying the particle concentration or mixing the different types of nanoparticles. Hybrid nanofluid has also been found to be more effective than unitary nanofluid for industrial applications because of its better heat transfer characteristics when compared with its cost [5
7]. However, this is not the case for all combinations of nanoparticles. Thus cost is also an important factor to consider while selection of nanoparticles combination and base fluid for preparing hybrid nanofluid. A substance that has solid matrix but comprising of continuous pores is known as porous medium. Wood, sand, human lungs, and sandstones are examples of natural porous media. Metal foams, ceramics, and composite materials are examples of artificial porous mediums. Porous mediums have extensive applications in engineering field and industry [8] embracing geothermal systems, solar heating systems, fuel cells, energy storage systems, catalytic converters, and cooling of electronic parts. Due to numerous applications of porous medium, many researchers are working to investigate thermal behavior of binary and hybrid nanofluids in porous media.

4.2 Natural convection heat transfer

FIGURE 4.1 Nanofluid advantages and disadvantages trade-off, graphical illustration.

The heat transfer coefficient and fluid flow may get affected by the presence of magnetic field. To investigate magnetic field effect on convective heat transfer, many studies have been conducted on magnetohydrodynamics natural convection of nanofluids. Few studies [9
12] explored heat transfer characteristics of hybrid nanofluids under various conditions inside porous medium. Fig. 4.2 provides the graphical illustration of the factors that needed careful consideration while investigating the hybrid nanofluids as a heat transfer media. Correlations developed to predict the heat transfer using hybrid nanofluid as a cooling medium under certain limitations are compiled and presented in Table 4.2. The developed correlations can predict heat transfer with certain deviation using specified ranges of parameters.

4.2 Natural convection heat transfer Natural convection is the phenomenon most frequently occur in many engineering applications. During the past few decades, investigators compiled a number of research articles on natural convection in closed and open cavities. The suspension of nanoparticles in base fluid found to be an effective technique to augment the rate of heat transfer. Abu-Nada and Oztop [13] numerically investigated the effect of fluid flow and natural convective heat transfer inside a two-dimensional enclosure filled with water-based copper (Cu) nanofluid varying the inclination angle (0
120 degrees) and particle concentration. Finite volume method was used to solve the governing equations and found that the augmentation in Nusselt number (Nu) was more prominent at low particle volume fraction than that of high concentration. In addition, inclination angle was found to be a good control

145

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CHAPTER 4 Hybrid nanofluids as a heat transferring media

FIGURE 4.2 Factors that needed careful consideration while investigating the hybrid nanofluids as a heat transfer media, graphical illustration.

parameter for pure water and nanoparticles suspended fluid filled enclosure. In terms of the stream function-vorticity for laminar and steady-state natural convection, the governing equations were expressed with the following sets of Eqs. (4.1)
(4.4):

• Vorticity

 


 ϕρ β 1 ð 1 2 ϕ Þρ β np bf μ np bf @ @λ @ @λ @ω @ω nf ω 0 2 0 ω 0 5 1 02 1 @x0 @y @y @x @y ρnf ρnf @x0 2
 @T @T 3g cosφ 2 0 @x0 @y sinΘ

• Energy @ @x0



     @λ @ @λ @ @T @ @T T 0 2 0 T 0 5 0 αnf 0 1 0 αnf 0 @y @y @x @x @x @y @y

(4.1)

(4.2)

• Kinematics @2 λ @2 λ 52ω 02 1 @x @y0 2 αnf 5 

keff ρcp nf

(4.3) (4.4)

where x and y symbolized the dimensional coordinates, and λ; ω; μ; ρ; ϕ; β; T; Θ; g; α; keff ; and cp denoted the dimensionless stream function, dimensional vorticity, dynamic viscosity, density, particle volume fraction, thermal expansion coefficient, dimensional temperature, transport quantity, gravitational acceleration, fluid thermal diffusivity, thermal conductivity, and specific heat at constant pressure, respectively.

4.2 Natural convection heat transfer

Some of the studies reported contradictory results and observed a reduction in natural convective heat transfer coefficient with increasing particle concentration. Wen and Ding [14] examined the heat transfer characteristics of titania (TiO2) nanofluid under the condition of natural convection. Investigators considered both steady and transient heat transfer coefficient and concluded that the natural CHT coefficient deteriorates systematically with the increase in nanoparticle concentration. Kalidasan et al. [15] observed the natural convection inside the open-ended C-shaped cavity heated partially having a square-shaped isothermal block inside. The study was conducted by varying the particle concentration (0%
5%) of titania
copper/water hybrid nanofluid and analyzed the hydrodynamic blockage effect of isothermal block. Heat transfer was found to be increased with the increase in nanoparticle percentage and Rayleigh numbers ðRa , 105 Þ, however, a marginal decreased in Nusselt number was noticed for all concentrations at ðRa 5 106 Þ. According to the investigators, the nanocomposite molecules interlinking breakage could be the possible reason of this decrease of heat transfer. Hwang et al. [16] presented a theoretical investigation on the below heated rectangular cavity and observed the natural convection employing alumina (Al2O3) nanoparticles suspended nanofluid. The effect of particle size, volume fraction, and nanofluid average temperature was analyzed on natural convection. Natural convection was found to be more stable employing alumina
water nanofluid than water for below heated rectangular cavity; as the size of particles decreased, particle concentration increased, or the fluid temperature increased. In many industrial processes, magnetic effect influenced the heat transfer significantly. Izadi et al. [9] investigated the natural CHT in a porous media with two variable magnetic sources employing magnetizable hybrid nanofluid of Fe3O4
MWCNT/water. The effect of various parameters such as Hartmann number (0
50), magnetic sources strength ratio ðγ 5 0:2
5Þ, porosity coefficient (0.1
09), and magnetic number (100
5000) was observed on natural convective heat transfer. Results portrayed that the effect of magnetic sources strength ratio on heat transfer was almost negligible at low Rayleigh numbers. Results also depicted that Nusselt number enhanced with the increase in magnetic number at Ra 5 104 , however, at Ra 5 106 Nusselt number increased with magnetic number at high values of γ. The effect of porosity was found to reduce with the increase in porosity as the medium turns into poreless gradually that caused the reduction in heat transfer. Sheikholeslami et al. [17] conducted a numerical investigation via finite element method (FEM) on magnetizable hybrid nanofluid of Fe3O4
MWCNT/water inside a circular cavity having two circular heaters. The solution was assumed as homogeneous and used the single-phase nanofluid model. Results revealed that Nusselt number augmented with the supplementation of nanoparticles in the base fluid (water). In addition, it was also observed that the thickness of thermal boundary layer around the circular heaters increased as location angle of heaters increased. Local heat transfer was estimated by using Eq. (4.5) also known as local Nusselt number ðNulocal Þ while the total heat transfer was evaluated by integrated Eq. (4.5), expressed with Eq. (4.6).

147

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CHAPTER 4 Hybrid nanofluids as a heat transferring media

Nulocal 5 2

  knf @T kbf @r

(4.5)

2s 32 s 321 sð2
 ð1 ð1
 ðs2 knf 4 @T @T 5 4 ds 1 ds ds1 ds5 Nuavg: 5 2 @r @r kbf 0

0

0

(4.6)

0

where “r” and “s” denoted the circle perpendicular direction and length of the circle respectively. Esfe et al. [18] presented a numerical study to investigate the natural convective heat transfer inside a trapezoidal cavity employing CNTs suspended binarybased (water
EG) nanofluid. Investigators observed the effect of aspect ratio (inclination angle) and particle concentration in the range of Rayleigh numbers ð103 2 106 Þ. Results portrayed a notable reduction in average  Nusselt number 4 ðNuavg Þ with increasing aspect ratio at low Rayleigh numbers Ra # 10 . At high  Rayleigh number Ra 5 106 , Nuavg showed an irregular trend; it first increased and then decreased with aspect ratio at a fixed particle concentration with a maximum Nuavg at an inclination angle of 30degrees. It was also noticed that at fixed particle concentration and inclination angle, Nusselt number augmented with Rayleigh numbers. In addition, results concluded that the conduction heat transfer was dominant at low Rayleigh numbers while CHT was dominant as Rayleigh number increased due to buoyancy effect. Izadi et al. [19] employed the hybrid nanofluid of Fe3O4
MWCNT/water inside a \-shaped enclosure to analyze the natural convective heat transfer. Effect of heat source positioning and heat source aspect ratio was studied varying the Rayleigh number and particle concentration. Results revealed that heat source aspect ratio augmentation systematically enhanced the heat transfer owing to the reduction of thermal boundary layer thickness. The average Nusselt number was found to be enhanced with particle concentration and Rayleigh number, while better condition for natural heat transfer was acquired by placing the heating source at the center of enclosure. The study conducted by Mehryan et al. [8] on a thick porous enclosure filled with micropolar nanofluid observed that the effect of vortex viscosity on Nusselt number completely depends on the Rayleigh number. At low Rayleigh number, it was found that the Nusselt number was independent of the vortex viscosity while it was completely dependent at high Rayleigh number. Rayleigh number influenced the particles suspension as well [20,21]. Motlagh and Soltanipour [21] used Buongiorno’s model to investigate the natural convection inside a tilted cavity filled with alumina
water nanofluid. Results revealed that at low Rayleigh number particles distribution was nonuniform while it was nearly uniform at high Rayleigh number. Mansour et al. [22] studied the effect of Al2O3
Cu/water hybrid nanofluid particle concentration on entropy generation and natural CHT inside a porous square-shaped cavity. Results revealed an augmentation in entropy generation with particle concentration and a decrease with Hartmann number (Ha), as shown in Fig. 4.3. A comparative study was also drawn and found that the suspension of Cu nanoparticles delivered better results in comparison to other

4.2 Natural convection heat transfer

FIGURE 4.3 Variation of total entropy generation with particle volume fraction and Hartmann number [22].

nanoparticles. The variation of average Nusselt number with particle concentration, Hartmann number, and Rayleigh number employing Cu
Al2O3/water hybrid nanofluid within open wavy cavity under magnetic field was observed by Ashorynejad and Shahriari [23]. Improvement in Nusselt numbers was obtained by varying the particle concentration and Rayleigh number while attenuated with an increase in Hartmann number. At low Rayleigh number (103), raising phase deviation ðΦÞ showed an erratic effect while played a positive role in improving the effect of nanoparticles at high Rayleigh number (105). Other important parameters that need careful consideration while analyzing hybrid nanofluids are the thermophysical properties (heat capacity, thermal conductivity, density, and viscosity). Investigators used the extended forms of available models to predict the thermophysical properties of hybrid nanofluids. However, in most of the experimental studies published recently investigators used different measuring instruments to compute these properties [24
27]. Chamkha et al. [28] conducted a numerical investigation to analyze unsteady natural convection inside a semicircular enclosure filled with water-based hybrid nanofluid of Al2O3
Cu. Obtained results exhibited a notable augmentation in

149

150

CHAPTER 4 Hybrid nanofluids as a heat transferring media

heat transfer at solid
liquid interface with the supplementation of nanoparticles. The extended form of the model of Pak and Cho [29], Xuan and Roetzel [30], Maxwell [31], and Brinkman [32] was used for estimating the density ðρÞ, heat capacity Cp , thermal conductivity ðkÞ, and viscosity ðμÞ of hybrid nanofluid, respectively, represented with Eqs. (4.7)
(4.10). Model of Pak and Cho [29] for density of unitary and hybrid nanofluid.

ρhnf

ρnf 5 ϕρnp 1 ð1 2 ϕÞρbf   5 ϕnp1 ρnp1 1 ϕnp2 ρnp2 1 1 2 ϕnp1 2 ϕnp2 ρbf

(4.7)

Model of Xuan and Roetzel [30] for heat capacity of unitary and hybrid nanofluid. ϕρnp Cp;np 1 ð1 2 ϕÞρbf Cp;bf ρnf   ϕnp1 ρnp1 Cp;np1 1 ϕnp2 ρnp2 Cp;np2 1 1 2 ϕnp1 2 ϕnp2 Cp;bf Cp;nf 5

Cp;hnf 5

ρhnf

(4.8)

Model of Maxwell [31] for thermal conductivity of unitary and hybrid nanofluid.

khnf kbf

"  # knc 1 2kbf 1 2ϕ knc 2 kbf  keff 5 kbf knc 1 2kbf 2 ϕ knc 2 kbf 20  13   ϕnp1 knp1 1 ϕnp2 knp2 6@ 1 2kbf 1 2 ϕnp1 knp1 1 ϕnp2 knp2 2 2ϕkbf A7 6 7 ϕ 6 7 6  7  56 0 1 7 6 7   ϕ k 1 ϕ k 6 7 np1 np1 np2 np2 A 4 @ 5 1 2kbf 2 ϕnp1 knp1 1 ϕnp2 knp2 1 ϕkbf ϕ

(4.9)

Model of Brinkman [32] for viscosity of unitary and hybrid nanofluid. μnf 5 μnf 5

μbf ð12ϕnp Þ2:5 μbf

ð12ϕnp1 2ϕnp2 Þ2:5

(4.10)

According to the results of investigations these models can predict the hybrid nanofluid thermophysical properties with an acceptable error [33
37], however, contradictory results were also observed. A study compiled by Babar and Ali [3] summarized the applications and challenges of hybrid nanofluid and raised a question that whether the further extended forms of these models could predict the values of trihybrid with an acceptable error. Investigators highlight the merits and demerits of hybrid nanofluids. Table 4.1 presents the schematic illustration of the physical models studied by different researchers.

Table 4.1 Schematic illustration of the physical models investigated by different researchers with influencing parameters ranges. References Izadi et al. [9]

Abu-Nada and Oztop [13]

Physical model (schematic illustration)

Parameters Magnetic number 5 100
5000, magnetic sources 5 0.2
5, Hartmann number 5 0
50, and porosity coefficient 5 0.1
0.9

Inclination angle, φ 5 0 2 120degrees and Rayleigh numbers 5 103 2 105

(Continued)

Table 4.1 Schematic illustration of the physical models investigated by different researchers with influencing parameters ranges. Continued Hwang et al. [16]

Particle concentration 5 0 2 0:05 vol:%

Kalidasan et al. [15]

Rayleigh numbers 5 104 2 106 and particle concentration 5 0 2 5 vol:%

Sheikholeslami et al. [17]

Rayleigh numbers 5 104 2 106 , particle concentration 5 0 2 0:3 vol:%, magnetic number 5 0
1000, Hartmann number 5 0
50, and location angle of heaters 5 0 2 π=2

(Continued)

Table 4.1 Schematic illustration of the physical models investigated by different researchers with influencing parameters ranges. Continued Esfe et al. [18]

Rayleigh numbers 5 103 2 106 , and particle concentration 5 0:0015 2 0:045 vol:%

Izadi et al. [19]

Rayleigh numbers 5 103 2 106 and particle concentration 5 0 2 0:003 vol:%,

(Continued)

Table 4.1 Schematic illustration of the physical models investigated by different researchers with influencing parameters ranges. Continued Mehryan et al. [8]

Rayleigh numbers 5 10 2 1000, particle concentration 5 0 2 0:08 vol:%, and porosity coefficient 5 0.1
0.9

Mansour et al. [22]

Rayleigh numbers 5 103 2 106 and particle concentration 5 0:02 2 0:1 vol:%

Ashorynejad and Shahriari [23]

Rayleigh numbers 5 103 2 106 , particle concentration 5 0:02and0:04 vol:%, and Hartmann number 5 0
90

158

CHAPTER 4 Hybrid nanofluids as a heat transferring media

FIGURE 4.4 Forced convective heat transfer in different applications.

4.3 Forced convection heat transfer Investigators analyzed the forced CHT of unitary and hybrid nanofluids in many application areas such as: in manufacturing industry as a coolant, electronic industry to maintain the temperature of electronic components like microprocesses in a combination of heat sinks, automotive industry, refrigeration and air conditioning, and solar energy. Fig. 4.4 shows the graphical illustration of the application of hybrid nanofluid in different arenas. Hybrid nanofluid is the advanced class of nanofluids and devised few years ago that is why limited studies are available on hybrid nanofluids.

4.3 Forced convection heat transfer

FIGURE 4.5 Isotherms (right) and streamlines (left) for Hybrid nanofluid of Al2O3
Cu/water in a horizontal channel cavity having an adiabatic square-shaped obstacle with the variation of Reynolds number at Ri 5 1, Ha 5 25, and ϕ 5 0.02 [38].

Hussain et al. [38] analyzed the effect of Reynolds number, Richardson number (Ri), and particle concentration employing the hybrid nanofluid of Al2O3
Cu in a horizontal channel cavity having an adiabatic square-shaped obstacle. Entropy generation was also analyzed in the presented study. Crank-Nicolson method in time and Galerkin FEM in space were used to solve the governing partial differential equations. The bottom wall was taken as hot while all the other walls and the channel interior was adiabatic except the left side that was taken as cold. The results led to an increase in heat transfer and entropy generation with increasing Reynolds number (Re), Richardson number, and particle concentration. Fig. 4.5 presented the streamlines and isotherms of the hybrid nanofluid (Al2O3
Cu/water) filled horizontal channel cavity having adiabatic squareshaped obstacle. Investigators expressed the one-dimensional governing equations of continuity, momentum, and energy as Eqs. (4.11)
(4.14). @u @v 1 50 @x @y @u @u @u 1 @p μhnf 1u 1v 52 1 ρhnf @t @x @y ρhnf @x

(4.11)


 @2 u @2 u 1 @x2 @y2

(4.12)

159

160

CHAPTER 4 Hybrid nanofluids as a heat transferring media

FIGURE 4.6 Variation of (A) Nusselt number and (B) friction factor with Reynolds number (comparison of hybrid and unitary nanofluid with water) [39].


2  ðρβ Þhnf @ v @2 v σhnf 2 1 1 gðT 2 Tc Þ 2 B v (4.13) @x2 @y2 ρhnf ρhnf o
2  @T @T @T @ T @2 T 1u 1v 5 αhnf (4.14) 1 @t @x @y @x2 @y2

@v @v @v 1 @p μhnf 1u 1v 52 1 @t @x @y ρhnf @x ρhnf

Entropy generation expressed as, Eq. (4.15). khnf S 5 2 To 1

"
 "

2 #
2 !
 # μhnf @T 2 @T @u 2 @v @u @v 2 σhnf 2 2 1 1 2 1 B v 1 1 1 @x @y @x @y @x @y To To o (4.15)

where To 5 ðTh 1 Tc Þ=2, Th and Tc denoted the temperature at hot and cold end, respectively.u and v represented the velocity components in x and y directions, p, α; β; and σ symbolized the pressure, thermal diffusivity, thermal expansion coefficient, and electrical conductivity, respectively. Suresh et al. [39] presented an experimental investigation on the hydrothermal performance of uniformly heat circular tube employing the hybrid nanofluid of Al2O3
Cu/water in a fully developed laminar regime. Nanocomposite powder of Cu
Al2O3 was used to prepare the water-based hybrid nanofluid. Results revealed an enhancement of 13.56% in Nusselt number in comparison of water. Investigators also compared the results of hybrid nanofluid with a unitary nanofluid of Al2O3/water and observed a slightly more friction factor for the case of hybrid nanofluid than that of Al2O3/water, Fig. 4.6 presented the variation of Nu and friction factor with Reynolds number. Heat loss of about 3% was also observed from insulation of the total heat supplied during the experimental work. Friction factor ðf Þ and heat loss from the insulation ðQloss Þ was examined using the Eqs. (4.16) and (4.17), respectively.

4.3 Forced convection heat transfer

f5 Qloss 5

Δp d 1=2ρv2 l

2πlðTw 2 Tamb: Þ  ln ro =ri 1 1 ro h kins

(4.16) (4.17)

where d; v; l; Tw ; Tamb: ; ro ; ri ; and kins denoted the test section diameter, fluid velocity, length of test section, wall temperature, ambient temperature, outer radius of insulation, inner radius, and insulation thermal conductivity, respectively. Yarmand et al. [40] studied the enhancement in Nusselt number and friction in turbulent flow regime employing hybrid nanofluid of platinum/graphene nanoplatelet. The study was conducted by varying the particle concentration and Reynolds number ranging from (0.02
0.1 wt.%), and (5000
17,500). Results yielded a maximum enhancement of about 28.48% in Nusselt number with an increase of 10% in friction factor. Friction factor was found to be reduced with Reynolds number and increased with particle concentration. The effect of different parameters on CHT of nanofluids under laminar, turbulent, and transient flow regimes was studied by Javed et al. [41] Investigators summarized the correlations of Nusselt number developed by different investigators in a tabulated form with limitations to assist the young scholars. According to the investigators, CHT coefficient was influenced by the size of nanoparticles, flow conditions, particle concentration, pH value, temperature, clustering of NPs, and surfactants. However, the effect of Re and concentration was found to more significant in most of the studies. The selection of nanoparticles pair is very crucial to get the desired amount of heat transfer. It is one of the benefits of hybrid nanofluid that the desired amount of heat transfer can be achieved by varying the particles mixing ratio. So, it is not true to say that hybrid nanofluid delivers better results in comparison of unitary nanofluids. Moreover, heat transfer is not the only parameter that decides the performance of nanofluid, in forced convection applications pumping power is also a significant parameter that needed to be considered. In other words, it is the tradeoff heat transfer and pumping power. Ahammed et al. [42] analyzed the heat transfer characteristics and entropy generation of water-based hybrid nanofluid of alumina
graphene in thermoelectric cooler coupled with minichannel heat exchanger. The unitary nanofluid of alumina and graphene was also analyzed and drawn a comparative study in the laminar flow regime. Entropy generation was found to be reduced with the increase in Reynolds number. Augmentation in heat transfer and pressure drop was also observed with Reynolds number. Unitary nanofluid of graphene showed the maximum enhancement in Nu with a minimum penalty of pressure followed by alumina
graphene hybrid nanofluid and alumina nanofluid. Nimmagadda and Venkatasubbaiah [43] numerically studied the nanofluid of silver (Ag), alumina and combination of these Ag
Al2O3 in microchannel heat sink. Results concluded that at high concentration (3 vol.%) hybrid

161

162

CHAPTER 4 Hybrid nanofluids as a heat transferring media

nanofluid delivered the better results than that of separately prepared nanofluid of Ag and Al2O3. Investigators suggested the hybrid nanofluids because it was also found to be cost-effective with superior heat transfer characteristics. A study conducted by Babar and Ali [44] on the hydrothermal performance of airfoil-shaped fin pin heat sink used for the cooling of electronic components employing the nanofluids of titania (TiO2/water) and ferric oxide (Fe2O3/water). Investigators observed an enhancement in Nu and pumping power varying the flow rate and heating power for a fixed particle concentration of 0.01 vol.%. According to the results, the enhancement in Nusselt number was 14.5% and 15.89% while pumping power increased by 42.46%, 30.5% for titania and ferric oxide nanofluids, respectively. In addition, with the increase in heating power and flow rate Nusselt number found to increase while pumping power decreased with the increase in heating power. Karimi and Afrand [45] numerically analyzed the heat transfer in horizontal and vertical tube radiator employing the EG-based hybrid nanofluid of MgO
MWCNTs. Elliptical and circular shaped tubes were also investigated by varying the inlet temperature and concentration and flow rate. Results revealed that radiator having vertical tubes showed an enhanced heat transfer and better efficacy of about 10% in comparison of horizontal tube radiator. In addition, 25% more penalty of pumping power and 10% higher Nusselt number was acquired with elliptical shaped tubes than that of circular. The increase in Nusselt number and pumping power was also found with nanoparticle concentration and Reynolds number. According to the results, compared to the inlet temperature nanoparticles concentration more effectively augment the rate of heat transfer. Nanoparticles are also suspended in lubricants called nanolubricants to improve the thermal properties and lubrication effect. Zhang et al. [46] tested the Al2O3 and SiC nanoparticles suspended nanolubricants and their hybrid in minimum-quantity lubrication grinding. It was observed that nanolubricant lowered the grinding force ratio, specific grinding energy, and surface roughness while better results were observed for hybrid nanolubricant. Investigators studied the different parameters by employing the simple and hybrid nanofluids in different manufacturing processes and automobile industry [47,48], however, limited studies are available in literature on the applications of hybrid nanofluids in these areas. A number of studies published recently analyzed the rheological behavior and thermal properties of oil-based nanofluids [49
52]. Nanofluid found be a potential candidate in solar energy systems, used in receiver, used as a coolant for thermal equilibrium of photovoltaic panels. A study compiled by Wahab et al. [53] on the potential of nanofluids in solar energy systems concluded that in most studies maximum efficiency was achieved at lower particle concentration, at higher concentration particle found to stick with the inner surface of heat exchanging device that caused the reduction in heat transfer. Jamil et al. [54] experimentally investigated the effectiveness of two cooling techniques, hybrid nanolubricant (alumina
MWCNT/ vegetable oil) and cryogenic CO2-based minimum quantity lubrication (MQL) techniques for tuning operation of titanium alloy

4.3 Forced convection heat transfer

(Ti
6Al
4V) varying the cutting speed and feed rate. Results yielded that suspension of nanosized particles not only increased the rate of heat transfer but also reduced the cutting force and surface roughness. It was found that employing nanoparticles suspended hybrid nanolubricant-based MQL technique tool life increased by 23%, cutting force and average surface roughness reduced by 11.8% and 8.72%, respectively, in comparison of cryogenic cooling technique. Xuan et al. [55] prepared the hybrid and mono nanofluids of TiO2 and Ag in water to study the solar energy absorption. According to the results, titania in a combination of Ag showed the same temperature that was obtained with the unitary nanofluid of Ag. So, hybrid nanofluid found to be cost-effective. In addition, hybrid nanofluid exhibited remarkable enhancement in optical absorption. To prove the significance of hybrid nanofluids investigators also conducted the comparative study of mono and hybrid nanofluids. Bellos and Tzivanidis [56] studied the following Syltherm 800-based nanofluids: 3% TiO2/Oil, 3% Al2O3/ Oil, and 1.5% TiO2-1.5% Al2O3/Oil in LS-2 PTC module. The study was conducted at a flow rate of 150 L/min varying the inlet temperature ranging from 300K to 500K in a turbulent flow regime. Thermal efficiency enhancement of about 1.8% was observed for hybrid nanofluid while it was maximum up to 0.7% for unitary nanofluids.

4.3.1 Single-phase and two-phase forced convection heat transfer Generally in unitary and hybrid nanofluid CHT modeling, investigators followed the single-phase and two-phase modeling techniques. In single-phase modeling, the mixture of base fluid and nanoparticle is considered as single-phase mixture, while in two-phase modeling the properties and behaviors of nanoparticle and base fluid are considered separately. Kumar and Sarkar [57] analyzed the forced CHT of MWCNT
Al2O3 nanoparticles suspended water-based hybrid nanofluid inside minichannel heat sink using single-phase and two-phase modeling. An experimental investigation was also conducted varying the Reynolds number and compared the results of numerical simulation with experimental data. According to the results, two-phase model showed a good agreement with the experimental data in comparison of homogeneous single-phase approach. In addition, an augmentation of about 15.6% in heat transfer coefficient was observed with 0.01 vol. % hybrid nanofluid of MWCNT
Al2O3 (2:8), however, a diminutive increase in pressure drop was also noticed. Fard et al. [58] studied the heat transfer characteristics of Cu/water nanofluid numerically. The study was conducted by employing the nanofluid inside a circular tube under constant wall temperature. For numerical investigation both singlephase and two-phase models were used and compared the results with the experimental data. Results revealed that two-phase model provided the better prediction of experimental values than that of single-phase model. Heat transfer enhancement was also observed with the increase of ϕ and Peclet number. Single-phase and two-phase flow equations can be expressed with Eqs. (4.18)
(4.23).

163

164

CHAPTER 4 Hybrid nanofluids as a heat transferring media

4.3.1.1 Single-phase • Continuity equation @ρ 1 r:ðρ:vm Þ 5 0 @t

(4.18)

@ðρvÞ 1 r:ðρ:vm vm Þ 5 2 r:p 1 r:τ 1 D @t

(4.19)

 @ðρhÞ 1 r: ρvm Cp T 5 r:ðkrTÞ @t

(4.20)

 @ ϕ ρ 1 r: ϕi ρi vi 2 Γi rϕi 5 0 @t i i

(4.21)

 @ ϕ ρ vi 1 ϕi ½ρi vi vi 2 μi ðrvi 1 ðrvi ÞT Þ 5 ϕi ðDi 2 rpÞ 1 Fi @t i i

(4.22)

• Momentum equation

• Energy equation

4.3.1.2 Two-phase • Continuity equation

• Momentum equation

• Energy equation N 

 X @ ϕi ρi hi 1 r: ϕi ðρi hi vi 2 ki r:Ti Þ 5 Γij hjs 2 Γji his 1 Qi 1 Si @t j51

(4.23)

where D; Γ; h; Q; N; and S denoted the body force, dispersion coefficient, enthalpy, interphase heat transfer, number of phases, and external heat sources, respectively. Behzadmehr et al. [59] numerically investigated the convective heat transfer in a circular tube employing Cu/water. The study was conducted in the turbulent flow regime and analyzed the Nusselt number using single-phase and two-phase mixture modeling. Comparison of Nusselt number predicted by using these models with experimental results showed that mixture model more precisely predicts the values in comparison of single-phase model. A study conducted by Labib et al. [60] used the two-phase mixture model to study the forced convective heat transfer inside a circular tube. Investigators divided the whole study into three parts in first part a comparative study was carried out to investigate the convective heat transfer of the base fluids water and EG, in second part heat transfer for water-based unitary nanofluid of alumina was studies, while hybrid nanofluid of alumina
CNT was investigated in last part of this numerical study and draw a

4.3 Forced convection heat transfer

comparative study with Al2O3
water nanofluid. It was revealed that base fluid of EG showed the better heat transfer rate than water. A newly developed waterbased hybrid nanofluid of Al2O3
CNTs observed to offer augmented heat transfer because of high thermal conductivity of CNTs. This is because of better shear thinning behavior of CNTs that caused the thinner boundary layer, in these regions significant heat transfer was observed. Investigators following the single fluid two-phase approach (mixture model) to numerically analyze the performance of hybrid nanofluids, expressed with the help of following Eqs. (4.24)
(4.30). As discussed above (Eqs. 4.21
4.23) individual fluid properties were used for unitary nanofluid while for mixture model properties of the mixture was used to solve the continuity, momentum and energy equations.

• Continuity equation @ρm 1 r:ðρ:~ vmÞ 5 0 @t

(4.24)

where ρm and ~ v m denoted the mixture density and mass-average velocity, respectively, these can be expressed with Eqs. (4.25) and (4.26). ρm 5

N X

ϕi ρi

(4.25)

i51 N P

~ vm 5

vi ϕi ρi~

i51

(4.26)

ρm

• Momentum equation To obtain the mixture momentum equation, summarized the momentum equations of all phases individually and it can be expressed with Eq. (4.27) 

  @ ρ ~ v m 1 r: ρm~ v m~ v m 5 2 rp 1 r: μm r~ g v m 1 r~ v Tm 1 ρm ~ @t m ! N X ~ 1 r: v dr;i~ v dr;i 1D ϕi ρ i ~

(4.27)

i51

where ~ v dr;i symbolized the drift velocity for secondary phase i, expressed with Eq. (4.28). ~ v dr;i 5 ~ vi 2 ~ vm

(4.28)

N  N X   @X v i ρi Ei 1 p Þ 5 r: keff rT 1 OE ϕi ρi Ei 1 r: ðϕi~ @t i51 i51

(4.29)

• Energy equation

where OE denote the other volumetric heat transfer resources and Ei is expressed as with Eq. (4.30).

165

166

CHAPTER 4 Hybrid nanofluids as a heat transferring media

Ei 5 hi 2

p v2 1 i ρi 2

(4.30)

Shahsavar et al. [61] used the two-phase mixture model to investigate the influence of magnetic field on the thermal entropy generation and friction factor flowing the nanofluid of Mn
Zn ferrite ferrofluid through parallel plates. According to the investigators, magnetic effect caused the rotation of magnetic nanofluid and thus flow disruption and better thermal equilibrium. It was revealed that by augmenting the magnetic field thermal entropy generation decreased and friction factor increased. The same trend of friction factor and thermal entropy generation was observed with the increase in Re. Nimmagadda and Venkatasubbaiah [62] analyzed the thermal characteristics of various unitary and hybrid nanofluids using two-phase mixture model and compared the results with the experimental data of Kalteh et al. [63,64] and Eulerian
Eulerian multiphase approach to check the effectiveness of this technique. It was found that the data obtained using two-phase mixture model showed a good agreement with Kalteh et al. [63,64] experimental results and Eulerian
Eulerian multiphase approach. In addition, investigators also studied the base fluids (water and methanol) with different mixture ratios (20:80, 50:50, and 80:20). Nusselt number found to be enhanced with the increase in water fraction.

4.4 Heat transfer in porous media A substance or medium that have continuous pores through which fluid can flow is known as porous medium. Metal foams, ceramics, sand, and composite materials are few examples of porous medium, which have applications in cooling of electronic parts, high efficiency insulators and geothermal systems, etc. To improve heat transfer characteristics of porous media, researchers are employing hybrid nanofluid. Izadi et al. [9] numerically investigated effects of various parameters including Hartmann number ðHa 5 0 2 50Þ, magnetic number ðMnf 5 100 2 5000Þ, porosity coefficient ðE 5 0:1 2 0:9Þ, and strength ratio of two magnetic forces ðγ 5 0:2 2 5Þ on natural convective heat transfer coefficient using (MWCNT
Fe3O4/water) hybrid nanofluid inside the porous cavity. When γ is increased from 0.2 to 5 at Mnf 5 100, the Lorentz forces dominated over Kelvin forces which caused reduction in flow strength. For Mnf 5 1000, the flow strength initially reduced with enhancement in γ from 0.2 to 1 while becoming stronger with further increase in γ. The average Nusselt number showed improvement with increase in γ and Mnf values at low Rayleigh number (Ra). The deterioration of average Nusselt number was observed with elevation in Ha and γ at higher Ra. The increase in E decreased porous medium effect and thus turning it into pore-less medium, which as result degraded Nusselt number. The viscosity of hybrid nanofluid plays important role in heat transfer rate as fluid motion is directly dependent on it.

4.6 Concluding remarks

Free CHT of hybrid nanofluid (Cu
Al2O3/water, 0 # ϕ # 0:02) was analyzed by Mehryan et al. [10] in cavity with two various porous matrix (glass and aluminum) having porosity ðE 5 0:3 2 0:9Þ. The drastic increment in viscosity due to addition of (Al2O3
Cu) nanoparticles provided more resistance to buoyancy force, which leads to reduction in Nusselt number. The study concluded that reduction in heat transfer was more prominent for hybrid nanofluid when compared with mono-nanofluid. The thermal diffusivity ratio may vary with porosity when thermal conductivity of solid and liquid phases are nearly same. This was main reason behind the dependence of Nusselt number on porosity for glass ball matrix. Gholinia et al. [11] numerically studied effects of application of hybrid base nanofluid on stretching cylinder under influence of magnetic source. The impact of nanoparticle type was significant for heating and cooling processes. The parameters including Squeeze number (S 5 0.3
0.9), Magnetic parameter (M 5 0.5
24), and Reynolds number (Re 5 2
8) showed negative effect on heat transfer rate. The influence of SWCNT on temperature profile was greater when compared with MWCNT due to higher thermal conductivity. Lower density of MWCNT allowed more increase in velocity profile than SWCNT. The double multi relaxation time lattice Boltzmann method was applied by Sajjadi et al. [12] to investigate magnetohydrodynamics (MHD) natural convection of (Fe3O4
MWCNT/water) hybrid nanofluid in porous cavity under various parameters porosity ð0:4 # E # 0:9Þ, Rayleigh number ð103 # Ra # 105 Þ, Hartmann number ð0 # Ha # 50Þ, volume fraction of nanoparticles ð0 # ϕ # 0:003Þ, and Darcy number ðDa 5 1022 2 1021 Þ. The study concluded negative role of magnetic field and Hartmann number on heat transfer rate. The increase in Darcy number, Rayleigh number porosity enhanced heat transfer performance.

4.5 Theoretical studies and models for prediction of heat transfer The experimental studies proposed correlations to predict Nusselt number for various hybrid nanofluids under specific limitations. These correlations are usually function of Reynolds number, Prandtl number, and volume concentration of hybrid nanofluid. Various available correlations for prediction of hybrid nanofluid Nusselt number are compiled and presented in Table 4.2.

4.6 Concluding remarks Hybrid nanofluid is the advanced class of nanofluid that can be prepared by suspending two or more types of nanoparticles in the base fluid. In most of the studies, rate of heat transfer found to be improved by employing hybrid nanofluids in

167

Table 4.2 Correlations developed by researchers to predict Nusselt number for hybrid nanofluids. References

Hybrid nanofluid

Correlation

[35]

Al2O3
Cu/water

Nu 5 3:935 1 0:0106Ra

[37]

MWCNT
Fe3O4/water

Nu 5 0:0215Re0:8 Pr 0:5 ð11ϕÞ0:78

[39]

Al2O3
Cu/water

Nu 5 0:031ðRe:PrÞ0:68 ð11ϕÞ95:73

[65]

Al2O3
Cu/water

Nu 5 0:125Re0:592 Pr 1=3 ð11ϕÞ77:13

[66]

GNP
Ag/water

Nu 5 0:0017066Re0:9253 Pr 1:29001

[67]

Al2O3
Cu/water

Nu 5 0:3124Re0:2351 Pr 0:7341 ð11ϕÞ145:611

[68]

MWCNT
Al2O3/water

Nu 5 0:3762Re0:6681 Pr 0:4

[69]

Cu
TiO2/water

Nu 5 0:012Re:Pr 0:333 ϕ0:032

[70]

Al2O3
graphene/water

Nu 5 3:33ðRe:PrðD=LÞÞ0:21 ð11ϕÞ3:12

[71]

Al2O3
SiO2/water Al2O3
TiO2/water Nanodiamond
nickel/ water

Nu 5 0:0074Re0:9 Pr 0:67 ϕ0:063

[72]

0:488

ð11ϕÞ

Nu 5 0:22Re0:8 Pr 0:5 ð11ϕÞ0:86

8:59

Limitations

Deviation

103 # Ra # 106 ϕ , 2% 3000 , Re , 22000 0:1 , ϕ , 0:3% 4:5 , Pr , 6:13 700 # Re # 2300 ϕ 5 0:1% 700 # Re # 2300 ϕ 5 0:1% 5000 # Re # 17; 500 0 # ϕ # 0:1% 2576 # Re # 9262 ϕ 5 0:1% 182 , Re , 956 5:5 , Pr , 8 4000 , Re , 8000 0:1 # ϕ # 2% 100 , Re , 1600 0:3 # φ # 1% D 5 0:8; 1:1; and2:1 mm L 5 0:27 m 7800 , Re , 22; 000 3 # ϕ # 4% 3000 , Re , 22; 000 0 , ϕ , 0:3% 4:39 , Pr , 5:71

6 12% 6 8%

23% to 5% 6 7% 6 8.05% 6 3% 6 10% 24% to 7% —

2 1.5% to 2.5% 6 4.5%

[73]

Nanodiamond
nickel/ water

Nu 5 0:02433Re0:8 Pr 0:4 ð11ϕÞ1:193 ð11ARÞ0:0291 ðDh =Di Þ20:1532

[74]

TiO2
SiO2/water 1 EG (60:40)

Nu 5 0:023Re0:8 Pr 0:4 ð0:011T=70Þ0:05 ð110:01ϕÞ6:9

EG, Ethylene glycol; MWCNTs, multiwalled carbon nanotubes.

3000 , Re , 22; 000 0 , ϕ , 0:3% 4:35 , Pr , 5:85 0 , AR , 4 0 , ϕ , 3% 30℃ , T , 70℃

6 8.55%

6 9.9%

170

CHAPTER 4 Hybrid nanofluids as a heat transferring media

different application areas. However, more work should be done in this field of thermal fluids to enrich the heat transfer characteristics with a little penalty of pumping power in forced convection applications. The comprised study on hybrid nanofluids as a heat transferring media concluded the following important points:

• On the base of heat transfer augmentation, no one can decide the performance • •

• • • • • •

of hybrid nanofluids. It is the trade-off of advantages and disadvantages, thus the factors such as: cost and pumping power should also be considered. CHT is dominant at high Rayleigh number (above 104 in most of the studies), while at low Rayleigh number the effect of conduction heat transfer is more dominant. Reynolds number, particle concentration, and temperature are the factors that influenced heat transfer more significantly thus in most of the studies investigators considered these factors in the models developed for Nusselt number. Supplementation of nanoparticles above a certain limit could cause the diminution of heat transfer. In comparison of single-phase modeling, two-phase modeling showed better agreement with the experimental results. Entropy generation increases with an increase in particle concentration and decreases with Hartmann number. Heat transfer in porous media using hybrid nanofluid is still in immature level of understanding as more research work is required to explore the effect of various parameters on heat transfer rate. The hybrid nanoparticles lead to drastic enhancement in viscosity of base fluid, causing a reduction in buoyancy force which as result decrements the average Nusselt number. Studies also observed that Hartmann number diminishes the improvement in heat transfer rate as a result of increase in Rayleigh number.

Nomenclature Ag Al2O3 CHT CNTs Cu cp D Da EG Fe3O4 g GO

Silver Alumina Convective heat transfer Carbon nanotubes Copper Specific heat at constant pressure ðkJ=kg KÞ Body force (N/m3) Darcy number Ethylene glycol Iron oxide Gravitational acceleration (m/s2) Graphene oxide

Subscript

Ha h k M MgO MWCNT Nu p Q Ri Re S Si T TiO2 u, v W WO3 x, y Zn

Hartmann number Enthalpy (kJ/kg) Thermal conductivity ðW=m KÞ Magnetic number Magnesium oxide Multiwalled carbon nanotube Nusselt number Pressure Interphase heat transfer Richardson number Reynolds number Squeeze number Silicon Dimensional temperature (K) Titania Velocity components Water Tungsten oxide Dimensional coordinates Zinc

Greek letters α β λ ω μ ρ ϕ Θ σ Γ E

Thermal diffusivity ðm2 =sÞ Thermal expansion coefficient (1/K) Dimensionless stream function Dimensional vorticity ð1=sÞ Dynamic viscosity ðN s=m2 Þ Density ðkg=m3 Þ Particle volume fraction Transport quantity Electrical conductivity Dispersion coefficient (kg/ms) Porosity

Subscript bf c eff h i; j nf np s

Base fluid Cold Effective Hot Phases index Nanofluid Nanoparticle Solid particle

171

172

CHAPTER 4 Hybrid nanofluids as a heat transferring media

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234. Available from: https://doi.org/ 10.1016/j.ijheatmasstransfer.2018.05.021. [2] T.R. Shah, H.M. Ali, Applications of hybrid nanofluids in solar energy, practical limitations and challenges: a critical review, Sol. Energy (2019). Available from: https:// doi.org/10.1016/j.solener.2019.03.012. [3] H. Babar, H.M. Ali, Towards hybrid nanofluids: preparation, thermophysical properties, applications, and challenges, J. Mol. Liq. (2019) 598
633. Available from: https://doi.org/10.1016/j.molliq.2019.02.102. [4] C. Qin, K. Kang, I. Lee, B.J. Lee, Optimization of a direct absorption solar collector with blended plasmonic nanofluids, Sol. Energy 150 (2017) 512
520. Available from: https://doi.org/10.1016/j.solener.2017.05.007. [5] M. Hemmat Esfe, A. Alirezaie, M. Rejvani, An applicable study on the thermal conductivity of SWCNT-MgO hybrid nanofluid and price-performance analysis for energy management, Appl. Therm. Eng. 111 (2017) 1202
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MWCNT (85:15 %)
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5

Tayyab Raza Shah1, Hasan Koten2 and Hafiz Muhammad Ali1,3 1

Mechanical Engineering Department, University of Engineering and Technology, Taxila, Pakistan 2 Mechanical Engineering Department, Istanbul Medeniyet University, Istanbul, Turkey 3 Mechanical Engineering Department, King Fahad University of Petroleum & Minerals (KFUPM), Dhahran, Saudi Arabia

Chapter Outline 5.1 Introduction ...............................................................................................179 5.2 Nanoparticle concentration .........................................................................180 5.3 Basefluid ...................................................................................................184 5.4 Temperature ...............................................................................................186 5.5 Sonication time ..........................................................................................187 5.6 Surfactant addition .....................................................................................190 5.7 Particle size ...............................................................................................191 5.8 Brownian motion of nanoparticles ................................................................194 5.9 Particle shape ............................................................................................197 5.10 pH value ....................................................................................................201 5.11 Clustering effect .........................................................................................203 5.12 Conclusion .................................................................................................204 References ..........................................................................................................205

5.1 Introduction Hybrid nanofluids are prepared by blending two different kind of nanoparticles in the same basefluid to have greater thermophysical, optical, rheological, and morphological properties. Hybrid nanofluids are projected to replace simple nanofluids due to quite a number of reasons such as wide absorption range, lower extinction, high thermal conductivity, low pressure-drop, and low frictional losses and pumping power as compared to the mono nanofluids. Hybrid nanofluids have been tested for various applications like solar collectors, Hybrid Nanofluids for Convection Heat Transfer. DOI: https://doi.org/10.1016/B978-0-12-819280-1.00005-7 © 2020 Elsevier Inc. All rights reserved.

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photovoltaic thermal applications, electronic component thermal management, photovoltaic thermal management, machine cutting, engine applications, and automotive cooling [1 3]. Science of hybrid nanofluids is quite intricate in terms of their response to temperature, particle specifications, basefluid, surfactant, and pH value. Literature suggests that thermophysical properties like thermal conductivity tends to vary with temperature, nanoparticle size, and concentration [4 12]. Viscosity of the hybrid nanofluids is also reported to fluctuate with particle size, concentration, and pH [13 21]. Preparation steps of hybrid nanofluids influence the performance up to a great extent. Among the preparation steps, ultrasonication is of great significance because of the reason that the stability and thermophysical properties. Compatibility of nanoparticles and basefluid is also a crucial consideration when deciding the combinations to prepare hybrid nanofluids. Different scientific explanations have been presented in the literature to comprehend the behavior science of hybrid nanofluids. However, research still stands at a point where there is still inconclusiveness regarding the response of hybrid nanofluids to the variations in influencing factors [3,22 29]. No technology is of any worth unless it is made available in industrial/market usage [3]. Various suggestions have been put forward by the researchers to ensure industrial realization of hybrid nanofluids. Ensuring the stability of hybrid nanofluids is the most emphasized suggestion and ways to keep the hybrid nanofluids stable have been briefly discussed by Ali et al. [30]. Second most challenging factor is the pressure drop or frictional losses occurring during the flow of hybrid nanofluids. To ensure industrial realization of hybrid nanofluids, Shah and Ali [2] suggested several techniques as presented in Fig. 5.1. This chapter is focused to explain the behavior science of hybrid nanofluids and factors influencing their performance. Effect of particle specifications like size and shape, basefluid, surfactant, sonication period, pH value, Brownian motion, concentration of nanoparticles, temperature, and clustering has been briefly discussed in the following sections.

5.2 Nanoparticle concentration Effect of nanoparticle concentration on the characteristics of hybrid nanofluids is quite obvious. Implication of nanoparticle concentration on the properties and performance of hybrid nanofluids has been briefly explained along with underlying aspects. The most obvious effect of nanoparticle concentration is on thermal conductivity of the hybrid nanofluids. Sajid and Ali [23] comprehensively reviewed the factors influencing the thermal conductivity of hybrid nanofluids and found the concentration of nanoparticles to be the most critical factor affecting the thermal conductivity of the nanofluid. Concentration intensification is reported to linearly augment the thermal conductivity of hybrid nanofluids. Elevation in thermal conductivity in response to

5.2 Nanoparticle concentration

FIGURE 5.1 Steps for industrial realization of hybrid nanofluids [2].

concentration hike is mainly attributed to greater heat transfer surface area inside the fluid as well as high Brownian motion of nanoparticles. Greater surface area leads to greater convection heat transfer inside the colloidal suspension thus making the fluid more effective. Harandi et al. [19] reported greater impact of concentration on the thermal conductivity of F-MWCNTs-Fe3O4/ethylene glycol (EG) hybrid nanofluid at high temperature and similarly greater impact of temperature at high concentration. They observed 30% maximum enhancement in thermal conductivity ratio of hybrid nanofluid at maximum tested temperature and concentration (i.e., 50 C and 2.3 vol.%). Rostamian et al. [31] reported the same results for thermal conductivity of CuO-SWCNTs/H2O-EG hybrid nanofluid. They observed the same trends and intimated the same reasons as did Harandi et al. [19]. Esfe et al. [8] appraised the thermal conductivity variation of SiO2-MWCNTs/EG hybrid nanofluid and observed

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nonlinear augmentation in thermal conductivity. They found 22.2% increase in thermal conductivity ratio at highest points of tested temperature and concentration range. They attributed the greatest increase at high temperature and concentration to the plethora of collisions and suspended particles. Similarly Hassan et al. [32] also reported the same results for thermal conductivity of Cu-Ag/H2O hybrid nanofluid thus endorsing the findings of previous research studies. Effect of nanoparticle concentration on thermal conductivity of hybrid nanofluid could be seen from the Fig. 5.2. Like thermophysical properties, rheological properties of hybrid nanofluids are greatly influenced by the concentration of nanoparticles. Esfe et al. [33] appraised both thermal conductivity and viscosity of Ag-MgO/H2O hybrid nanofluid against nanoparticle concentration and observed significant increase in thermal conductivity and viscosity against nanoparticle concentration increase. Afrand et al. [15] examined the effect of concentration and temperature on viscosity of Fe3O4-Ag/ EG hybrid nanofluid and observed significant increase in viscosity with increasing nanoparticle loading. However, the viscosity was observed of drop with increasing temperature of the nanofluid. They attributed the viscosity drop to the weakening van der Waals forces due to temperature rise (Fig. 5.3).

FIGURE 5.2 Effect of nanoparticle concentration on thermal conductivity of hybrid nanofluid [19].

5.2 Nanoparticle concentration

FIGURE 5.3 Effect of nanoparticle loading on viscosity of hybrid nanofluid [15].

Esfe et al. [34] in another study explored the dynamic viscosity of MWCNTsSiO2/SAE40 and observed the same findings and trends as shown in Fig. 5.3. Topmost enhancement in hybrid nanofluid’s viscosity was reported to be 30.2%. Moreover, Soltani and Akbari [35] examined the dynamic viscosity of MgOMWCNT/EG hybrid nanofluid and Asadi and Asadi [19] tested the dynamic viscosity of MgO-MWCNT/EG and MWCNT-ZnO/Engine Oil hybrid nanofluid respectively and reported the similar trends, that is, viscosity was highest at highest concentration and lowest temperature. Greater number of nanoparticles, that is, high concentration causes greater number of interactions between the nanoparticles which makes the viscosity to increase. Increase in concentration does not only causes high thermal conductivity and viscosity but it also causes greater agglomeration of nanoparticles which makes system’s performance vulnerable. Ali et al. [36] observed the system performance to increase from 0.01 to 0.2 vol.% concentration and then the performance dropped when the concentration increased up to 0.3 vol.% (Fig. 5.4). Therefore, it is highly recommended to wary of the consequences of high concentration when preparing a nanofluid.

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FIGURE 5.4 Effect of nanoparticle concentration on system performance [36].

Cost of the hybrid nanofluid can be easily manipulated and the system could be made economical in this way. Despite of increasing the concentration of nanoparticles in a mono nanofluid and making it vulnerable to cluster formation, it is recommended to introduce another nanoparticle of greater thermal conductivity and prevent the danger of clustering and cost elevation.

5.3 Basefluid Basefluid is of critical significance when it comes to the success of a nanofluid. Nanofluids were primarily developed to improve the thermophysical characteristics of conventional Thermofluids, therefore, a particular nanoparticle behaves differently in different basefluids. Water, EG, water EG mixture, thermal oils and some other lubricants have been tested as basefluids. Thermophysical properties (such as thermal conductivity, viscosity, pressure drop, frictional losses), optical properties (such as absorptivity, emissivity, extinction coefficient and scattering coefficient), and stability of a nanofluid is entirely dependent of the mentioned characteristics of the basefluid since, the insertion of nanoparticles can only addup to the magnitude of those properties. Selection of basefluid for a particular nanoparticle is indeed a critical concern because of the fact that chemical interaction has its own implications. For instance, carbon nanotubes (CNTs) or graphene nanoplatelets (GNPs) are primarily hydrophobic in nature and therefore they do not suspend in water because of

5.3 Basefluid

FIGURE 5.5 Chemical activation process of GNPs (functionalization of GNPs and preparation of nanofluid) [37]. GNPs, Graphene nanoplatelets.

their noninteractive chemical nature. Hence, CNTs are first made functional via some functionalization method and then dispersed in the basefluid (Fig. 5.5). Some of the researchers have conducted brief analysis both experimental and numerical of the effect of basefluid on thermophysical properties and performance of hybrid nanofluids. Timofeeva et al. [38] observed greater improvement in thermophysical properties of water EG basefluid than the simple water when SiC nanoparticles were added. The smaller improvement in thermal conductivity of water was attributed to the fact that water already had greater thermal conductivity than the water EG mixture (Fig. 5.6). Kumar et al. [39] conducted brief analysis of effect of basefluid on thermal conductivity and viscosity of the Cu-Zn hybrid nanofluid. They tested three different basefluids namely; vegetable oil, paraffin oil, and SAE oil. The results indicated that vegetable oil outperformed rest of the basefluids in terms of relative viscosity and relative thermal conductivity. Similar analysis were conducted by Reddy and Chamkha [40], they also held basefluid to be an influential factor. Thermal conductivity enhancement ratio

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FIGURE 5.6 Effect of basefluid on percentage enhancement in thermal conductivity of the nanofluid [38].

TCR is reported to decrease with increasing viscosity of the basefluid by Tsai et al. [41]. Same sort of studies have been conducted by Labib et al. [42] and Bayat and Nikseresht [43]. Above discussion reflects that the mutual compatibility of basefluid and nanoparticles from the chemical perspective is of ultimate significance for the success of prepared hybrid nanofluid.

5.4 Temperature There is no ambiguity regarding the effect of temperature on the performance and thermophysical properties of hybrid nanofluids. Since increase in temperature results in increased kinetic energy of the nanoparticles and the interaction due to greater Brownian motion is enhanced thus increasing the thermal conductivity of hybrid nanofluids. Contrary to thermal conductivity, viscosity of the hybrid nanofluids undergoes a significant alleviation as a result of temperature increase

5.5 Sonication time

FIGURE 5.7 Effect of temperature on viscosity ratio and viscosity of SiO2-MWCNT/SAE40 hybrid nanofluid [44].

however, relative viscosity is reported to increase as well as shown in Fig. 5.7. Temperature increase also increase the stability of the hybrid nanofluids [44 47]. Despite of positive impact on thermophysical properties, temperature enhancement does not always improve the performance of the system employing hybrid nanofluid because of operational limitation of the particular system. Liu et al. [48] employed nanofluid as working fluid in direct absorption solar collector and observed decrease in efficiency of the system with increasing temperature (Fig. 5.8). If nanofluids are employed for cooling purposes, the effect of nanofluid’s temperature elevation is not always beneficial since temperature augmentation also causes the heating of system’s components. Therefore, it is necessary to operate the system at optimum temperature in spite of upper range of temperature.

5.5 Sonication time Sonication is the most important process in the preparation of nanofluids. Sonication is carried out in a ultrasonication path, ultrasonic vibrator, and mechanical homogenizer following the magnetic stirring of mixture in magnetic stirrer. Ultrasonication frequency is reported to be 20 40 kHz. Apart from sonication frequency and power, sonication time is the most crucial part of the process. Stability of the prepared nanofluid is greatly dependent of the time of sonication. Researchers have linked the stability of the nanofluids directly with the sonication span however, there comes a point past which the stability and thermophysical properties start to deter. Sonication is performed to achieve multiple purposes including deagglomeration of nanoparticles, size reduction, and dispersion in the basefluid. Most general

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FIGURE 5.8 Effect of temperature on solar collector’s efficiency employing nanofluid [48].

observation as reported by the researchers it that the nanofluid characteristics tend to improve up to some specific ultrasonication time and then start to fray. Asadi et al. [49] investigated the influence of ultrasonication time on thermophysical properties and stability of the MWCNT-H2O nanofluid over the course of 30 days. They varied the sonication period from 10 to 80 minutes for various samples of nanofluid (0.1, 0.3, and 0.5 vol.%) and observed that the stability of the samples started to deter past 60 minutes sonication. Maximum thermal conductivity enhancement was also observed at 60 minutes sonication period. Stability of the nanofluid sample sonicated for 80 minutes was observed to deter after 5 days of preparation and then the sample sonicated for 75 minutes started to sediment. After 30 days, the samples sonicated for 60 minutes and less were found to be stable. Similar observations have been reported for the thermal conductivity against sonication time as well (Fig. 5.9). Garg et al. [50] performed similar tests for CNT-based nanofluids and analyzed thermal conductivity, viscosity, and convective heat transfer. Prolonging the sonication period lets the particles to coalesce again thus the particle size tends to mount causing thermal conductivity to decrease. Kole and Dey [51] appraised the effect of sonication period on ZnO-EG nanofluid and observed the aforementioned phenomenon as shown in Fig. 5.10. During ultrasonication, size of nanoparticles

5.5 Sonication time

FIGURE 5.9 Effect of sonication period on stability (A C) and thermal conductivity of MWCNT water nanofluid (D) [49].

FIGURE 5.10 Effect of sonication on particle size: (A) TEM image of nanofluid samples subjected to 4, 12, 60, and 100 h of ultrasonication (a d) and (B) size variation against sonication period [51]. TEM, Transmission electron microscopy.

initially decreases due to dispersion energy and then after specific time interval the particles start to agglomerate and hence the size tends to increase. Li et al. [52] experimentally appraised the stability, thermal conductivity, and viscosity of the Cu-EG nanofluid and observed an increase in stability and

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thermal conductivity and decrease in viscosity up to a certain sonication time period and then due to reformation of clusters (coalesce). It is to be considered that the insertion of nanoparticles increases the viscosity of hybrid nanofluids and the viscosity enhancement is maximum when the dispersion is uniform. Nonetheless, viscosity agglomeration results in reduced viscosity of hybrid nanofluids. A plethora of studies have been conducted to the subject and almost same outcomes have been reported as discussed in the prior discussion [53 60].

5.6 Surfactant addition Various chemical substances are employed as surfactant during the preparation of hybrid nanofluids. Purpose of surfactant addition is to enable the hybrid nanofluids last longer with uniform dispersion of nanoparticles. Most commonly used surfactants are Gum Arabic (GA), sodium dodecyl sulfate (SDS), sodium dodecyl benzene sulfonate (SDBS), cetyltrimethylammonium bromide (CTAB), polyvinyl pyrrolidone (PVP), etc. Insertion of surfactants optimizes the pH value of the solution and surface tension. Surfactants are also used for surface activation. Some acids like HCL could also be used as pH control substance. Effectiveness of surfactant is linked with the chemical nature of the fluid. Different surfactants perform differently in the same fluid. Therefore, appropriate surfactant should be opted for the given nanofluid. Xian et al. [61] conducted brief analysis of the effect of different surfactants including CTAB, SDS, and SDBS on the stability of GNPs/H2O-EG and GNPsTiO2/H2O-EG hybrid nanofluids and observed CTAB to be the best surfactant (Fig. 5.11). Hormozi et al. [62] appraised the effect of different surfactants on thermal conductivity and performance of hybrid nanofluid based system. Al2O3-Ag/water hybrid nanofluid samples were prepared with different surfactant (SDS and PVP). They reported SDS to be the best performer. Addition of surfactant not only prolongs the stability period, but it also can increase the thermal conductivity of the nanofluid. Gangadevi et al. [62] tested nanofluid samples of Al2O3/water and CuO/water with and without surfactant (SDBS). They obtained greatest thermal conductivity for the samples containing surfactant. The underlying reason for this outcome is the reduced surface tension due to surfactant. Chakraborty et al. [63] tested the effectiveness of SDS and Tween-20 surfactant for Cu-Zn-Al LDH nanofluid and reported SDS to be the best one. They found the surface tension value of SDS surfactant based nanofluid to be slightly smaller than the surface tension values for nanofluid samples containing Tween-20. Viscosity of the nanofluids has been reported to decrease with surfactant addition however contrary results are also available in the literature. pH value of the nanofluids has also been reported to vary due to the addition of surfactants. The underlying science of effect of surfactant on the thermophysical properties has been briefly discussed in the literature [64 72].

5.7 Particle size

FIGURE 5.11 Stability of COOH-GNPs/H2O-EG mono nanofluid and COOH-GNPs-TiO2/H2O-EG hybrid nanofluid [61]. EG, Ethylene glycol.

5.7 Particle size Size of nanoparticles is exceedingly important factor that influences the overall effectiveness of hybrid nanofluids. A number of research articles have reiterated the significance of nanoparticle size. Size of nanoparticles brings about variation in stability, surface area to volume ratio, Brownian motion, thermal conductivity, optical characteristics, and viscosity. Size of the nanoparticles in nanofluids is specified by an image called electron micrograph which is developed by using

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transmission electron microscopy (TEM) or scanning electron microscopy (SEM). Some other tests used for characteristic evaluation of nanofluids include X-ray diffraction, field-emission scanning electron microscopy, high-resolution transmission electron microscopy, Fourier transmission infrared spectroscopy (FT-IR), dynamic light scattering, and UV spectroscopy. Size of nanoparticles in nanofluids is supposed to be less than 100 nm however, some studies have discussed the nanoparticle size up to 210 nm. Nanoparticle size is controlled by different means in different preparation methods. In single step preparation method of nanofluids, size of particles is controlled by controlling the degree of superheat and pressure applied. In case of two step method, the nanoparticle size is manipulated while mechanical pulverization of metals. Most significant consequence of nanoparticle size is felt on thermal conductivity of hybrid nanofluids. Thermal conductivity of nanofluids is the most critical parameter that determines the effectiveness of the particular fluid. Diverse results have been reported in literature regarding the effect of nanoparticle size on thermal conductivity of hybrid nanofluid, nevertheless, most common observation is that the smaller nanoparticle size nanofluids tend to have higher thermal conductivity. Mintsa et al. [73] conducted an experimental study to appraise the effect of nanoparticle size on thermal conductivity of Al2O3/water and CuO/water nanofluids. They tested 36 and 47 nm Al2O3 nanoparticle sizes. Following the brief experimental results, they found that the nanoparticles with smaller diameter carried higher thermal conductivity. They attributed the higher thermal conductivity of smaller size nanofluids to higher contact (surface) area and higher Brownian motion owing to greater number of nanoparticles. Chopkar et al. [74] experimentally analyzed the influence of nanoparticle size variation on thermal conductivity of Al2Cu and Ag2Al nanoparticles based nanofluids. They tested 30 40 nm range of nanoparticles. They observed decrease in thermal conductivity with increasing nanoparticle size. Experimental results obtained by Chopkar et al. [74] have been shown in Fig. 5.12. Teng et al. [75] also reported the same findings as they observed hike in thermal conductivity with reducing size of nanoparticles of Al2O3 dispersed in water. They observed the thermal conductivity ratio to increase from 1.045 to 1.145 as the particle size decreased from 100 to 20 nm at 50 C and 2 vol.%. TEM image of aforementioned fluid samples is shown in Fig. 5.13. He et al. [76] also reported increase in thermal conductivity enhancement (%) of TiO2/water nanofluid with decreasing nanoparticle size. TCE increased from 1% to 3.4% as the nanoparticle size decreased from 210 to 95 nm respectively. Timofeeva et al. [77] conducted experimental appraisal of dependency of heat transfer and thermophysical characteristics of α-SiO2/water nanofluid on nanoparticle size. A range of 16 90 nm size of nanoparticles was examined in the study and they reported the thermal conductivity to be high at higher nanoparticle size. Shalkevich et al. [78] evaluated the thermal conductivity of gold nanoparticles based nanofluids. They examined the gold nanofluid samples having different sized nanoparticles - suspending inside. They used a range of 2 45 nm and

5.7 Particle size

FIGURE 5.12 Response of thermal conductivity of nanofluids to nanoparticle size variation [74].

FIGURE 5.13 TEM image of nanoparticles of Al2O3 of size 20 nm (A), 50 nm (B), and 100 nm (C) [75].

observed maximal thermal conductivity for nanofluid having 40 nm size nanoparticles of gold. Beck et al. [79] tested a wide range of nanoparticle size (8 282) of Al2O3 nanoparticles dispersed in water basefluid and EG basefluid. They also reported reduction in thermal conductivity elevation with reducing size of nanoparticles. Besides these studies, many research activities have been performed to draw conclusive results regarding the effect of nanoparticle size on thermal conductivity like the studies by Patel et al. [80], and Chopkar et al. [81]. There are also some studies that reported no effect of particle size on the performance of nanofluid [1]. Nonetheless, the most established narrative is the one which states that the size reduction leads to greater thermal conductivity of nanofluids with the justification that smaller size nanoparticles provide greater specific area for heat transfer and since smaller size of nanoparticles implies greater number of particles therefore, higher Brownian motion would take place leading to higher thermal conductivity [23].

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Effect of particle size on viscosity of hybrid nanofluids is inconclusive as yet. There are two contradictory notions pertaining to the subject. Some of the researchers are of the view that increased size of particles leads to higher viscosity of hybrid nanofluids whereas some have the other opinion. Hamza et al. [82] critically analyzed the subject in their extensive review of viscosity of hybrid nanofluids. Following the analysis, they concluded that the number of studies focused on evaluation of implication of particle size on viscosity of hybrid nanofluids. Nevertheless, the effect of particle size on viscosity of nanofluids is quite pronounced regardless of in what way it affects. Significance of particle size can be understood by the fact that for different sizes different formulas have been devised by the researchers for predicting the viscosity of the fluid [28]. Performance of hybrid nanofluid based systems is found to be influenced by the size of nanoparticles. Review of past literature shows that particle size plays critical role in the operational success of hybrid nanofluids in solar energy systems. In solar systems, if appropriate size of nanoparticles is used, quite a number of losses—scattering in particular—could be averted. Scattering becomes extremely prominent if the particle size gets greater than 40 nm which causes the system efficiency to decline by a great extent. However, when the size of particles is less than 16 nm, the scattering effects becomes almost negligible. Therefore, it is useful to keep the particle size as small as possible for efficient operation of converting light energy into desired energy form. Nevertheless, there are different opinion regarding the overall effect of nanoparticle size on the performance of solar collectors using hybrid nanofluids. Some research studies claim to high system efficiency with larger particle size. Stability of hybrid nanofluids is influenced by the particle size to the nth degree. It has been observed by the researchers that the greater size of nanoparticles results in earlier sedimentation. Larger size of nanoparticles makes the nanofluids extremely vulnerable to agglomeration and consequently cause the stability to vanish. Ali et al. [30] reviewed that the size of nanoparticles tends to increase when dispersed in the basefluid due to the agglomeration. Babu et al. [28] reported that the speed of nanoparticle sedimentation is predominantly influenced by their size. Decreasing the particle size could lead to slower sedimentation. There is a critical value of nanoparticle size at which the sedimentation is expected to be zero. Critical size of nanoparticles is computed by Eq. (5.1). V5

 2R2
ρnp 2 ρbf 9μbf

(5.1)

In Eq. (5.1), ‘R’ is the nanoparticle size, ‘μ’ is the viscosity, and ‘ρ’ represents the density, whereas ‘V’ is the particle velocity in the basefluid.

5.8 Brownian motion of nanoparticles Brownian motion is the random/zigzag motion of suspended nanoparticles in basefluid mainly occurring due to the interaction between the particles. Brownian

5.8 Brownian motion of nanoparticles

motion causes the transfer of momentum/kinetic energy from faster particles to the low velocity particles. This motion of nanoparticles is credited for their suspension stability and thermal transportation. Brownian motion of nanoparticles affects the thermal conductivity and stability of hybrid nanofluids. Whereas, Brownian motion itself is greatly influenced by the nanoparticle size, temperature, and viscosity of fluid (basefluid/nanofluid). To evaluate the impact of Brownian motion on thermal conductivity and viscosity of hybrid nanofluids, a number of research activities have been carried out. High thermal conductivity of hybrid nanofluids is the most infectious aspect of hybrid nanofluids which is reported to increase with increase in temperature owing to the fact that the Brownian motion of nanoparticles gest enhanced in response to temperature escalation. Esfahani et al. [11] observed the thermal conductivity of ZnO-Ag/water (2 vol.%) hybrid nanofluid to increase from 0.65 to 0.81 W/m K when temperature increase from 25 C to 50 C. They held higher particle Brownian responsible for improvement (Fig. 5.14). Similar trends have been reported by the other researchers as well [5,6,8 12,19]. Brownian motion of smaller particles has been reported to be much higher than the larger ones. Smaller size of nanoparticles implies greater number of nanoparticles

FIGURE 5.14 Effect of temperature on thermal conductivity of ZnO-Ag/water hybrid nanofluid.

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in turn high number of collisions. Higher Brownian motion of particles with decrease in size could recognized by increasing thermal conductivity of nanofluid with decreasing size of nanoparticles. Arani et al. [83] reported the thermal conductivity of alumina nanofluid to increase with particle size alleviation from 60 to 20 nm. Graph of their experimental results has been shown in Fig. 5.15. Brownian motion enables the nanoparticles to stay suspended in the basefluid therefore, extent of Brownian motion of particles is exceedingly crucial for the colloidal suspension stability. High Brownian motion enables the nanofluids to last longer and perform efficiently. Since Brownian motion is high for smaller nanoparticles and high temperature, it can be inferred that the stability of hybrid nanofluids lasts longer if the temperature is high and the size of particles is small. Size of nanoparticles for successful suspension due to Brownian motion is predicted by Eq. (5.2) [84]. 0 d5@

114 6kB T


A πg ρnp 2ρbf

FIGURE 5.15 Nanoparticle size effect on thermal conductivity of nanofluid [83].

(5.2)

5.9 Particle shape

In the equation ‘kB’ is the Boltzmann constant, ‘T’ is the temperature (absolute), and ‘d’ is the diameter of nanoparticles. Brownian motion of nanoparticles is heavily affected by the viscosity of the basefluid. Greater viscosity of the basefluid cause the Brownian motion of nanoparticles in hybrid nanofluids to slow down. In turn, it is highly suitable for the basefluid to have small value of viscosity so as to permit high Brownian motion. It is also of great consideration that although smaller sized nanoparticles possess high Brownian motion and as a result the thermal conductivity of the fluid becomes greater but smaller size nanoparticles increase the viscosity of the nanofluid way greater than the large sized nanoparticles do [77].

5.9 Particle shape Different shapes of nanoparticles have been reported in the literature namely; spherical, cylindrical, platelets, nanorods, and blade/laminar. Shape of the nanoparticles could be examined via electron micrographs (microscopy) or spectroscopic tests like UV spectroscopy or FT-IR spectroscopy (Table 5.1). Table 5.1 Different shapes and shape factors of nanoparticles [85]. Shape

Name

Shape factor (n)

Spherical

3.0

Platelet

5.7

Cylindrical

4.8

Blade/laminar

Brick

16.2

3.7

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Shape effect on nanofluid operation has been appraised by adequate number of researchers. It is of common observation that the nanoparticles having cylindrical shape have greater value of thermal conductivity. CNTs (cylindrically shaped) nanoparticles have 3000 W/m K thermal conductivity for MWCNTs and 1500 W/ m K thermal conductivity for SWCNTs whereas, spherically shaped nanoparticles of SiO2, TiO2, ZnO, MgO, CuO and Al2O3 possess thermal conductivities in the range of 1.4 48.44 W/m K. Nine et al. [86] observed significant role of shape of nanoparticles on the thermal conductivity of hybrid nanofluids. They analyzed Al2O3-MWCNT/water hybrid nanofluid and found that cylindrical shape nanoparticles tend to magnify the thermal conductivity of hybrid nanofluids way greater than the spherical shaped nanoparticles. Chopkar et al. [81] also reported that the spherical shaped nanoparticles caused smaller thermal conductivity escalation as compared to cylindrical and plate like nanoparticles. Timofeeva et al. [38] conducted experimental research to examine the effect of particle shape on alumina/ EG water nanofluid. They found the blade shaped nanoparticles to be the greatest thermal conductivity carrying particles than platelet, cylindrical and brick shaped nanoparticles (Fig. 5.16). In contradiction to all these studies, Arani et al.

FIGURE 5.16 Effect of particle shape on thermal conductivity of nanofluids [38].

5.9 Particle shape

FIGURE 5.17 Effect of particle shape on Nusselt number of nanofluids [83].

[83] reported the spherical shaped nanoparticles of alumina to depict greatest Nusselt number in wavy mini channel experiments (Fig. 5.17). Stability of nanofluids is also associated with nanoparticle shape. It is important for the nanoparticles to carry both high stability and high thermal conductivity otherwise; they will be of no use. SiO2 (spherical) nanoparticle based nanofluids have been reported to have high stabilities but the issue is their low thermal conductivity. On the other hand, despite of high thermal conductivity, CNTs have very little stability. Thus, there is a need to find some way to prepare fluid that could last longer and depict high thermal conductivity. Kim et al. [87] made an endeavor of this purpose and successfully developed nanofluid that had both high stability as well as thermal conductivity. Alumina-water nanofluid samples with different particle shapes (i.e., brick, platelet, and blade) were pared and were brought under examination. They observed that the nanofluid sample containing brick shaped nanoparticles possessed higher thermal conductivity and stability (Fig. 5.18). Quite a number of studies have discussed the effect of particle shape on convective heat transfer performance and thermophysical properties of nanofluids

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FIGURE 5.18 Stability and thermal conductivity comparison of different Al1O3/water nanofluid samples [87].

[38,81,83,86 95]. Olatundun and Makinde [91] tested five different shapes of nanoparticles of Al2O3-CuO. They observed that increase in Nusselt number of Al2O3-CuO/water hybrid nanofluid is greatest for blade shaped nanoparticles sample as compared to the samples containing platelet nanoparticles, cylindrical nanoparticles, brick shaped nanoparticles, and spherical nanoparticles. Similarly Ghadikolaei et al. [90] inspected the influence of particle shape on the thermophysical performance of TiO2-Cu/H2O hybrid nanofluid. They found the platelet shape to be more effective as compared to brick shape and cylindrical shape of nanoparticles. Vanaki et al. [95] also found platelet shaped nanoparticles based nanofluid sample to be more effective in wavy channels. Nonetheless, cylindrical shaped nanoparticles were found to be best among the other shaped nanoparticles for heat exchanger applications because of higher overall heat transfer coefficient by Elias et al. [89] and Elias et al. [88]. Entropy generation minimalization was reported to be greatest for cylindrical shaped nanoparticles as compared to rest of the particles having different shapes (other than cylindrical, i.e., platelet, brick, and blade). In light of above discussion, operational superiority of any of the shapes of nanoparticles is inconclusive as yet since quite diverse results have been observed

5.10 pH value

in the literature. Further research must be conducted to draw clarity about this specific subject.

5.10 pH value pH of colloidal solutions is a climacteric aspect of hybrid nanofluids. pH value of colloidal solutions is manipulated via the introduction of surfactants in the mixtures. Apart from pH variation, inclusion of surfactants in the hybrid nanofluids has several other implications such as variation in viscosity and intermolecular forces (electro kinetic characteristics). Commonly used surfactants are CTAB, SDS, HCL, sulfuric acid, etc. In a nanofluid, when the number of oppositely charged ions become equal, agglomeration becomes maximum and the solution is said to be equipotential/isoelectric. At this point, the mixture becomes unstable and requires pH manipulation via some sort of surfactant. For a stable suspension, pH of the mixture should be as far as possible from the isoelectric point’s pH value (DLVO theory of colloidal suspension) [96]. pH value of a solution is measured by pH meter or conventionally with pH strips. Different hybrid nanofluids have been found to be stable at different pH values. Optimum value of pH varies from one fluid to other fluid. Optimum pH was reported to be 11 for SiO2-graphene/naphthenic-oil nanofluid by Qing et al. [97]. They attributed the maximum stability and high heat transfer at this pH value to the increased surface charge. Higher surface charge offers greater intermolecular repulsion thus making the dispersion more uniform and stable. It has also been that hybrid nanofluids possess maximal thermal conductivity when their pH is closer to that of the basefluid. This phenomenon was briefly studied by Leong et al. [10]. Their result has been presented in Fig. 5.19. They observed maximum thermal conductivity of Cu-TiO2/water EG hybrid nanofluid at 7 pH value. Esfe et al. [33] reported the maximum stability of Ag-MgO/water hybrid nanofluid at 5.74 pH value. Similarly Suresh et al. [98,99] reported the maximum stability of Al2O3-Cu/water hybrid nanofluid at 6 pH value. They stated the same reason behind the stability at this pH as was stated by Qing et al. [97]. Nevertheless, there are also research studies available that have the different opinion, that is, they reported to have achieved better thermal conductivity at 8.5 9.5 pH value [100]. Strong effect of pH has been reported on viscosity of the nanofluids in the literature. Research studies have reported the viscosity alleviation as the pH value gets greater than the neutral value (i.e., 7) whereas, an increase in viscosity below the neutral value has been reported Fig. 5.20. Considering the literature, different particles based nanofluids have different value of optimum pH values in terms of both thermal conductivity and viscosity however, it mandatory for the fluids to have pH value different from the isoelectric point. Increase in concentration of nanoparticles has also been reported to increase the pH value.

201

FIGURE 5.19 Thermal conductivity variation against pH value of Cu-TiO2/water EG hybrid nanofluid [10]. EG, Ethylene glycol.

FIGURE 5.20 pH value effect on viscosity of SiC-water nanofluid [77].

5.11 Clustering effect

5.11 Clustering effect Clustering of nanoparticles is the most unwanted phenomenon in hybrid nanofluid. Formation of clusters mainly occurs due to low surface charge and inappropriate combination of nanoparticles. pH value and concentration of nanoparticles are the two main underlying reasons for cluster formation in hybrid nanofluids. Cluster formation not only causes heat transfer performance deterioration, but it also causes the nanoparticles to sediment and perish the stability of nanofluids. It has been reported in the past studies that despite of good initial colloidal dispersion, nanoparticles tend to form clusters and thus increase the nanoparticle size and density which makes gravitation force to prevail and settle down the nanoparticles in the basefluid. Cluster formation cause the viscosity of hybrid nanofluids to increase as well. Clustering can be more clearly visualized at isoelectric point at which number of positive charges become equal to negative charges (Fig. 5.21). All the above stated phenomenon makes the thermal conductivity, viscosity, and other important properties time dependent since clustering become prominent with elapsing time. Thermal conductivity of nanofluids tends to decrease with time and viscosity tends to increase with time. Karthikeyan et al. [102] evaluated the clustering and time dependency of thermal conductivity of CuO/water EG nanofluids and observed significant drop of thermal conductivity with time.

FIGURE 5.21 Stability deterioration of nanofluids due to clustering/sedimentation of nanoparticles with time [101].

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FIGURE 5.22 Time dependency of thermal conductivity of Fe nanofluid (EG as basefluid) [103]. EG, Ethylene glycol.

Similarly Hong [103] evaluated the time dependency of thermal conductivity and cluster size. He observed significant cluster size escalation and thermal conductivity alleviation with time (Fig. 5.22). Clustering cause particle’s hydraulic diameter size escalation which cause viscosity enhancement and elevation in pressure drop. Hence, clustering cause great operation challenge for nanofluid based systems [104].

5.12 Conclusion Brief review of literature reveals that hybrid nanofluids experience significant variation in thermophysical and rheological characteristics in response to variation in nanoparticle size, nanoparticle shape, nanoparticle concentration, basefluid, surfactant, sonication period, temperature, pH value, nanoparticle Brownian motion, and clustering. Considering the findings of discussed studies, following considerations could be drawn:

• foremost influencing parameter is the concentration of nanoparticles on the thermophysical properties and operation success of hybrid nanofluids. Increase

References

•

• • • •

in volumetric concentration nanoparticles leads to higher thermal conductivity and heat transfer rate. However, high concentration also causes high viscosity, frictional losses and pressure drop; effect of nanoparticle size and shape is still inconclusive. Some studies report the thermal conductivity and viscosity to increase with decreasing size of nanoparticles whereas, some few studies have presented opposite results. Cylindrical shaped nanoparticles based nanofluids have been reported to carry much higher thermal conductivity as compared to spherical ones however, cylindrical shaped nanoparticles based nanofluids exhibit very little stability period; temperature has quite clear influence on hybrid nanofluids, increase temperature causes increase in thermal conductivity and reduction in viscosity and pressure drop; Brownian motion of nanoparticles is the most important factor that enables the nanoparticles to stay suspended and carry quite infectious thermophysical characteristics; pH value of hybrid nanofluids must be far from the pH of isoelectric point. pH value affects value of surface charge and stability of the nanoparticles greatly; and clustering causes increase in hydraulic diameter which makes viscosity of hybrid nanofluids to elevate. Clustering is one of the most adverse phenomena hindering the practicability of hybrid nanofluids.

In light of the findings of this study, it is suggested to conduct some research activities to inspect conclusive impact of nanoparticle size and shape on thermal conductivity and viscosity.

References [1] H.M. Ali, T.R. Shah, H. Babar, Z.A. Khan, Application of nanofluids for thermal management of photovoltaic modules: a review, Microfluid. Nanofluidics, InTech, 2018. Available from: http://dx.doi.org/10.5772/intechopen.74967. [2] T.R. Shah, H.M. Ali, Applications of hybrid nanofluids in solar energy, practical limitations and challenges: a critical review, Solar Energy 183 (2019) 173 203. Available from: https://doi.org/10.1016/j.solener.2019.03.012. [3] H. Babar, H.M. Ali, Towards hybrid nanofluids: preparation, thermophysical properties, applications, and challenges, J. Mol. Liq. 281 (2019) 598 633. Available from: https://doi.org/10.1016/j.molliq.2019.02.102. [4] M.F. Nabil, W.H. Azmi, K.A. Hamid, N.N.M. Zawawi, G. Priyandoko, R. Mamat, Thermo-physical properties of hybrid nanofluids and hybrid nanolubricants: a comprehensive review on performance, Int. Commun. Heat Mass Transf. 83 (2017) 30 39. Available from: https://doi.org/10.1016/j.icheatmasstransfer.2017.03.008.

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[84] F. Yu, Y. Chen, X. Liang, J. Xu, C. Lee, Q. Liang, et al., Dispersion stability of thermal nanofluids, Prog. Nat. Sci. Mater. Int. 27 (2017) 531 542. Available from: https://doi.org/10.1016/j.pnsc.2017.08.010. [85] G. Sobamowo, A. Akinsholo, A. Yinusa, Thermo-Magneto-Solutal squeezing flow of nanofluid between two parallel disks embedded in a porous medium: effects of nanoparticle geometry, slip, and temperature jump conditions Thermo-Magneto-Solutal squeezing flow of nanofluid between two parallel D (2018). [86] M.J. Nine, M. Batmunkh, J.-H. Kim, H.-S. Chung, H.-M. Jeong, Investigation of Al2O3-MWCNTs hybrid dispersion in water and their thermal characterization, J. Nanosci. Nanotechnol. 12 (2012) 4553 4559. Available from: https://doi.org/ 10.1166/jnn.2012.6193. [87] H.J. Kim, S.-H. Lee, J.-H. Lee, S.P. Jang, Effect of particle shape on suspension stability and thermal conductivities of water-based bohemite alumina nanofluids, Energy 90 (2015) 1290 1297. Available from: https://doi.org/10.1016/j.energy.2015.06.084. [88] M.M. Elias, I.M. Shahrul, I.M. Mahbubul, R. Saidur, N.A. Rahim, Effect of different nanoparticle shapes on shell and tube heat exchanger using different baffle angles and operated with nanofluid, Int. J. Heat Mass Transf. 70 (2014) 289 297. Available from: https://doi.org/10.1016/j.ijheatmasstransfer.2013.11.018. [89] M.M. Elias, M. Miqdad, I.M. Mahbubul, R. Saidur, M. Kamalisarvestani, M.R. Sohel, et al., Effect of nanoparticle shape on the heat transfer and thermodynamic performance of a shell and tube heat exchanger, Int. Commun. Heat Mass Transf. 44 (2013) 93 99. Available from: https://doi.org/10.1016/j.icheatmasstransfer.2013.03.014. [90] S.S. Ghadikolaei, M. Yassari, H. Sadeghi, K. Hosseinzadeh, D.D. Ganji, Investigation on thermophysical properties of Tio2 Cu/H2O hybrid nanofluid transport dependent on shape factor in MHD stagnation point flow, Powder Technol. 322 (2017) 428 438. Available from: https://doi.org/10.1016/j.powtec.2017.09.006. [91] A.T. Olatundun, O.D. Makinde, Analysis of blasius flow of hybrid nanofluids over a convectively heated surface, Defect Diffus. Forum 377 (2017) 29 41. Available from: https://doi.org/10.4028/www.scientific.net/DDF.377.29. [92] M. Shafahi, V. Bianco, K. Vafai, O. Manca, Thermal performance of flat-shaped heat pipes using nanofluids, Int. J. Heat Mass Transf. 53 (2010) 1438 1445. Available from: https://doi.org/10.1016/j.ijheatmasstransfer.2009.12.007. [93] S. Ferrouillat, A. Bontemps, O. Poncelet, O. Soriano, J. Gruss, Influence of nanoparticle shape factor on convective heat transfer and energetic performance of waterbased SiO2 and ZnO nanofluids, Appl. Ther. Eng. 51 (2013) 839 851. Available from: https://doi.org/10.1016/j.applthermaleng.2012.10.020. [94] T.E. Amin, G. Roghayeh, R. Fatemeh, P. Fatollah, Evaluation of nanoparticle shape effect on a nanofluid based flat-plate solar collector efficiency, Energy Explor. Exploit. 33 (2015) 659 676. Available from: https://doi.org/10.1260/0144-5987.33.5.659. [95] S.M. Vanaki, H.A. Mohammed, A. Abdollahi, M.A. Wahid, Effect of nanoparticle shapes on the heat transfer enhancement in a wavy channel with different phase shifts, J. Mol. Liq. 196 (2014) 32 42. Available from: https://doi.org/10.1016/j. molliq.2014.03.001. [96] P.K. Das, A review based on the effect and mechanism of thermal conductivity of normal nanofluids and hybrid nanofluids, J. Mol. Liq. 240 (2017) 420 446. Available from: https://doi.org/10.1016/j.molliq.2017.05.071.

References

[97] S.H. Qing, W. Rashmi, M. Khalid, T.C.S.M. Gupta, M. Nabipoor, M.T. Hajibeigy, Thermal conductivity and electrical properties of hybrid SiO2-graphene naphthenic mineral oil nanofluid as potential transformer oil, Mater. Res. Express. 4 (2017). Available from: https://doi.org/10.1088/2053-1591/aa550e. [98] S. Suresh, K.P. Venkitaraj, P. Selvakumar, M. Chandrasekar, Synthesis of Al2O3 Cu/water hybrid nanofluids using two step method and its thermo physical properties, Colloids Surfaces A Physicochem. Eng. Asp. 388 (2011) 41 48. Available from: https://doi.org/10.1016/j.colsurfa.2011.08.005. [99] S. Suresh, K.P. Venkitaraj, P. Selvakumar, M. Chandrasekar, Effect of Al2O3 Cu/ water hybrid nanofluid in heat transfer, Exp. Therm. Fluid Sci. 38 (2012) 54 60. Available from: https://doi.org/10.1016/j.expthermflusci.2011.11.00. [100] X.F. Li, D.S. Zhu, X.J. Wang, N. Wang, J.W. Gao, H. Li, Thermal conductivity enhancement dependent pH and chemical surfactant for Cu-H2O nanofluids, Thermochim. Acta. 469 (2008) 98 103. Available from: https://doi.org/10.1016/j. tca.2008.01.008. [101] S. Askari, H. Koolivand, M. Pourkhalil, R. Lotfi, A. Rashidi, Investigation of Fe3O4/graphene nanohybrid heat transfer properties: experimental approach, Int. Commun. Heat Mass Transf. 87 (2017) 30 39. Available from: https://doi.org/ 10.1016/j.icheatmasstransfer.2017.06.012. [102] N.R. Karthikeyan, J. Philip, B. Raj, Effect of clustering on the thermal conductivity of nanofluids, Mater. Chem. Phys. 109 (2008) 50 55. Available from: https://doi. org/10.1016/j.matchemphys.2007.10.029. [103] K.S. Hong, T.-K. Hong, H.-S. Yang, Thermal conductivity of Fe nanofluids depending on the cluster size of nanoparticles, Appl. Phys. Lett. 88 (2006) 031901. Available from: https://doi.org/10.1063/1.2166199. [104] D. Huang, Z. Wu, B. Sunden, Effects of hybrid nanofluid mixture in plate heat exchangers, Exp. Therm. Fluid Sci. 72 (2016) 190 196. Available from: https://doi. org/10.1016/j.expthermflusci.2015.11.009.

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6

Furqan Jamil1 and Hafiz Muhammad Ali2 1

Mechanical Engineering Department, University of Engineering and Technology, Taxila, Pakistan 2 Mechanical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), Dharan, Saudi Arabia

Chapter Outline 6.1 Introduction .................................................................................................216 6.2 Main applications of hybrid nanofluids ..........................................................218 6.2.1 Solar energy .............................................................................218 6.2.2 Refrigeration and heating, ventilation, and air conditioning applications ..............................................................................223 6.2.3 Heat exchanger .........................................................................224 6.2.4 Heat pipes ................................................................................228 6.2.5 Coolant in machining and manufacturing ....................................229 6.2.6 Electronic cooling .....................................................................234 6.2.7 Automotive industry ..................................................................236 6.2.8 Generator cooling ......................................................................238 6.2.9 Transformer cooling ...................................................................238 6.2.10 Nuclear system cooling ..............................................................240 6.2.11 Biomedical ...............................................................................243 6.2.12 Space, Ships, and defense .........................................................245 6.3 Conclusions .................................................................................................245 Nomenclature ......................................................................................................246 Abbreviations ........................................................................................246 Symbols ...............................................................................................246 References ..........................................................................................................246

Hybrid Nanofluids for Convection Heat Transfer. DOI: https://doi.org/10.1016/B978-0-12-819280-1.00006-9 © 2020 Elsevier Inc. All rights reserved.

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6.1 Introduction The conventional fluids such as water and ethylene glycol have low thermal conductivity (TC) values. Adding nanosized particles enhance the thermal properties of conventional fluids. The new class of fluids, namely, nanofluids coined by Choi [1], is mostly undergone in several engineering applications due to its extraordinary thermophysical properties. The researchers in almost every field are trying to implement the usage of nanofluids in their respective applications. The hybrid nanofluids are advance type of nanofluids that are formed by combination of two different nanoparticles (NPs) in base fluid. The thermal properties of hybrid nanofluids will be better properties than base fluid and nanofluids [2]. Compared to conventional fluids, these fluids have superior properties as [3]

• • • •

high surface area and high HT between fluid and particles; high dispersion stability and Brownian motion of particles; remarkable increment in TC by varying particle concentration; and reduction in pumping power compared to conventional fluids power.

Turcu et al. [4] was possibly first who prepared hybrid nanofluids using polypyrrole-carbon nanotubes (CNTs) and multiwall carbon nanotubes (MWCNTs) on magnetic Fe3 O4 hybrid NPs. The better increment in thermal properties can be gained by combining hybrid silver NPs with MWCNTs [5]. Suresh et al. [6] found that TC enhancement of Al2 O3 -Cu was 12.11% having volume concentration 2%. The metal NPs were found to be higher TC due to small interatomic space resulted in more conduction [7]. More than 90% of both experimental and numerical studies found that nanofluids and hybrid nanofluids exhibit HT characteristics compared to water and ethylene glycol [8]. The experiments done by various researchers indicated that nanofluids have large HT ability compared to single base fluid which is due to high value of TC of nanofluids. The work of various researchers [9 12] has indicated remarkable increment in TC of working fluid. Kang et al. [13] concluded that silver NPs containing nanofluids have good value of TC. Hybrid nanofluid can be synthesized using single-step or two-step technique and TC is the main parameter for HT enhancement of hybrid nanofluids. The efficiency of hybrid nanofluid (HyNF) affects by several parameters such as synthesis of NPs, level of purity of NPs, and dispersion of NPs [14]. HT through fluid is due to convection which largely depends on convective HT coefficient. The expected results are hybrid nanofluids that can be performed better compared to nanofluids in same type of applications. Nanotechnology has been used in many applications that make more efficient in working. This results in decrement in cost of construction, maintenance, and repair. The objective of this chapter is to overview the hybrid nanofluids and state of the research work in use of hybrid nanofluids. The main areas of applications in which hybrid nanofluids can be used are discussed in this chapter. There are numerous applications in which hybrid nanofluids can be used and some of the highlighted areas are given in Fig. 6.1.

6.1 Introduction

FIGURE 6.1 Major areas of applications of hybrid nanofluids.

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6.2 Main applications of hybrid nanofluids 6.2.1 Solar energy The devices that are mostly used to convert solar energy into thermal energy are solar collectors as well as concentrators. The efficiency of these collectors remains major challenge after making in working conditions [15,16]. Different types of fluids such as water, oil, and ethylene glycol are used as circulating medium, but due to low performance, new class of fluids called nanofluids are introduced as working fluids [17 19]. Theses fluids showed better performance compared to conventional fluids. Hybrid nanofluids are new dawn for young researchers and scholars started to study hybrid nanofluid in solar energy due to its thermal characteristics [20]. Younis et al. [21] investigated the aluminum oxide-zinc oxide Al2O3-ZnO/ water nanofluids on photovoltaic thermal (PV/T) system efficiency. The computational as well as experimental study was conducted, and authors dispersed 0.5 wt. % of Al2O3 and ZnO using ethylene glycol as surfactant. The results indicated that energy and exergy efficiency were 4.1% and 4.6%, respectively. Verma et al. [22] performed experiments by using copper oxide (CuO)/MWCNTs and magnesium oxide (MgO)/MWCNTs nanofluids in flat plate solar collector. The energy and exergy efficiencies as well as comparison with unitary fluid were calculated. The results indicated that thermal efficiencies of hybrid nanofluids using the above combination were 18.05% and 20.52%, respectively. The results showed that by using MgO-MWCNTs/water and CuO-MWCNTs/water hybrid nanofluids, exergy efficiency up to 30.09% and 33.78% was observed, respectively, whereas CuO/water and MgO/water indicated lower increment in exergy efficiency. Chen et al. [23] studied CuO/antimony doped tin oxide (ATO) HyNF in solar energy areas. The HyNF selection must be in visible region as mentioned by authors. The absorption fraction in solar weight was found to be 9.8% and 10.1% having CuO and ATO nanofluids, respectively. Zeng et al. [24] studied the characteristics of MWCNTs-Ag/SiO2 hybrid nanofluids in solar energy sector. The authors selected this combination due to that MWCNTs have high radiations absorption. It was found that MWCNTs were efficient compared to Ag/SiO2. Farajzadeh et al. [25] carried out numerical as well as experimental approach by considering Al2O3, TiO2, and the combination along with base fluid. The results indicated that addition of NPs increased efficiency of setup by 21% and 19% in case of Al2O3 and TiO2, respectively. The optimal properties of CuOZnO/water HyNF were investigated by Fang and Xuan [26]. Three solutions having CuO/water and CuO-ZnO/water were synthesized, and volume fraction of NPs was 0.001% 0.01%. The results indicated that best performance was obtained by CuO-ZnO/water having 30% ZnO and efficiency was 97.35%. Gulzar et al. [27] investigated photothermal characteristics of different HyNFs. Therminol-55 oil was base fluid and NPs were Al2O3, TiO2, and their combination. The results concluded that hybrid nanofluids showed best performance in

6.2 Main applications of hybrid nanofluids

terms of efficiency and maximum observed temperature of Al2O3/Therminol-55 oil, TiO2/Therminol-55 oil, and Al2O3-TiO2/Therminol-55 oil was 152.9 C, 149.6 C, and 158.6 C, respectively, as well as 125.8 C for pure fluid. The concentration variation on temperature is represented in Fig. 6.2. The studies related to improvement in efficiency resulting in enhancement in Nusselt number are also found. Bellos and Tzivanidis [28] carried out experiments by using conventional and hybrid nanofluids in parabolic trough collectors. The nanofluids were TiO2/oil, Al2O3/oil having 3% concentration, and hybrid Al2O3-TiO2/oil having 1.5% concentration. The HT enhancement was observed in case of hybrid nanofluids and comparison of nanofluids and hybrid nanofluids is shown in Fig. 6.3. Mehrali et al. [29] used reduced graphene oxide nanosheets coated along gold NPs in solar absorber. These NPs were chosen due to its better absorbance and plasmonic effect and results showed that these hybrid nanofluids resulting in achieving 77% efficiency which revealed that graphene NPs have high light absorption capacity. The photothermal efficiency of nanofluids at different concentrations is illustrated in Fig. 6.4 in which S1 and S2 indicated nanofluids samples having 0.15 and 0.13 g of AgNO3.

FIGURE 6.2 Variation of particles concentration on temperature increment [27] (Permission taken from Springer Nature).

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CHAPTER 6 Applications of hybrid nanofluids in different fields

FIGURE 6.3 HT enhancement of nanofluids and hybrid nanofluids at different temperatures [28] (Permission taken from Elsevier).

FIGURE 6.4 Photoconversion efficiency of different nanofluids at various concentrations [29] (Open access).

6.2 Main applications of hybrid nanofluids

Xuan et al. [30] also studied plasmonic hybrid nanofluids, namely, TiO2-Ag/ water in solar energy absorption applications and variation of concentration on temperature was under consideration. The concentrations 0.002, 0.005, 0.01, and 0.015 were used and highest temperature was at 0.01 concentration. But increment in concentration revealed in solar absorption at less value of depth and results showed that optimum concentration of nanofluids was necessary for achieving high temperature. Karami [31] performed experiments to investigate exergy analysis on solar collector by using Fe3O4-SiO2/water nanofluids. The concentration variation and flow rate on efficiency were evaluated. Three concentrations of nanofluids 500, 1000, and 2000 ppm and flow rates of 0.0075, 0.0015, and 0.0225 kg/s were used. The results revealed that increment in concentration and flow rate increased the exergy efficiency of system as represented in Fig. 6.5. The results concluded that at 2000 ppm concentration of nanofluids, increment in exergy efficiency of more than 66% was observed and the various related studies are summarized below (Table 6.1).

FIGURE 6.5 Variation of volume fraction and flow rate on exergy efficiency [31] (Permission taken from Springer Nature).

221

Table 6.1 Various studies on HyNFs in solar energy. Authors

Solar system

Crisotomo et al. [32]

Nanofluids

Particle size

Concentration

Results

PV/T system

Ag-SiO2/water

—

—

Bhalla et al. [33]

Solar collector

Al2O3-Co3O4/water

d 5 13/10 30 mm

Hjerrild et al. [34]

PV/T system

Ag-SiO2-CNT/water

Ag-SiO2 nanodisc: 17.5 nm CNT:6 13 nm

Twelve various mass fractions used Ag-SiO2: 0.006 wt.% CNT:0.067 wt.%

Yu and Xuan [35]

—

CuO/CuO-Ag/water

D 5 600 nm

0.015 0.025 vol.%

Farajzadeh et al. [25]

Flat plate

Al2O3-TiO2/water

Al2O3:20 nm TiO2: 15 nm

0.1 wt.%

Zeng et al. [36]

Solar collector

Sn-SiO2-Ag/water

68 105 nm

0.01 0.5 vol.%

The 12% enhancement in energy output using nanofluid-based PV/T system when compared to single system Binary fluid was used, and blended NPs resulted in 80% absorption of solar radiations at depth of 20 mm Hybrid nanofluids indicated 51% optical efficiency. Electrical and thermal efficiency enhanced by 30% at 0.026 wt.% of Ag and SiO2 NPs. Heat absorption was enhanced by Ag NPs and showed 96.11% photothermal conversion efficiency at 35 C and at 60 C efficiency achieved 39.58%. The thermal efficiency increased by 19% and 21% using TiO2/water and Al2O3/water, respectively, while binary nanofluids showed 26% efficiency. The storage capacity of thermal energy enhanced 12% at 0.05 vol.% of binary fluid in comparison to base fluid.

Notes: CNTs, Carbon nanotubes; HyNF, hybrid nanofluid; NP, nanoparticle; PV/T, photovoltaic thermal.

6.2 Main applications of hybrid nanofluids

6.2.2 Refrigeration and heating, ventilation, and air conditioning applications Addition of NPs in refrigerant resulted in enhancement of HT and high value of HT coefficient of the refrigeration system [37]. The values of TC and viscosity are important factors in determining the performance of nanorefrigerant compared to conventional water fluid. The researchers used various nanorefrigerants instead of conventional fluids to measure the performance of the refrigeration system. It is concluded that 50% consumption of energy in buildings results in waste of heating, ventilation, and air conditioning (HVAC) system. Researchers are more focusing nowadays on energy consumption in HVAC system [38]. Some have done to modify the design of setup but mostly now investigating various fluids that includes addition of NPs. Jiang et al. [39] studied the effect of adding CNTs on refrigerant which was R113 and the influence of CNTs diameter on value of “k” was determined. The experimental results indicated that CNT-based nanorefrigerants have high value of “k” compared to CNTs-water refrigerants. It was also concluded that value of “k” decreased with increment in diameter of CNTs. Selvam et al. [40] investigated silver nanofluids in ethylene glycol and water mixture. The thermophysical properties such as viscosity, TC, and density were measured by thermal properties analyzer. The TC was increased by enhancing the concentration of NP and temperature. The enhancement in TC was observed between 0.15 and 12 vol.% around 50 C. But viscosity as well as density was decreased by increment with temperature. Akilu et al. [41] studied TiO2-CuO nanocomposite in ethylene glycol and viscosity as well as TC was measured by increasing the concentration of NPs and temperature. The results concluded that the above parameters largely depend on the concentration and temperature of NP. The increment of 16.7% and 80% was observed at 2 vol.% concentration in comparison to base fluid. Bi et al. [42] performed the experiments to measure boiling HT properties of R22 refrigerant along Al2O3 NPs. The results showed that NPs addition increased refrigerant HT along reduced bubble size that move quickly near HT surface. Wang et al. [43] studied TiO2 NPs to increase the stability of oil hydrofluorocarbon refrigerants. The results concluded that by using HFC134a refrigerant and mineral oil with TiO2 NPs, the performance of system was more by giving back lubricant to compressor. Loaiza et al. [44] investigated nanofluids as secondary coolant in vapor compression system. The various nanofluids containing different nano particles (Cu, Al2O3, CuO, and TiO2) having different concentration were utilized. The simulation results showed that refrigeration capacity and refrigerant side pressure drop dropped by increasing volume fraction and decreasing diameter of NPs. Eshgarf and Afrand [45] investigated rheological behavior of COOH with MWCNTs-SiO2/EG-water hybrid nanofluids in cooling system applications. The temperature range was 27.5 C 50 C and volume fraction of solid was 0.0625%

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CHAPTER 6 Applications of hybrid nanofluids in different fields

2%. It was observed that nanocoolant sampled revealed pseudoplastic rheological behavior and apparent viscosity was decreased with increasing volume fraction and decreased with increment in temperature. Soltanimehr and Afrand [46] also measured the value of “k” increment of COOH-functionalized MWCNTs/EGwater hybrid nanofluids by varying the concentration of nanotubes. The experiments were performed at temperature range of 25 C 50 C and volume fraction of 0% 1.0% for cooling applications. The experiments showed that increment in value of “k” was 34.7% at solid volume fraction of 1.0% and 50 C temperature. The results were also compared with Maxwell model and maximum deviation of 6 1.8% for proposed correlation. The vapor compression refrigeration performance in combination with chilled water air conditioning was investigated by Ahmad et al. [47]. The nanofluids TiO2/water and Al2O3/water were compared with Al2O3-TiO2/water hybrid nanofluids at different concentrations. The different parameters such as NPs concentration, size, type, nanofluid flow rate, and air velocity were under consideration. The experimental results revealed that Al2O3/water showed higher performance coefficient and lower value of compression ratio. The addition of NPs in refrigerants enhances the performance of HVAC system. Various techniques are used for this purpose such as ultrasonic agitation and magnetic force agitation [48]. The value of “h” and HT in vapor compression regeneration system depends on the value of “k” which can be increased by adding NPs. This results in decrement in compressor work as frictional pressure drop. Zawawi et al. [49] investigated various NPs as Al2O3-SiO2, Al2O3-TiO2, and SiO2-TiO2 in polyalkylene glycol. Results revealed that 20.5% increment of viscosity contained Al2O3-TiO2/PAG nanolubricant having 1% volume concentration. The value of “k” enhanced by 2.4% for Al2O3-SiO2/PAG having 0.1% nanolubricant. Sun et al. [50] measured HT of MWCNT-COOH/R141b and MWCNT-OH/ R141b. The concentration of nanorefrigerant was 0.059, 0.117, and 0.1765 vol.%. The results revealed that MWCNT-COOH/R141b exhibited better properties compared to MWCNT-OH/R141b. Ohunakin et al. [51] used Al2O3, SiO2, and TiO2 lubricants in refrigeration as working fluid and NPs were dispersed in mineral oil. The different parameters such as power consumption, viscosity, and “k” were under consideration. The results revealed that SiO2, TiO2 NPs reduced power consumption by 12% and 13%, respectively, compared to base LPG refrigerant and the various related studies are summarized below (Table 6.2).

6.2.3 Heat exchanger Heat exchanger function is to exchange heat from hot fluid to cold fluid and utilizing nanofluids in heat exchanger is a new dawn in recent years. Heat exchangers are widely used in many engineering applications such as automobiles, aerospace, and energy systems. The thermal performance of heat exchanger is vital for proper working of system, but pressure drop and pumping power

6.2 Main applications of hybrid nanofluids

Table 6.2 Various studies on hybrid nanofluids in HVAC applications. References

Nanorefrigerant

Experiment type

Results

Akilu et al. [41]

TiO2-CuO/ ethylene glycol

Performance evaluation of nanocomposites in ethylene glycol

Zawawi et al. [49]

Al2O3-SiO2,

Determine HT enhancement by using nanorefrigerant

Experimental results indicated that nanorefrigerants enhanced value of “k” and viscosity by 16.7% and 80%, respectively. The experimental results showed that increment in value of “k” was 2.4% and 20.5% for Al2O3-SiO2, Al2O3-TiO2, respectively.

Nabil et al. [52]

Al2O3-TiO2, SiO2-TiO2, PAG Al2O3-SiO2/PAG

Nabil et al. [53]

TiO2-water/ ethylene glycol

Balaji et al. [54]

Al2O3-water/ ethylene glycol

Examined the effect of using Al2O3-SiO2/ PAG in air conditioning Check performance of NPs in water ethylene glycol Experimental investigation on air conditioning compressor load

It was concluded that nanolubricant has high value of “k” and viscosity compared to pure PAG. The results revealed increment value of “k” by 15.4% and Nusselt number by 22.8% and 28.95% at 50 C and 70 C, respectively. The performance coefficient and “k” value of system enhanced by 49.32% and 12.24%, respectively.

Notes: HT, Heat transfer; HVAC, heating, ventilation, and air conditioning; NP, nanoparticle; PAG, polyalkylene glycol.

consumption limit its applications. The researchers and scientists have investigated that by increasing the TC of base fluids, the thermal performance of heat exchanger can significantly increase. So, incorporating various fluids such as nanofluids and hybrid nanofluids enhances the thermal performance of heat exchanger [55]. Madhesh and Kalaiselvam [56] investigated HT enhancement and rheological behavior of hybrid nanofluids through tabular heat exchanger. The effect of Nusselt number, Reynold number, value of “h,” and pressure drop was calculated at various concentrations ranging from 0.1% to 1.0% of copper titania hybrid nanocomposites (HyNC). The experimental results indicated that value of “h” increased by 59.3% at volume concentration of 0.7% of HyNC. The value of pressure drops and friction factor at volume concentration of 1.0% of HyNC showed 5.4% and 0.8%, respectively. Haung et al. [57,58] studied corrugated-pate heat exchanger using alumina and MWCNTs NPs to measure HT and pressure characteristics. The flow diagram is illustrated in Fig. 6.6. The mixture was synthesized by mixing 1.89 vol.%

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CHAPTER 6 Applications of hybrid nanofluids in different fields

FIGURE 6.6 Proposed experimental setup [57] (Permission taken from Elsevier).

alumina/water nanofluids and 0.0111 vol.% MWCNT/water nanofluids and ultrasonic vibration was done for almost three hours. The hybrid nanofluids exhibited best performance for highest pumping power. The HT and pressure drop properties of hybrid nanofluids containing alumina-MWCNTs/water in corrugated heat exchanger were measured. The experimental results indicated that value of “h” of hybrid nanofluids was slightly higher than unitary nanofluid. Allahyar et al. [58] conducted experiments by employing alumina-silver hybrid nanofluids for measuring performance and pressure drop in helical coil heat exchanger. The hybrid nanofluids were prepared by single step technique. The results concluded that by controlling Reynold number less than 5500 the maximum HT was obtained by 31.58% compared to base fluid at 0.4 vol.%. Megatif et al. [59] carried out study to measure the value of “h” by using TiO2CNTs hybrid nanofluids in laminar in shell and tube heat exchanger. It was concluded that low value of “k” was obtained of hybrid nanofluid compared to CNTs. But low preparation cost as well as higher stable, CNT-TiO2 HyNFs were suitable in HT applications. Madhesh et al. [60] studied particle concentration variation of Cu-TiO2 HyNFs in tube-type heat exchanger. Various parameters such as “h” and overall HT coefficient were under consideration and results concluded that 49%, 52%, and 68% increment was occurred, respectively. It was also observed that after 1% increment of particle concentration the value of Nusselt number and “h” started

6.2 Main applications of hybrid nanofluids

to decrease. Shahsavar et al. [61] investigated Fe3O4-CNT/water hybrid nanofluid in double pipe mini channel heat exchanger. The hybrid nanofluids were in tube side as a coolant while water was in annulus side. The thermal of non-Newtonian hybrid nanofluids was compared with Newtonian fluids. The non-Newtonian hybrid nanofluids exhibited higher HT and “h” compared to Newtonian fluids, whereas opposite behavior occurred in case of pumping power, pressure drop, and performance evaluation. Madhesh and Kalaiselvam [62] performed experiments to measure HT properties of Cu-Titania/water hybrid nanofluids. The different parameters such as overall HT coefficient were measured at various NPs volume concentrations. The results indicated that maximum overall HT coefficient was increased up to 30.4% up to 0.7% volume concentration of hybrid nanofluids. Bhattad et al. [63] studied Al2O3-MWCNT/water in plate heat exchanger and made comparison along base fluid. The influence of various operating parameters such as nanofluid inlet temperature, flow rate on coolant outlet temperature, “h,” pressure drop and pumping power was studied. The results concluded that 39.16% enhancement in “h” was found using hybrid nanofluids when compared to with base fluid with small increment of pumping power (1.23%). Suresh et al. [64] performed experiments by utilizing Al2O3-Cu/water nanofluids in circular copper pipe. The proposed experimental setup is illustrated in Fig. 6.7, in which heat was supplied with electrically heated wire. The results concluded the maximum increment of Nusselt number 13.56% at Reynold number 1730 using hybrid nanofluid when compared with base fluid water. The value of friction factor was also higher at 0.1% concentration Al2O3-Cu/water nanofluids compared to Al2O3/water nanofluids. Momin [65] measured HT rate in circular tube of copper using Al2O3-Cu/ water nanofluids having fully developed laminar flow. The results concluded the maximum increment of Nusselt number 13.56% at Reynold number 1730 having

T1 T3 T4 T5

Calming section

T6

T7

T8

T9

T2

Riser

Test section Air cooled heat exchanger

Flow control valve

Pump

Colleccting tank

FIGURE 6.7 Proposed experimental setup by Suresh et al. [64] (Permission taken from Elsevier).

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CHAPTER 6 Applications of hybrid nanofluids in different fields

particle volume fraction 0.1% in comparison with base fluid water. Hussein [66] carried our experiments in double tube heat exchanger by using aluminum nitride (AIN) NPs/ethylene glycol hybrid nanofluids. The author concluded that friction factor decreased as flow rate of hybrid nanofluids increased. Thermal performance and HT efficiency was also increased by 35% and 160%, respectively, in comparison of ethylene glycol alone.

6.2.4 Heat pipes Heat pipes are basically carriers of heat that transport heat from its one end having high temperature called evaporator to its low temperature side called condenser. The liquid is converted into vapors by absorbing heat at hot end and travels to cold end where it condenses and moves back by capillary action. The pressure difference is the reason of flowing working fluid from evaporator to condenser. The heat pipe mainly consists of three sections as evaporators, adiabatic sections, and condenser [67] as represented in Fig. 6.8. The researchers investigated various modifications in changing the structure of heat pipe and if there is no structural change then only working fluid is the main solution for increasing the efficiency. The choice of working fluid is very vital as it lead to decrement in thermal resistance of heat pipe. The nanofluid utilization in heat pipe has been used and the various type of hybrid nanofluids are also investigated by different authors. Han and Rhi [68] used hybrid nanofluids in specially designed grooved heat pipe to measure its thermal performance at various parameters. The parameters included HT rate, volume concentration, inclination, and cooling water temperature. The nanofluids used were Ag/water, Al2O3/water, and Ag-Al2O3/water hybrid nanofluids at different concentrations. The results concluded that by comparing water, nanofluids, and hybrid nanofluids, Ag-Al2O3/water showed higher

FIGURE 6.8 Basic working of heat pipe [67] (Permission taken from Elsevier).

6.2 Main applications of hybrid nanofluids

thermal performance with increasing concentration. Ramachandran et al. [69] determined the performance of cylindrical screen mesh heat pipe by using Al2O3CuO/water having various concentrations. The proposed experimental setup is illustrated in Fig. 6.9. The heat pipe was made of copper tube and wick structure was made by layers of copper screen mesh and heat input was varied between 50 and 250 W. The reduction in thermal resistance of 44.25% was observed at heat load of 250 W by using hybrid nanofluids. Swapnil et al. [70] studied working of heat pipe utilizing Al2O3-boron nitride/ water hybrid nanofluids. The different parameters such as particle concentration, HT rate, and inclination angle were varied. The experimental results indicated that thermal resistance decreased by enhancing inclination angle of pipe, particle concentration, and heat input rate. Kamble et al. [71] conducted tests on copper made heat pipe by using Al2O3-CuO/water hybrid nanofluids. The authors under considered parameters were volume concentration of particles, heat input, and inclination angle. Decrement in thermal resistance was 34.6%, 39.28%, and 32%, respectively, relative to particle concentration up to 2 vol.%, inclination angle 0 90 degree and heat input rate 25 100 W.

6.2.5 Coolant in machining and manufacturing The process of grinding produces high amount of energy per unit volume and most energy is converted into heat results in generating high amount of heat that can cause work piece damage. The work piece may undergo various residual stresses, cracks, and distortion [72]. The working feasibility of small size machine is not possible without proper circulation of working fluid as lubrication. The idea of using minimum quantity lubrication (MQL) used mostly researcher in their work [73,74]. Later, hybrid nanofluids are utilized due to lubrication and cooling problems as small lubrication lead to improper working of machine. Hybrid nanofluids have superior thermal properties due to that investigators used hybrid nanofluids as nanolubricants in manufacturing sector. Esfe et al. [75] investigated rheological behavior of MWCNTs-SiO2/oil hybrid nanolubricants having particle concentration 0 2 vol.% and temperature of 25 C 50 C. It was observed that hybrid nanofluids exhibited Newtonian behavior up to 1 vol.% and at 1.5 2 vol.%, HyNFs indicated non-Newtonian behavior. Esfe et al. [76] also investigated MWCNTs-alumina/oil hybrid nanolubricants to measure rheological properties of nanolubricants. The under considered hybrid nanofluids showed Newtonian behavior at 0 1 vol.% particle concentration and temperature of 5 C 50 C. As volume concentration enhanced beyond this limit, the hybrid nanofluids indicated non-Newtonian behavior. Esfe and Sarlak [77] examined the rheological properties of CuO-MWCNTs/ engine oil hybrid nanofluids. The experiments were performed at different concentration and temperature of hybrid nanofluids. The results indicated that nanolubricants showed non-Newtonian behavior as temperature increased above 45 C and 45.52% enhancement in viscosity was found at 55 C temperature having

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FIGURE 6.9 Proposed experimental setup [69]. T1, T2, T3, T4, and T5—T-type thermocouples located at the surface of heat pipe; T6 and T7—T-type thermocouples to measure the inlet and outlet cooling water temperature; 1—condenser section; 2—adiabatic section; 3— evaporator section; 4—heating coli; 5—rotameter; 6—chiller unit; 7—overhead tank; 8— data acquisition system; 9—autotransformer; and 10—computer (Permission taken from Elsevier).

6.2 Main applications of hybrid nanofluids

1 vol.% concentration. Nadooshan et al. [78] studied MWCNTs-SiO2/10W40 hybrid nanolubricants to determine rheological properties of hybrid nanofluids. The experiments were carried out by changing temperature, volume concentration, and shear rate. It was observed that under examined HyNFs indicated nonNewtonian behavior at all considered temperature range. Kumar et al. [79] investigated rheological properties and value of “k” of Cu-Zn hybrid nanofluids by utilizing three various base fluids. The study illustrated that vegetable oil-based hybrid nanofluids showed increment in value of “k” and showed better rheological properties. The change in viscosity was less showed with application of shear rate. Zhang et al. [80] used Al2O3/SiC hybrid nanofluids for (MQL) having workpiece of Ni-based alloy. The experiments were done, and the results were compared with Al2O3 and SiC nanofluids. The results indicated that hybrid nanofluid showed better results when compared with single fluid by decreasing grinding force ratio. Singh et al. [81] used alumina-graphene/water hybrid nanofluids in hard turning of AISI304 steel. The graphene NPs were blended at various concentrations in alumina-nanofluids and increment in concentration enhanced the value of “k” and viscosity. The results concluded that hybrid nanofluids performed better compared to alumina-nanofluids in cutting fluid. It was observed that using MQL technique, hybrid nanofluids reduced surface roughness by 20.28%, while cutting force, thrust force, and feed force by 9.94%, 17.38%, and 7.25%, respectively. Sharma et al. [82] studied alumina-molybdenum/water hybrid nanofluids in turning of AISI304 stainless steel. The hybrid nanofluids were prepared by combining alumina-based nanofluids in molybdenum disulfide NPs. The proposed experimental setup is indicated in Fig. 6.10 and pin disc test and contact angle

FIGURE 6.10 (A) Proposed experimental setup and (B) view of machining zone [82]. 1. HMT Lathe (NH22) machine. 2. Microprocessor-based speed controller. 3. Spray nozzle. 4. Kistler force dynamometer. 5. Kistler charge amplifier. 6. Force display unit. 7. MQL unit. 8. Air dryer. 9. Air compressor. 10. Carbide cutting insert (Permission taken from Elsevier).

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measurement were measured of nanofluids for checking tribology and wettability. Along rough surface methodology method was used for carrying out experiments. The results indicated that cutting force, feed force, thrust force, and surface roughness were reduced by 7.35%, 18.08%, 5.73%, and 2.38%, respectively, by using hybrid nanofluids when compared with alumina-nanofluids. The effect of hybrid nanofluids on coated carbide cutting tool performance of aluminum alloy AA6061-T6 was investigated by Sahid et al. [83]. The different parameters such as depth of cut, cutting speed, and feed rate were under consideration. The analysis showed that by using TiO2-ZnO/ethylene glycol hybrid nanofluids reduced machining cost and better machineability under MQL method. The effect of surface roughness against hybrid nanofluids reflected minimum as indicated in Fig. 6.11. Sharma et al. [84] studied tribological properties of alumina/graphene hybrid nanofluids during turning operation of steel and compared with alumina nanofluids. The results concluded that by varying particle concentration, the friction

FIGURE 6.11 Surface roughness rate of dry, MQL, and hybrid nanofluids [83]. MQL, Minimum quantity lubrication (Open access).

6.2 Main applications of hybrid nanofluids

factor and wear were reduced. The nodal temperature and flank wear were reduced to 5.79% and 12.29%, respectively, when compared with unitary fluid. The authors also examined variation of alumina-graphene/water HyNFs fluids on tribological properties of lubricant in turning of AISI304 stainless steel. It was observed that hybrid nanofluids showed lowest friction coefficient. Sharma et al. [85] also studied alumina/MWCNTs hybrid NPs in cutting fluids at fixed volume proportion. The performance of cutting fluid was under considered using MQL in turning of AISI304 stainless steel. It was observed that tool flank wear and nodal temperature reduced by 11% and 27.36%, respectively, compared to alumina-based lubricants. Eltaggaz et al. [86] investigated alumina/gamma hybrid NPs using MQL during machining of austempered ductile iron. The effect of hybrid nanofluids on behavior of tool wear was examined. The best tool life obtained when combining of MQL nanofluids at cutting speed of 120 m/min and feed rate of 0.2 mm/rev. The utilization of hybrid nanofluids using MQL method in ultrasonic assisted grinding was considered by Rabiei et al. [87]. The authors studied MWCNTs, Al2O3, and hybrid nanofluids MWCNTs/Al2O3 in oil mist. The different parameters such as grinding forces, maximum temperature, and friction coefficient were under examination. The maximum grinding temperature reduced from 254 C to 111 C and tangential, normal, and friction coefficient decreased by 61.5%, 47.1%, and 27.3%, respectively. Jamil et al. [88] investigated alumina-MWCNTs/oil hybrid nanofluids using MQL technique in turning of Ti-6Al-4V. The Taguchi-based L9 orthogonol array was used for the design of experiments and considered parameters were cutting speed, feed rate, and cooling technique. The results indicated that surface roughness and cutting force deceased by 8.72% and 11.8% while tool life increased by 23% in comparison to cryogenic cooling. Sharma et al. [89] developed molybdenum-desulfide/alumina NPs in oil water base fluid for improvement in tribological properties of AISI304 steel. The tribological testing and contact angle measurement testing were performed for prepared lubricants. The hybrid nanofluids showed better performance compared to oil water nanofluids. Also tool flank wear was greatly reduced by using hybrid nanofluids compared to monotype nanolubricant. Gajrani et al. [90] used molybdenum-desulfide/calcium fluoride hybrids NPs in vegetable oil for machining experiments. The schematic diagram is represented in Fig. 6.12. The experiments were performed at various concentrations of hybrid nanofluids and tool wear, surface adhesion, and surface roughness parameters were considered. The results showed that at 0.3% concentration of hybrid nanofluids, system performed better in terms of performance. The reduction in tool cutting, feed force, and friction coefficient was 17%, 28%, and 11%, and improved in surface finish was 37%. Zhang et al. [91] performed performance comparison of molybdenumdesulfide, CNTs and molybdenum-desulfide hybrid nanofluids in grinding of Ni based alloy. The result showed that hybrid nanofluids indicated good grinding

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FIGURE 6.12 Schematic diagram for proposed setup [90] (Permission taken from Elsevier).

compared to single nanofluids. Zhang et al. [92] used MQL method utilizing Al2O3-SiC/oil for determining lubricating properties of hard Ni-based alloy. The hybrid nanofluids were synthesized at 2 vol.% of NPs and oil. The effect of size of NPs on grinding performance parameters was determined. The maximum removal rate of workpiece was seen to be 189.05 mm3/sN at Al2O3-SiC mixed size ratio of 70:30. Also the best morphology was obtained by using this method. Taghizadeh and Zarepour [93] investigated MWCNTs/Al2O3 hybrid NPs in grinding process of Inconel 600. The effect of NPs size, volume concentration, and mixing ratio on surface quality was determined. The highest surface quality was obtained having mixing ratio of 25% 75% of MWCNTs/Al2O3, volume concentration of 0.6%, and size 20 and 15 nm, respectively and the various related studies are summarized below (Table 6.3).

6.2.6 Electronic cooling The rapid increment in modern technology numerous enhancement of heat generation in electronics has been occurred which decreases the performance of device and its life. Generated heat from single chip is enhanced from 330 W=cm2 in 2007 and to 520 W=cm2 in 2011 which is indicated by international technology road map for semiconductors [94]. Therefore the designing of efficient electronic components is necessary for proper working and various attempts have been made in this field. According to Agostini et al. [95] it is great issue to dissipate

6.2 Main applications of hybrid nanofluids

Table 6.3 Studies related to hybrid nanofluids in machining process. Authors

Hybrid NPs

Base fluid

Results

[81]

Aluminagraphene

Water

[82]

Aluminamolybdenum disulfide

Water

[83]

TiO2-ZnO

Ethylene glycol

[84]

Aluminagraphene

Water

[85]

Alumina/ MWCNTs

Water

[86]

Alumina/gamma

Water

[90]

Molybdenumdesulfide/calcium fluoride Molybdenumdesulfide/CNTs

Vegetable oil

Hybrid nanofluids reduced surface roughness by 20.28% while cutting force, thrust force, and feed force by 9.94%, 17.38%, and 7.25%, respectively. The results indicated that cutting force, feed force, thrust force, and surface roughness were reduced by 7.35%, 18.08%, 5.73%, and 2.38%, respectively, by using hybrid nanofluids when compared with alumina-nanofluids. The analysis showed that by using TiO2ZnO/ethylene glycol hybrid nanofluids reduced machining cost and better machineability under MQL method. It was observed that hybrid nanofluids showed low friction coefficient. The results also concluded that tool flank wear and nodal temperature decreased by 12.29% and 5.79%, respectively, by using hybrid nanofluids when compared to alumina nanofluids. It was observed that tool flank wear and nodal temperature reduced by 11% and 27.36%, respectively, compared to alumina-based lubricants. The best tool life obtained when combination of MQL-nanofluids at cutting speed of 120 m/min and feed rate of 0.2 mm/rev. The reduction in tool cutting, feed force, friction coefficient was 17%, 28%, 11%, and improved in surface finish was 37%. It was observed that hybrid nanofluids indicated better results of grinding compared to single nanofluids.

[91]

Water

Notes: CNTs, Carbon nanotubes; MQLs, minimum quantity lubrications; MWCNTs, multiwall carbon nanotubes; NP, nanoparticle.

heat of 300 W=cm2 at 85 C. Different techniques are utilized for cooling of components that PCM heat sink and fins but these techniques are insufficient for meeting the demand of thermal management of these components [96,97]. The output parameters like maximum power output were consideration by using various nano fluids to minimize heat dissipation of heat sinks. Selvakumar and Suresh [98] investigated Al2O3-Cu hybrid NPs for cooling of thin channel electronic heat sink. The hybrid nanofluids effect in enhancement

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the value of “h” was under considered. The results concluded that by using nanofluids the value of “h” was significantly increased when compared to water. The rise in pumping power was less in case of using hybrid nanofluids in comparison with water as working fluid. Nimmagadda and Venkatasasubbaiah [99] studied HT characteristics of micro channel by using Al2O3, Ag, and hybrid Al2O3 1 Ag nanofluids. The effect of Reynold number, pure, and hybrid NPs particle concentration on HT characteristics was considered. The results indicated that average value of “h” was enhanced by increment in volume concentration of NPs. The results concluded that 3 vol.% of hybrid nanofluids showed higher value of “h” compared to pure water and pure NPs. Bahiraei et al. [100] conducted the study of graphene-sliver hybrid NPs in microchannel heat sink having ribs and secondary channel. The ribs made flow toward secondary channel while secondary channel made increased flow area resulting in reducing pressure drop. The performance of heat sink was significantly improved by using above combination along hybrid nanofluids. The value of “h” was enhanced to 17% by increasing concentration from 0% to 0.1% at Reynold number of 100. Kumar and Sarkar [101] performed numerical simulation to measure HT and pressure drop characteristics of mini channel heat sink by using Al2O3/water and hybrid Al2O3-MWCNTs/water nanofluids. The various vital parameters were hydraulic diameter, channel aspect ratio, and Reynold number and were under consideration. The maximum value of “h” was achieved at 0.01 vol.% concentration of hybrid nanofluids at mini channel depth of 0.5 mm and 15.6% increment of “h” was observed. Nazari et al. [102] used nanofluids of alumina, CNTs, and base fluid of water and ethylene glycol for cooling of central processing unit (CPU). The decrement in temperature of CPU was 22% having CNTs/water nanofluids. The value of “h” was increased up to 6% by adding 0.5 vol.% of alumina and 13% by adding 0.25 vol.% of CNTs. Thus hybrid nanofluids can provide better results for electronic cooling. Khoshvaght-Aliabadi and Nozan [103] studied corrugated-shaped mini channel for increment in Nusselt number by using water and conclude that high value was obtained using trapezoidal shape. The increment in Nusselt number was obtained 13% 14% when using water, hybrid nanofluids can produce better results in terms of thermal characteristics. Ahammed et al. [104] performed entropy generation analysis of hybrid nanofluids for cooling of electronic components. The alumina, graphene, and their hybrid combination were prepared and tested. The increment in value of “h” was 88.62% for graphene/water nanofluids, while 31.89% and 63.13% were observed using alumina/water and hybrid nanofluids, respectively.

6.2.7 Automotive industry The thermal management of engine in automobile is necessary as it directly affects its performance in terms of economy, material selection, and emission

6.2 Main applications of hybrid nanofluids

maintenance [105]. The thermal management of vehicle engine is a technology that reduces energy utilization which results in improving thermal efficiency and minimizing losses. The mixture of ethylene glycol and water has proved to be promising nanofluid for automotive cooling compared to single water. The addition of NPs to the engine oil improves the performance of automotive and cooling of engine. These improvements help in reducing heat losses and decrease the size of radiator in terms of size and weight. Ali et al. [106] studied frictional power losses and wear rate in sliding contact of piston ring and cylinder by using alumina-TiO2/oil hybrid nanofluids. The reduction in frictional losses was 40% 51% and 17% decreased in wear rate compared to base fluid (oil). The effect of addition of surfactant on output parameters was also observed. The oleic acid was added as surfactant and effect of agglomeration and it was observed that friction coefficient decreased by 18%. Sidik et al. [107] reviewed study on engine oil cooling system by summing all studies of single type of nanofluid. The authors study indicated that adding small number of NPs ( , 1% volume fraction) can enhance the HT rate up to 50% compared to mono nanofluids. Tijani and Sudirman [108] studied the HT behavior of water/antifreezing-based nanofluids which was used as coolant in radiator. The water and ethylene glycol having 50% concentration was used as mixture. Al2O3 and CuO NPs having various concentrations were added in base fluid. The HT characteristics was determined by using simulations based on value of “h,” “k,” and Nusselt number. It was observed that the rate of HT was enhanced by adding NPs and maximum rate of HT was observed at 0.3% concentration of NPs as illustrated in Fig. 6.13.

FIGURE 6.13 NPs concentration of various fluids versus increment in TC [108] (Permission taken from Elsevier).

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Karimi and Afrand [109] investigated the efficiency of vertical and horizontal tube radiators. The hybrid nanofluid which was under consideration was MgOMWCNTs/ethylene glycol. The results indicated that vertical tube radiator exhibited better performance and 10% high efficiency compared to horizontal tube. Also pressure drop in circular tube radiator was 25% less than elliptical shape tubes. Afrand et al. [110] performed experiments using SiO2-MWCNTs/engine oil hybrid nanofluids by changing temperature and volume fraction of particles. The hybrid nanofluids exhibited Newtonian behavior for most experiments consideration of temperature and particle volume fraction. The maximum increment was 37.4% at 1 vol.% and 60 C.

6.2.8 Generator cooling The new technologies in cooling of various devices directly play influence in the performance of system. The HT directly influences the performance of engine, selection of material, fuel efficiency, and emission. The control of heat during combustion helps in improvement in the life of engine, cooling of oil, and ultimately climate control. The conventional fluids have not better performance and advance fluids must be necessary in circulation for minimizing heat loss in coils. The researchers investigated various NPs in base fluids for enhancing the performance of system. Kulkarni et al. [111] studied aluminum oxide NPs in cooling of diesel electric generator (DEG). The nanofluids were used at different concentrations and measured the effect of cogeneration efficiency of DEG. It was found that nanofluids decreased the cogeneration efficiency. This was occurred as decrement in specific heat which affected recovery of waste heat from engine. The efficiency of heat exchanger having waste heat recovery was enhanced by using nanofluids which have high value of “h.” The efficiency increased from 78.1% to 81.11% by using Al2O3 NPs in ethylene glycol water which were used in heat exchanger. The cogeneration efficiency of various nanofluids is represented in Fig. 6.14. Amiri et al. [112] prepared ethylene glycol-based graphene NPs for cooling of engine and improvement in performance. The properties of synthesized nanofluids were determined and the value of “k,” viscosity, specific heat capacity, and density was determined experimentally to measure thermal efficiency. It was observed that pressure drop increment was not significant at different temperatures and volume fractions. The technique of utilizing hybrid nanofluids in generator cooling has not been done much and researchers must consider this for their future work.

6.2.9 Transformer cooling By utilizing better working fluid, transformer life enhances, and maintenance cost reduces. The nanofluids can be used in cooling of transformer and nanodiamond can be used to oil used in transformer and other equipment for increment of “k”

6.2 Main applications of hybrid nanofluids

FIGURE 6.14 Variation of heat exchanger efficiency by changing concentration of nanofluids [111] (Permission taken from Elsevier).

and dielectric properties [113]. Nanosized particles also having low cost and radially available can be utilized in mineral oil used in transformer and oil base electrical components which results in increment of dielectric properties. The failure life, oil life, and load boundaries are extend by using such combination which ultimately enhances the performance as well as life of transformer [114]. Choi et al. [115] used Al2O3/AIN transformer oil-based nanofluids to increase the thermal characteristics of oil. The results concluded 8% and 20% increment in the value of “k” and overall HT coefficient having 0.5% volume concentration of AIN particles as illustrated in Fig. 6.15. As dispersion of particles increased the value of “k” and thermal characteristics were greatly affected. The authors also used ceramic NPs for making high-efficiency transformer oil due to their electrical insulation property. By natural convection test, the cooling effect of Al2O3/ AIN-oil nanofluids on heating elements and oil was confirmed. The oil that used in operation of transformer has excessive maintenance, failure chances, and replacement cost including overheating. The transformer oil is poor thermal conductor and cracking of molecules occurs due to heat generation. The inclusion of NPs in such oil results in enhancing TC of oil and various authors studied on this. They performed tests by adding NPs in transformer oil

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FIGURE 6.15 (A) TC increment with variation of volume fraction. (b) Variation of overall heat transfer coefficient against Reynolds number [115]. TC, Thermal conductivity (Permission taken from Elsevier).

and concluded that adding small fraction of NPs less than 1% increased the TC much high [116]. This results in achieving high performance of transformer in terms of cooling effect.

6.2.10 Nuclear system cooling The utilization of nanofluids in water cooled nuclear reactors can result in vital improvement in the performance of system in terms of economics cost and safety margin. The flux of heat in fuel rod plays vital role in determining the performance of nuclear reactor due to maximum heat flux. In cylindrical solid fuel the heat generated flows into coolant through on rod surface while annular fuel has two surfaces [117] as represented in Fig. 6.16. The earlier MIT studies showed that internally and externally cooled annular fuel increased power density greatly and safety margin in standard Westinghouse pressurized water reactor [118,119]. Boungiorno and Hu [120] measured the critical heat flux of nanofluids and enhanced the heat transfer in nuclear reactor. The results were interested because of application of nanofluids as the value of critical heat flux was increased. The results indicated that less failure of nuclear reactor occurred and increment of decay power removal in vessel was 40% more in vessel by using nanofluids. The stability of alumina base nanofluids was experimentally investigated in in-vessel retention environment. The results concluded that nanofluids were stable against dilution and when exposed to gamma radiations [120]. Mousavizadeh et al. [121] investigated TiO2/water nanofluids for determining HT characteristics of VVER-1000 nuclear reactor. The simulation was done using computational fluid dynamics and different parameters such as value of “k,” “h,” and fuel cell temperature was determined along comparison was done without

6.2 Main applications of hybrid nanofluids

FIGURE 6.16 Diagram of solid and annular fuel [117] (Permission taken from Elsevier).

using NPs. The results concluded that the value of “k” and “h” was enhanced by using nanofluids. Ghazanfari et al. [122] performed thermal analysis of nanofluid which was used in VVER-1000 nuclear reactor. The under considered nanofluid was Al2O3/ water and used at various concentrations. The fuel rod was simulated using computational fluid dynamics code and results were compared with unitary water. It was observed that as the particle concentration increased, the coolant temperature increased, and the temperature of fuel decreased. Hatami et al. [123] carried out experiments to optimize arrangement of fuel rod cooled by nanofluids in pressurized water reactor. The fuel rods geometry is shown in Fig. 6.17. The Al2 O3 water, TiO2 water nanofluids were used and simulation was done by ANSYS fluent software to measure the effect of varying concentration on HT efficiency. The results indicated that Al2 O3 and TiO2 NPs enhanced the Nusselt number by 17% and 10%, respectively. The distance parameter was minimum level and diameter parameter was maximum level for better cooling of rods. Nourollahi et al. [124] conducted tests to investigate variations in coolant temperature and velocity in fuel assembly of VVER-1000 reactor. The aluminum oxide/water nanofluids were used to measure the effects by using Fouriertransformed conservation equations. The thermal hydraulic analysis of nanofluids on noise was also under considered. The results indicated that with increment in mass fraction, the reduction of fluctuation of temperature and velocity was observed. Hadad and Kowsar [125] used nanofluids as coolant in pressurized water reactor of VVER-1000 for increment in HT. The nanofluids were also used as neutron moderator and neutron absorber. The PWR was modeled with coupled neutronics and fluid dynamics codes. The five nanofluids were used and results illustrated

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FIGURE 6.17 Control volume of fuel rods considered by authors [123] (Permission taken from Elsevier).

FIGURE 6.18 The variation of coolant temperature against various nanofluids in the channel [125] (Permission taken from Elsevier).

that 2 vol.% of silver oxide exhibited better results for neutronics and thermohydraulic safety in pressurized water reactor. The variation in coolant temperature using silver oxide nanofluids is illustrated in Fig. 6.18. The effect of NPs in base fluid for cooling of nuclear reactor has great influence on its performance. The various NPs have different effect and changing

6.2 Main applications of hybrid nanofluids

concentration varies the TC of nanofluid. The fuel cell temperature decreased with increase in the concentration of NPs. The thermophysical properties of added NPs in base fluid showed better results [126]. The researchers should consider various hybrid nanofluids for improvement in temperature reduction and should be considered for future work.

6.2.11 Biomedical The nanotechnology applications at cellular and molecular level have brought great improvement in the field of health care and life sciences [127]. It became the most imperative study in recent years. Nanofluids and NPs are widely used in biomedical sector. NPs have adhesion to tumor cells compared to normal cells and combined effect of radiations as well as hyperthermia is due to heat produced after repair process as radiations induced DNA damage [128,129]. Wang and Leon [130] studied NPs are fastened with the aid of releasing anticancer medicine at fixed rate. Most of the studies done in 1990 on bio microelectronic mechanical system such as electronically activated drug delivery microchip and nanomedicine applications of nanogels and gold-coated NPs [131]. The main purpose of developing nanotechnology in biomedical is to monitor and control of biological cell activities efficiently. The conventional delivery of drugs is represented by high and low phenomena. The nanodelivery drugs system controlled releasing of drug for a specific duration of time [130]. The bio microelectronic mechanical system was first applied by Kleinstreuer et al. [132], in which uniform delivery of nanodrugs was done. The heat flux was applied on nanofluids and fluid velocity was added at temperature of 37 C. The results indicated that nanodrug had positive impact on uniform drug concentration. The nanofluids also have emerging field in cancer image and drug delivery due to extraordinary properties of nanofluids. The use of iron-based NPs and magnetic nanofluids has been used for guidance of tumors along magnets. This results in the diagnosis of affected parts without damaging healthy tissues and improvement in cancer treatment. Magnetic NPs are widely used due to its controlment by magnetic force compared to other metal type NPs [133]. The nanofluids having magnetic NPs act as superparamagnetic nanofluids [134]. The coating of NPs and biocompatible water-based magnetic are vital techniques in biomedical sector. For most of the applications, the NPs size should be less than 15 nm and widely dispersed in water [135,136]. The conventional cryopreservation protocols which were used for freezing having cell injury due to ice formation or toxicity of high cryoprotectant concentration. He et al. [137] proposed cryopreservaion method for obtaining fast cooling rates by using quartz microcapillary. The experimental setup is illustrated in Fig. 6.19. It was observed that for low concentration of nanofluids, the process was more effective for cryopreservation of murine embryonic stem cells.

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FIGURE 6.19 The proposed experimental setup [137] (Permission taken from Elsevier).

The cryosurgery technique is used to destroy unwanted tissues by method of freezing and this technique is popular for clinic applications. The cryosurgery is replacement of conventional cancer treatment. Yan and Liu [138] carried out simulations on phase change bio-HT at cell level to measure the temperature between conventional cryosurgery and nanocryosurgery. The addition of NPs has reduced the final temperature and enhanced the freezing rate. The introduction of NPs using nanofluids increases the nucleation rate. The colloidal gold has been used for the diagnosis of syphilis, supramolecular, and biosciences. The gold NPs have been extensively used for biomedical applications and are biocompatible. This is due to extraordinary stability of gold NPs and diversity in terms of preparation [139]. Ijaz and Nadeem [140] investigated Ag-alumina/blood hybrid unit to measure its impact on hydrodynamics of overlapped stenotic artery. The convective and constant slip phenomena were considered using solid NPs for experimental analysis. The comparison between Ag and hybrid NPs was done and it was concluded that hybrid blood was more efficient to minimize shear stress on wall and resistance to blood flow in stenotic artery. The aqueous suspension of hybrid graphene oxide-iron oxide (GO-Fe3 O4 ) was tested in cellular imaging by Narayanan et al. [141]. The agarose phantoms were made, and values were measured on 7 T MR scanner. This hybrid combination indicated good cell viability and enhancement in TC was found using

6.3 Conclusions

hybrid combination. The hybrid NPs were able to penetrate cell cytoplasm which resulted in giving platform for cellular applications. The cobalt oxide (Co3 O4 ) and its composites have been utilized in medical applications by Sundar et al. [142]. The cobalt compounds are nontoxic and due to its magnetic properties, it is widely used in medical applications. The tumor-affected areas can be trace by magnetic particles and cobalt composites have shown best behavior toward cancer-affected applications. Ijaz et al. [143] developed mathematical model to investigate hydrodynamics of overlapped stenotic artery. The variation of concentration of Cu-CuO/blood hybrid nanofluid was investigated. The results illustrated that hybrid combination showed resistance to flow and stress on wall of stenotic artery and combination was most suitable for hydrodynamic impact.

6.2.12 Space, Ships, and defense The increment in weight of space station and air craft has made restriction in practical applications which results in demanding cooling system with high efficiency including small size. Many military equipments require high heat flux cooling for reliable operation. For high cooling conventional fluids are facing challenge for operation. The researchers are focusing on light-weight equipments in which various NPs are used for working efficiently. The different hybrid NPs are promising fluids for better performance of aerodynamic applications. You et al. [144] and Vassallo et al. [145] concluded that critical heat flux in pool boiling increased by adding nanofluids compared to base fluid. There is need of further research for achieving efficient cooling of devices for cooling requirement of space applications. The nanofluids can provide high cooling of components for military systems, military vehicles and sub marines applications. Thus nanofluids have broad range of applications in space and defense field [146]. Wang and Mujumdar [147] concluded that the value of critical heat flux increased in pool boiling with nanofluids compared to base fluid. Thus such level can raise the chip power in electronic components and cooling for space applications. The large value of critical heat flux results in high heat removal and utilization of nanofluids make cooling of components in space applications. The defense sector in United States is creating unique kinds of weapons and advance system in which high heat is utilized. This heat having high amount can be transported by nanofluids to the desire location. Therefore thermal management of these devices must be done by circulating nanofluids or hybrid nanofluids to accomplish high critical flux. The result will reduce the drag and fuel cost of the ship [129].

6.3 Conclusions The applications of hybrid nanofluids have been extensively discussed as conclusion. On the other hand, in this chapter, the thermal characteristics of HyNF were higher compared to single base fluid and nanofluids. The concluded remarks are

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that performance of HyNF enhances as increment of temperature and NPs volume fraction but up to certain limits. Hybrid nanofluids indicated better results in terms of HT in many applications and further research must be done on hybrid nanofluids to broad its area of applications. The production cost of hybrid nanofluids is also high which researchers must be considered for future work.

Nomenclature Abbreviations Ag EG HT HVAC HyNF MWCNTs MQL NPs PAG s TC

silver ethylene glycol heat transfer heating, ventilation, and air conditioning hybrid nanofluids multiwall carbon nanotubes minimum quantity lubrication nanoparticles polyalkylene glycol second thermal conductivity

Symbols h k

convective heat transfer thermal conductivity

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CHAPTER

Barriers and challenges in hybrid nanofluids development and implementation

7 Alina Adriana Minea

1

Technical University Gheorghe Asachi, Ia¸si, Romania

Chapter Outline 7.1 Stability of hybrid nanofluids .........................................................................256 7.1.1 Stability enhancement procedures ................................................258 7.2 Viscosity and thermal conductivity modeling techniques for hybrid nanofluids .260 7.2.1 Viscosity modeling techniques for hybrid nanofluids .......................260 7.2.2 Thermal conductivity modeling techniques for hybrid nanofluids .....261 7.3 Nanoparticles dispersion in hybrid nanofluids ................................................261 7.3.1 Pairs of nanoparticles ..................................................................263 7.3.2 Hybrid nanocomposites ................................................................263 7.3.3 Other approaches ........................................................................264 7.4 Pumping power studies and approach on hybrid nanofluids .............................265 7.4.1 Pumping power comparison for water based hybrid nanofluids: theoretical approach ....................................................................266 7.5 Selection of proper hybrid nanofluids ............................................................271 7.5.1 Selection of suitable pairs of nanomaterials or hybrid materials .......272 7.5.2 Selection of base fluids ...............................................................272 7.6 pH control of hybrid nanofluids .....................................................................272 7.7 Conclusion and perspectives .........................................................................274 Nomenclature ......................................................................................................274 Abbreviations ........................................................................................274 Roman letters .......................................................................................274 Greek letters .........................................................................................275 Subscripts ............................................................................................275 References ..........................................................................................................275

Hybrid Nanofluids for Convection Heat Transfer. DOI: https://doi.org/10.1016/B978-0-12-819280-1.00007-0 © 2020 Elsevier Inc. All rights reserved.

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7.1 Stability of hybrid nanofluids The research on nanofluids and later on, hybrid nanofluids as well as ionanofluids, is on the top of preoccupation of a lot of research groups. Nanofluids were engineered as nanoparticles suspended in a more or less common base fluid (i.e., water, ethylene-glycol, oils, and ionic liquids). Following the preparation of nanofluids, some research groups thought that adding two nanoparticles or composite ones can overcome some barriers encountered in the simple nanofluids thermophysical properties [1
8]. Actually, hybrid nanofluids are based on the synergy of a multicomponent medium for heat transfer, as can be noticed from Fig. 7.1. Three classes of hybrid materials are initiated based on a metal matrix: (1) Metal matrix nanocomposite; (2) Nanocomposites with ceramic matrix; and (3) Nanocomposites with polymer matrix. Stability is one of the crucial factors that is accountable for the overall benefits as well as for the heat transfer augmentation of the hybrid nanofluids since the presence of nanoparticles determine strong van der Waals forces thus creating aggregates. Derjaguin, Landau, Verway, and Overbeek (DLVO) established in 1940 some theoretical guidelines dealing with stability of the suspensions with nanoparticles and microparticles [9]. The DLVO theory proposes to evaluate the stability of a

FIGURE 7.1 Hybrid nanofluids types.

7.1 Stability of hybrid nanofluids

particle in a certain liquid using the summation of van der Waals attractive and electrical double layer repulsive forces which occur among different nanoparticles because of the particles Brownian movement. Basically, the DLVO theory considers the combined influence between van der Waals forces and double layer. The stability of hybrid nanofluids is of great importance especially to further sedimentation and clustering of the nanoparticles and was evaluated by different researchers with the help of techniques like [8
28]:

• • • • •

visual analysis, pH studies, TEM or SEM tests, Zeta potential analysis, and spectral tests.

Visual analysis is one of the most encountered technique when it comes to sedimentation, even if the results are not outstanding. On the other hand, hybrid nanofluids stability is directly connected with their electro kinetic properties, and consequently the measuring of the suspensions pH it is a good tool to evaluate the stability of a nanoparticle enhanced fluid, due to strong repulsive forces that occur. The nanofluid pH assessment can be enlarged or diminished through the addition of a suitable nonreactive alkaline or acidic solution, correspondingly [8
10]. Several research was pursued to establish the consequence of pH values on a certain nanofluid stability [8,11
14], but less on hybrid nanofluids. For example, Wen et al. [8] noticed that nanofluids based on CNT gives good stability when added to water in comparison with other base fluids. Particles size distribution is a good tool to evaluate the nanofluid stability by using TEM or SEM microscopy procedures. These two techniques allow us to estimate the formation of agglomerates and to visualize the nanoparticles dimensions. If clusters are present in the TEM/SEM imaginings it can clearly affirm that sedimentation is expected to happen, thus going to a further sedimentation and lack of stability. The TEM samples preparation technique is fully described by Kong et al. [15] as: it first considers a carbon coated copper grid where a drop of the nanofluid is placed. Then, the monitoring of the nanoparticles distribution is accomplished after the base fluid is evaporated under vacuum [15]. Actually, the total evaporation of the fluid goes to aggregation of nanoparticles, making this technique available only for low volume concentrations of nanoparticles. The SEM technique is rather similar. On the other hand, Zeta potential is the most accurate evaluation method using the electrophoretic behavior of the fluid. In hybrid nanofluids, the Zeta potential can have positive or negative values and the stability is evaluated as very good for around 6 25 mV [16]. Moldoveanu and Minea [16] investigated the stability of two hybrid nanofluids with alumina
silica and alumina
titania nanoparticles and found good stability by assessing the Zeta potential, (i.e., the nanofluid stability is decreasing by adding nanoparticles).

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CHAPTER 7 Barriers and challenges in hybrid nanofluids

Other method for stability estimation of hybrid nanofluids is spectral analysis. The absorbance intensity and the nanoparticles concentration in a certain fluid are reliant on the UV
vis spectral investigation, that actually reveals if the nanoparticles dispersed in the considered fluid has characteristic absorption bands in the wavelength interval 190
1100 nm. Zeta potential measurements performed by Gulzar et al. [25] on Al2O3
TiO2 Therminol-55 hybrid nanofluid showed values in the interval 68.5
57.64 mV after 3 hours of preparation, 64.3
48.36 mV after 72 hours of preparation and 54.52
34.43 mV after 7 days. Some other studies related to stability estimation are depicted in Table 7.1.

7.1.1 Stability enhancement procedures To attain stable nanofluids, it is mandatory to have a very good nanoparticles dispersion within the base liquid. Several researchers reported various methods of improving the stability of the hybrid nanofluids, that can be outlined as:

• • • •

addition of surfactants, surface modification, ultrasonic treatment, and manipulating the solution pH.

Table 7.1 Studies in regard to stability of hybrid nanofluids. Nanoparticles in the hybrid nanofluids

Method

Al2O3
SiO2 water

Zeta potential

Al2O3
TiO2 water

Zeta potential XRD and SEM UV, XRD, and SEM

Sundar et al. [19]

Al2O3
Cu nanocomposite water MWCNT
Al2O3 nanocomposite water Nd
Ni water

Madhesh et al. [20] Batmunkh et al. [21] Afrand et al. [22] Afrand et al. [23] Aparna et al. [24] Gulzar et al. [25] Mousavi et al. [26]

Cu
TiO2 water Ag
TiO2 water Fe3O4
Ag water SiO2
MWCNTs water γ
Al2O3/Ag water Al2O3
TiO2 Therminol-55 MgO
TiO2 water

Reference Moldoveanu and Minea [16] Moldoveanu and Minea [16] Suresh et al. [17] Nine et al. [18]

XRD, SEM, and Raman spectroscopy XRD, FESEM, and EDAX UV, XRD, and SEM XRD XRD Zeta potential Zeta potential SEM, XRD, and Zeta potential

7.1 Stability of hybrid nanofluids

Several surfactants as for example SDBS, CTAB, and SDS are considered to be added to improve the dispersion of nanofluids [1]. Surfactants actually improve the stability of the nanofluids and also may influence the uniformity of the nanoparticles distribution. Addition of the surfactants is an easy technique to improve the nanofluids stability, but also may influence significantly the thermophysical properties. Nanofluids demonstrate an increased sedimentation without surfactants in comparison with those with surfactants. The mechanism relies on the coverage of the nanoparticles surface with surfactants molecules and therefore, decrease the aggregation [2,3]. Surfactants used for hybrid nanofluids increased stability can be categorized in four major classes as:

• • • •

non-ionic surfactants, anionic surfactants, cationic surfactants, and amphoteric surfactants.

On the other hand, addition of surfactants is not the best option since their influence on heat transfer behavior of hybrid nanofluids is of great importance. Surfactants addition may create contamination of heat exchanger surfaces, may produce foam in the heating or cooling process and also can increase the thermal resistance of the mixture causing a decrease in thermal conductivity. So, when possible, a surfactant-free solution can be the best option. As an alternative, a number of methods can be used as: ultrasonic bath, stirrer and high-pressure homogenizer. For example, Hwang et al. [4] used a modified magnetron sputtering system in which sputtered nanoparticles were considered to mix directly. Other approaches consist of synthesis of a certain nanofluid type using surface adjustment [5], the aqueous organic process [6], and acid treatment [7]. For example, Esfe et al. [27] manufactured hybrid nanofluids with SWCNT and MgO nanoparticles at very low concentrations (up to 0.55%) and noticed an acceptable stability by stirring in magnetic field for 5.5 hours. On the other hand, Aparna et al. [24] considered the effect of ultrasonication time on their hybrid nanofluid thermal conductivity and concluded that 2 hours give the best results on stability and thermal conductivity measurements, while increasing excessively the sonication time, no real benefits can be attained. An interesting study comes from Sun et al. [28] using silver
MWCNT/water hybrid nanofluids with various dispersants. The hybrid nanofluids stability was estimated by testing the transmission ratios at 0, 2, and 12 hours. The smaller the transmittance is, the better the solution stability is attained, and results concluded that using 1631 chlorine as dispersant for the Ag
MWCNT hybrid nanofluid is the best choice. Generally, lots of authors were considering different times of sonication, varying from 0.5 to 7 hours. Nevertheless, the results are rather controversial and no pattern was identified by now, the outcomes being actually dependent on each research groups testing conditions and equipment.

259

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CHAPTER 7 Barriers and challenges in hybrid nanofluids

Kumar and Arasu [9] were presenting in a recent review article a very good synthesis of surfactant-free methods that can be applied for increasing the stability of hybrid nanofluids. Some of these are:

• • • •

mechanochemical reaction, wet mechanochemical reaction, chemical modification, and plasma treatment.

The basic mechanisms that influence the hybrid nanofluid stability were identified by Kumar and Arasu [9] and classified in two categories: (1) steric repulsion, and (2) electrostatic (charge) repulsion and were discussed in detail. If it discusses only the achievements in regard to hybrid nanofluids, the studies on stability enhancement are extremely limited since little researchers discussed this issue. Some of these results will be discussed in Sections 7.5 and 7.6.

7.2 Viscosity and thermal conductivity modeling techniques for hybrid nanofluids 7.2.1 Viscosity modeling techniques for hybrid nanofluids Viscosity is extremely important for implementing hybrid nanofluids in real life applications and influences actually the overall performance of the equipment. The main idea when dealing with viscous fluids is the large effort in pumping power and this possible disadvantage of these new fluids have to be overcome by using small nanoparticles concentrations. Nevertheless, even if some researchers studied the rheological behavior and viscosity of hybrid nanofluids, the studies are not enough to validate a strong conclusion. Afrand et al. [22] measured Fe3O4
Ag/EG hybrid nanofluid viscosity by using a Brookfield DV-I PRIME digital viscometer equipped with a temperature bath. Measurements were performed in the range of 25  C
50  C with the shear rate variation from 12.23 to 122.3 s21. The results showed that hybrid nanofluids have a Newtonian behavior at low concentrations and both the consistency index and power-law index experimental data were fitted to attain specific correlations. Ho et al. [29] investigated Al2O3
MEPCM/water viscosity and found its significantly increase. Suresh et al. [17] studied Al2O3
Cu/water hybrid nanofluid viscosity and noticed its increase. The same conclusion was also drawn by Baghbanzadeh et al. [30] for Silica/MWCNT
water. Another method to study the viscosity was artificial neural networking technique (ANN) modeling used by Afrand et al. [31] who proposed an equation for estimating the MWCNTs
SiO2/AE40 nanolubricant relative viscosity by using 48 experimental records. The correlation is an exponential one, depending on both temperature and volume fraction of the nanoparticles.

7.3 Nanoparticles dispersion in hybrid nanofluids

Some other studies performed on an Anton Paar equipment come from Moldoveanu et al. [32,33]. The research performed was on alumina, silica, and titania hybrid nanofluids at low concentrations up to 3%. They also fitted the experimental data and proposed more complex correlations depending on nanoparticles concentration and temperature. Plus, the possible hysteresis in viscosity was discussed. As for the mathematical expression of the existing correlations, the area is huge starting from basic linear equations and going to complex polynomial ones or exponential. Nevertheless, most of the correlations are polynomial, depending on volume concentrations and in some cases also depending on temperature. Overall, even if the studies on viscosity are rather limited for hybrid nanofluids, the researchers mostly used viscometers to determine experimental data that were fitted to get correlations. As a conclusion, the modeling techniques have to be extended to molecular simulations or more complex measurements studying the hysteresis effect, temperature, particle dimension, and shape.

7.2.2 Thermal conductivity modeling techniques for hybrid nanofluids Thermal conductivity of hybrid nanofluids was the most studied thermophysical characteristic especially due to its relevance in heat transfer capability. Nevertheless, the modeling techniques are rather limited to experimental data fitting. Several techniques for determining the thermal conductivity of nanofluids were identified as: transient hot wire method, thermal constants analyzer, steady state parallel plate, and 3ω method. As for the mathematical expression of the existing correlations, the area is vast starting from basic linear equations and going to complex polynomial ones, or even sinusoidal, logarithmic or exponential. Nevertheless, most of the correlations are polynomial. Few correlations proposed for hybrid nanofluids are in Table 7.2. On the other hand, Esfe et al. [39
42] performed ANN method and estimated the thermal conductivity. Besides the experimental data fitting and ANN method, another approach used in the literature, especially in numerical studies (e.g., Minea [43]), is the evaluation of thermal conductivity with the mixture law.

7.3 Nanoparticles dispersion in hybrid nanofluids As was depicted earlier, hybrid nanofluids were engineered by adding pairs of nanoparticles or hybrid nanocomposites in a base liquid. A synthetic presentation of various types of nanoparticle used for hybrid nanofluids is depicted in

261

Table 7.2 Hybrid nanofluids thermal conductivity. Reference

Hybrid nanofluid

Method

Correlation

Aparna et al. [24]

γ-Al2O3/Ag water

Experimental

knf 5 A 1 Bϕ 1 CT 1 DϕT,where,A 5 0.2154, B 5 20.1177, C 5 0.0012, and D 5 0.0018 for 30:70 Al2O3/Ag nanofluid A 5 0.541, B 5 22.8811, C 5 0.0003359, and D 5 0.0122 for 50:50 Al2O3/Ag nanofluid A 5 0.2239, B 5 1.0229, C 5 0.00129, and D 5 20.0008196 for 70:30 Al2O3/Ag nanofluid

Harandi et al. [34]

MWCNT
Fe3O4/EG

Experimental

knf kbf

Esfe et al. [35]

CuO
SWCNT

Experimental

Vafaei et al. [36]

MgO
MWCNT/EG

Experimental

Moldoveanu et al. [37]

Al2O3
SiO2
water

Experimental

5 1 1 0:0162ϕ0:7038 T0:6009
 knf 5 1 1 ð0:04056 3 ðϕT ÞÞ 2 0:003252 3 ðϕT Þ2 1 kbf

 1 0:0001181 3 ðϕT Þ3 2 0:000001431 3 ðϕT Þ4
 knf 0:3097 2 0:002T kbf 5 0:9787 1 exp 0:3081ϕ khnf 5 0:995 1 10:097φ1 2 120:835φ21 1 23:227φ2 kf 2 43:648φ22 1 22380:350φ32 khnf 5 2 0:347 1 0:003T 1 6:639φtot 2 109:024φ2tot

Moldoveanu et al. [38]

Al2O3
TiO2
water

Experimental

khnf 5 0:607 2 0:005φ1 1 0:009φ21 1 0:109φ2 2 0:059φ22 1 0:013φ32 khnf 5 2 0:347 1 0:003T 1 6:639φtot 2 109:024φ2tot

7.3 Nanoparticles dispersion in hybrid nanofluids

Table 7.3 Nanoparticles pairs and nanocomposites used in experiments. Silver based

Aluminum oxide based

Titanium oxide based

Ag
GNP
s Ag
WO3 Ag
Si Ag
MgO Ag
ZnO

Al2O3
Cu Al2O3
TiO2 Al2O3
SiO2 Al2O3
CNT Al2O3
CuO Al2O3
graphene

TiO2
SiC TiO2
Cu TiO2
ZnO TiO2
SiO2 TiO2
CuO
C TiO2
Ag TiO2
CNT TiO2
MWCNT

CNT based MWCNT
Al2O3 MWCNT
GO MWCNT
Si MWCNT
ZnO MWCNT
Ag MWCNT
SiO2 FMWCNT
Fe3O4 FMWCNT
MgO DWCNT
ZnO CNT
Fe3O4

Other nanoparticles type Ni
ND Cu
Zn GNP
Pt GNP
SiO2 Co3O4
ND Co3O4
GO Al
-Zn SiC
TiO2 Cu
Zn

Table 7.3. Plus, the fluids used for hybrid nanofluids preparation were identified in the literature as:

• • • • •

water, ethylene glycol, mixture of water with ethylene glycol, vegetable oil, different oils: PAO, transformer oil, diathermic oil, paraffin oil, and SAE.

7.3.1 Pairs of nanoparticles Using pairs of nanoparticles is believed to overcome the disadvantages of using of a particular nanoparticle put off in the base fluid. The basic idea is to combine the favorable properties offered by each nanoparticle and to overcome the drawbacks of increasing the viscosity. An effect that is insufficiently studied by now is the synergy between different types of nanoparticles. Table 7.4 shows the studies performed by now by different research groups.

7.3.2 Hybrid nanocomposites Using hybrid nanocomposites is the most studied approach in the literature and authors found numerous benefits like: improved thermal conductivity and heat transfer enhancement. Table 7.5 shows a synthesis of the studies performed by now by different research groups.

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CHAPTER 7 Barriers and challenges in hybrid nanofluids

Table 7.4 Pairs of nanoparticles used for hybrid nanofluids. Reference Moldoveanu and Minea [16] Moldoveanu and Minea [17] Munkhbayar et al. [44] Ho et al. [45]

Labib et al. [46] Ramachandran et al. [47] Esfe et al. [27] Aparna et al. [24]

Pairs of nanoparticles in the hybrid nanofluids

Base fluid

Al2O3
SiO2 Al2O3
TiO2 Ag
MWCNT Al2O3
microencapsulated phase change material (MEPCM) Al2O3
CNTs Al2O3
CuO SWCNTs(60%)
MgO(40%) Al2O3
Ag

Distilled water Distilled water Water Water

Water Deionized water Ethylene glycol Water

Table 7.5 Hybrid nanocomposites used for hybrid nanofluids. Reference Suresh et al. [17] Nine et al. [18] Sundar et al. [19] Madhesh et al. [20] Batmunkh et al. [21] Afrand et al. [22] Afrand et al. [23] Baghbanzadeha et al. [48] Jana et al. [49] Jha and Ramaprabhu [50,51] Chen et al. [52] Abbasi et al. [53]

Pairs of nanoparticles in the hybrid nanofluids Al2O3
Cu nanocomposite MWCNT
Al2O3 nanocomposite Nd
Ni Cu
TiO2 Ag
TiO2 Fe3O4
Ag SiO2
MWCNTs MWCNT
SiO2 Cu
CNT and Au
CNT metal
MWNT Ag/MWNT γ-Al2O3/MWCNT

Base fluid Water Water Water Water Water Water Water Distilled water Water Deionized water 1 EG Water Water

7.3.3 Other approaches Other approaches identified in the open literature when it comes to hybrid nanofluids are mostly referring to mixing of two simple nanofluids, that is simply the case of using pairs of nanofluids in the same base fluid. Another aspect is mixing of two base fluids, for example water and ethylene glycol, but this case is basically reducing to nanoparticles suspended in another base fluid and cannot be considered as a hybrid nanofluids, at least in the opinion of this author.

7.4 Pumping power studies and approach on hybrid nanofluids

7.4 Pumping power studies and approach on hybrid nanofluids Suresh et al. [17] in their research found a penalty in pumping power due to increase in friction factor. Moghadassi et al. [54] concluded that increasing the volume fraction of nanoparticles one will get a good heat transfer augmentation. However, they noticed an increase in friction factor and stated that this was caused by the viscosity increase due to the addition of the nanoparticles. Sundar et al. [19] reported results of the hybrid MWCNT
Fe3O4 with different concentrations and found an increase in friction factor for the 0.3% MWCNT
Fe3O4 concentration. The upsurge was 1.11 times and 1.18 times for Re equal to 3000 and 22,000, correspondingly. Yarmand et al. [7] studied graphene nanoplatelets
silver (GNP
Ag) hybrid nanofluid in terms of friction factor and heat transfer augmentation. The friction factor was improved and the pumping power was kept in satisfactory limits. Madhesh et al. [20] studied the rheological properties of Cu
TiO2 hybrid nanoparticles in connection with friction factor and found an upsurge of the friction factor due to nanoparticle loading in the suspension. These effects were explained by the viscosity increase of the hybrid nanofluid if compared with the base fluid. A comprehensive and recent study came from Nabil et al. [55]. This study reveals that the results on hybrid nanolubricants with oxide and MWCNT nanocomposites showed an increase in pumping power because of the viscosity upsurge. Huminic and Huminic [56] performed a numerical study on MgO
MWCNT/ EG nanofluids for two inlet temperatures (i.e., 313 K and 323 K), Re 5 50
1000, and hybrid nanoparticles volume concentrations between 0% and 0.4%. They discussed also, in terms of pumping power, the effect of hybrid nanofluid adoption on performances of an elliptical tube. Their study main conclusion was that the pumping power is decreasing for low concentration of hybrid nanocomposites of 0.1%
0.2%, while the hybrid nanofluids with 0.4% volume concentration produce an increase in the pumping power. A very good outline of the hybrid nanofluids advantages and disadvantages in relation to pumping power was noticed in the recent work of Babar and Ali [57]. The authors affirmed that hybrid nanofluids responded very well in practical applications in regard to thermophysical properties, nevertheless an increase in viscosity was noticed that determines a penalty in pumping power. Review concluded that a higher pumping power was noticed regardless of nanoparticles types and concentrations. As an outcome of recent hybrid nanofluids studies, it may affirm that the majority of the researchers concentrated on thermal conductivity and heat transfer enrichment and disregarded the increase in pumping power. This pumping power increase is mainly due to the viscosity increase, that is very high in many cases.

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Some future studies have to focus on the overall benefits of implementing these new nanoparticles based fluids by weighting the advantages in augmenting heat transfer and the drawbacks offered by the increase in pumping power. Plus, an overall energy efficiency parameter needs to be considered.

7.4.1 Pumping power comparison for water based hybrid nanofluids: theoretical approach In this section, a theoretical description of some hybrid nanofluids in terms of pumping power is discussed. First of all, the pumping power is mainly dependent on the fluid viscosity and density and several hybrid nanofluids were selected from the archived literature—see Table 7.6 for their viscosity and density experimental values. The analytical comparison will be attained using the equations proposed by Mansour et al. [63]:


for laminar flow: μhnf Whnf 5 Wbf μbf

ρbf ρhnf

!2 (7.1)

Table 7.6 Properties of studied water based hybrid nanofluids. Nanoparticles suspended in water

Viscosity (kg/m-s)

Density (kg/m3)

0.5% Al2O3 1 0.5% SiO2 0.5% Al2O3 1 1% SiO2 0.5% Al2O3 1 1.5% SiO2 0.5% Al2O3 1 0.5% TiO2 0.5% Al2O3 1 1% TiO2 0.5% Al2O3 1 1.5% TiO2 0.1% Al2O3
Cu 1% Al2O3
Cu 0.1% MWCNT
Fe3O4 0.3% MWCNT
Fe3O4 0.5% Ag
MgO 1% Ag
MgO 1.5% Ag
MgO 2% Ag
MgO 1% S1 nanofluid 1% S2 nanofluid 0.15% GO/Co3O4

0.000995 0.001190 0.001016 0.001101 0.001690 0.002001 0.000930 0.001935 0.000910 0.001010 0.000838 0.000890 0.001025 0.001091 0.001900 0.002200 0.001040

1018.348 1025.328 1032.308 1037.590 1063.813 1090.035 1001.300 1030.100 1002.340 1010.040 1028.680 1058.870 1089.050 1119.230 1059.650 1069.750 1001.950

Reference Moldoveanu et al. [32,33]

Mehryan et al. [58] Sundar et al. [59] Esfe et al. [60]

Balla et al. [61] Sundar et al. [62]

7.4 Pumping power studies and approach on hybrid nanofluids




for turbulent flow: μhnf Whnf 5 Wbf μbf

!0:25

ρbf ρhnf

!2 (7.2)

where W, pumping power, μ, viscosity, and ρ, density and hnf and bf refers to hybrid nanofluid and base fluid (i.e., water), correspondingly. Equations (7.1) and (7.2) were established by Mansour et al. [63] in the case of fixed values for heat flux for the same pipe configuration and taking into account the basic equations for defining pumping power both for laminar and turbulent flow. W If the ratio between pumping power Whnf . 1, then the water replacement with bf another fluid is not beneficial. Results for hybrid nanofluids from Table 7.6 are depicted in Figs. 7.2
7.4. If it looks to Fig. 7.2, it can easily notice that in turbulent flow, all of the hybrid nanofluids can efficaciously substitute water in a certain heat exchanger, while in laminar flow, only the lowest concentration of alumina
silica nanoparticles can give good results. If it looks to Fig. 7.3, one can see that disregarding the flow type (i.e., even if it is about laminar or turbulent flow), only the lowest concentration hybrid nanofluids (i.e., less than 0.5%) can successfully replace water. Fig. 7.4 describes the pumping power ratio for hybrid nanofluids considered by Esfe et al. [60] and Sundar et al. [62] and it can notice that all the hybrid nanofluids are a good option in laminar and turbulent flow, even if in some cases the

FIGURE 7.2 Pumping power ratio for hybrid nanofluids studied by Moldoveanu et al. [32,33].

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FIGURE 7.3 Pumping power ratio for hybrid nanofluids studied by Mehryan et al. [58], Sundar et al. [59], and Balla et al. [61].

FIGURE 7.4 Pumping power ratio for hybrid nanofluids studied by Esfe et al. [60] and Sundar et al. [62].

concentration is rather high (see the 2% hybrid settled by Esfe et al. [60]). Nevertheless, the described phenomenon because of to the small viscosity of the manufactured hybrid nanofluid.

7.4 Pumping power studies and approach on hybrid nanofluids

7.4.1.1 Pumping power comparison for several water based hybrid nanofluids: a numerical approach In this section, a numerical approach in estimating the hybrid nanofluids pumping power in steady state system using CFD code Ansys Fluent is considered. For this purpose, the schematic setup is shown in Fig. 7.5 and was used by this author for previous numerical studies. Actually, in Fig. 7.5 is a simple geometry used by Sundar et al. [59]. More details about this can be found in Sundar et al. [59]. The single phase method was considered to simulate the performance of the hybrid nanofluids in a typical convection application. This methodology is supposing to provide very good results, since all the thermophysical properties were previously experimentally determined. The single phase model is actually handling the nanoparticle enhanced fluid as a consistent fluid, with enhanced properties due to the solid nanoparticles incidence [43]. The governing equations are [43]: Mass conservation: divðρvÞ 5 0

(7.3)



 divðρvvÞ 5 2 grad P 1 μr2 v 2 div ρu0 u0

(7.4)

Momentum conservation:

Energy conservation:

 div ρvcp T 5 div kgradT 2 ρcp u0 t0

(7.5)

In Eqs. (7.3
7.5), v, P, and T signify the time averaged flow variables while u0 and t0 are the
variations in
velocity   and temperature, respectively. On the other hand, the terms ρu0 u0 and ρcp u0 t0 are turbulent shear stress and turbulent heat flux, consequently. The κ-ε model engaged for this numerical study has two new equations, one for turbulent kinetic energy and the other for the rate of dissipation, as is explained in

FIGURE 7.5 Considered geometry
section through the 3D tube.

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Ansys Fluent documentation. The two equations and the corresponding values were detailed in [43]. For turbulence modeling was enforced a constant turbulence intensity, equal to 1%. Further details about the numerical setup model can be found in Minea [43]. Boundary conditions. The numerical field is a 3D tube with L 5 1.75 m length and an interior diameter D 5 0.014 m (see Fig. 7.5 and Sundar et al. [59]). The tube wall is heated with a uniform heat flux q 5 12,998.83 W/m2 and at the tube inlet was imposed a constant velocity. At tube outlet the temperature and velocity gradients were considered zero. Additionally, a constant temperature of 300 K was considered at fluid entrance and Reynolds number was considered between 7800 and 22,000. Three different mesh sizes were tested in regard to grid sensitivity and its influence on numerical results and the 20 3 24 3 400 non-uniform grid was considered optimum in terms of numerical results accuracy as well as their independency in regard to the number of nodes used [43]. The model validation was completed using a comparison of present numerical data with previous ones attained both on experimental bases by Sundar et al. [59] and by theoretical means, using Notter
Rouse equation [64] expressed as: Nu 5 5 1 0:015Re0:856 Pr0:347

(7.6)

Results were compared and a very good agreement was noticed, with an accuracy of less than 4%. Discussion on pumping power. Pumping power can be assessed using the following equation [43]: _ W 5 vΔP 5w

  πD2 L ρw2 f D 2 4

(7.7)

_ ΔP, w, and f are the volume flow rate, pressure drop, fluid velocity, where, v, and friction factor, respectively. Friction factor, f, equation was found to be [56]: f5

2ΔPD ρw2 L

(7.8)

In this part, a new criterion, PEC, projected by Hasanpour et al. [65] will be debated. This criterion reflects both the enhancement in Nu and the upsurge in friction factor: 

Nuhnf Nubf



PEC 5  1=3

(7.9)

fhnf fbf

When PEC . 1, the flow is improved and the implementation of a new fluid leads to overall performance amelioration. In respect to pumping power calculus [see Eq. (7.7)], the pressure drop was numerically evaluated and the equivalent friction factor was considered as will be depicted further on.

7.5 Selection of proper hybrid nanofluids

FIGURE 7.6 Relative pumping power and PEC assessment.

The results were numerically obtained and portrayed in Fig. 7.6 where it can obviously see that silica and titania hybrid nanofluids have a good performance in respect to pumping power rise after nanoparticles addition in the base fluid. The pumping power increase over the base fluid is lower for the silica hybrid with alumina nanoparticles, actually going to a decrease in pumping power (i.e., a 4% reduction was detected) due to a reduced viscosity. One can notice here the synergy effect among alumina and silica nanoparticles, effect that was acknowledged also by this author previously. If it considers a shared examination among heat transfer enhancement and friction coefficient, PEC [see Eq. (7.9)] can be seen as a very good instrument and the corresponding outcomes are likewise illustrated in Fig. 7.6. PEC analysis can reveal a conclusion that all studied alumina, silica, and titania nanofluids are actually a worthy option as new fluids for typical convection situations if minor nanoparticle fractions are preserved.

7.5 Selection of proper hybrid nanofluids The selection of hybrid materials or proper pairs of materials for hybrid nanofluids remains an open question in the literature. The idea of replacing simple nanofluids with hybrid ones is actually to be able to decrease the pumping power and to increase the thermal conductivity while specific heat is maintained in reasonable intervals. If it considers that nanofluids research started more than 20 years ago and was not able to conduct to a straightforward conclusion, the idea of hybrid nanofluids seems a little too optimistic at this

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moment, at least in this author opinion. Nevertheless, in the absence of systematic studies on pairing different nanoparticles and base fluids, it cannot affirm what is the best combination.

7.5.1 Selection of suitable pairs of nanomaterials or hybrid materials The selection of suitable pairs of nanomaterials have to be accomplished by studying their possible synergy and their thermophysical properties at the end of the fabrication process. There is no such a study in the open literature. An attempt was performed by Moldoveanu et al. [16,19,32,33,38]. In these studies, the same conditions were applied to two hybrid nanofluids based on water, alumina, silica, and titania and the results conducted to a conclusion that alumina 1 silica hybrid nanofluids are performing better in heat transfer than alumina 1 titania due to the alumina
silica nanoparticles synergetic effect. Babar and Ali [57] also discussed the selection of pairs of nanofluids and affirmed that, in combination with features like risky chemical reactions, solubility, viscosity, and specific heat, the Price
Performance Factor have to be the main parameter which coordinates the blend of nanoparticles.

7.5.2 Selection of base fluids Appropriate selection of base fluids depends principally on the specificity of a certain technical area. For example, oil-based nanofluids are commonly involved in manufacturing operations for lubrication or high-temperature uses, although water and EG based nanofluids are frequently used in the areas where the fluid is used for cooling applications in different pipes or channels (see Babar and Ali [57]). Concluding, in regard to the base fluid selection, this desiderate depends mostly on the final implementation of the nanofluid and the temperature interval needed for a specific application.

7.6 pH control of hybrid nanofluids pH is in all cases strongly related to the hybrid nanofluid stability. On the other hand, the stability of a liquid is appropriately linked with its electro kinetic properties, thus pH is an indicator of the action of strong repulsive forces. Overall, the added improvement in heat transfer brought by nanoparticle based fluids is largely ascribed to the enhanced nanoparticles thermal conductivity that is reliant on a number of factors like: size, nature, shape, surfactant, pH, and concentration. Even if some studies on the pH variation of nanofluids are in the

7.6 pH control of hybrid nanofluids

literature, the hybrid nanofluids pH research is rather limited. Overall, the idea is that the pH increase determines a thermal conductivity augmentation. Nevertheless, other research indicates that thermal conductivity decreases while the base fluid pH upsurges for example from 2 to 11.5 [66]. Gupta et al. [1] acknowledged the influence of pH values of hybrid nanofluids not only on the suspensions stability. They affirmed that, based on different studies, the pH value it is of great relevance in obtaining also the desired thermophysical properties, like viscosity or thermal conductivity. Suresh et al. [17] experimentally determined the pH values of alumina
copper hybrid nanofluid and found to be around 5.5 value that is different from isoelectric points of alumina and copper. Also, the pH value was found to increase with nanoparticles concentration upsurge. Their explanation relies on the good suspension stability and large repulsive forces between nanoparticles. Esfe et al. [30], on the other hand, recommended to control the hybrid suspensions pH values as a very good method to check the nanofluid stability and lack of agglomeration. Farbod and Ahangarpour [67] synthesized hybrid nanoparticles of Ag/MWCNTS and prepared hybrid nanofluids. The prepared suspensions were filtered and washed using deionized water to obtain a pH of 7, considered as favorable for nanofluids stability. Xie et al. [68] established based on some experimental work that appropriate pH value for water based alumina, copper, and graphite nanofluids are 8, 9.5, and 2, respectively. Leong et al. [69] also recommended a pH 5 7 for their manufactured Cu
TiO2 hybrid nanofluid. They proved that the thermal conductivity is influenced by pH and a maximum value can be obtained for pH 5 7, when neutral solutions are prepared. Esfe et al. [60] studied Ag
MgO hybrid nanofluids in several concentrations and thought that pH 5 5.74 is an optimum value for stability. This value was considered an indication of a few hours’ stability of the hybrid nanofluid. On the other hand, Akilu et al. [70] in their study about TiO2
CuO/C hybrid nanofluid are recommending a basic pH for a better solution stability. Qing et al. [71] research was accomplished on SiO2
graphene hybrid nanofluid with 4 distinct pH, from 9 to 12. Their outcome was that the nanofluids having a pH equal to 11 have the maximum stability and a pH of 12 revealed the highest instability. Chang et al. [72] studied Ag/Fe nanocomposite hybrid nanofluid by means of both pH and zeta potential and stated that the pH can be controlled by adding HNO 3 and NaOH to the new fluid. The results showed a pH 5 8 for the suspensions and 3.8 for the nnaoparticles. Plus, when pH is increasing the stability of the suspensions is decreasing. So, they were using an alkaline solution to adjust the values and to keep the suspensions stability for six months.

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7.7 Conclusion and perspectives As one can see from the information depicted in this chapter, even if hybrid nanofluids are of increased interest at this moment, there are a lot of uncertainties in their research. All these worries have to be systematically addressed by performing coordinated research. The major concerns are:

• the big differences between theoretical, numerical and experimental outcomes; • lack of standards when it comes to fabrication; • lack of quality information when dealing with surfactants, since most of the research groups are not declaring this aspect;

• stability in time for the suspensions. Actually there is no recognized method to • • •

check this aspect and the variety of methods used by different groups cannot go to a common outcome; insufficient understanding of the mechanisms that appear in the heat transfer enhancement, especially when thermal conductivity increase is smaller than convective heat transfer coefficient increase despite of viscosity upsurge; good selection approach for different pairs of nanoparticles, overcoming the disadvantages of nanofluids themselves (otherwise, there is no point to use hybrid nanoparticles); and costs estimation starting with producing these hybrid nanofluids and continuing with their exploitation.

Nomenclature Abbreviations ANN artificial neural network CFD computational fluid dynamics CTAB cetyl trimethyl ammonium bromide EG ethylene glycol GNP graphene nanoplatelets MWCNT multiple wall carbon nanotube PEC performance evaluation criterion SDBS sodium dodecyl benzene sulfonate SDS sodium dodecyl sulfate SEM scanning electron microscopy SWCNT single wall carbon nanotube TEM transmission electron microscopy

Roman letters cp specific heat D diameter

References

f friction factor k thermal conductivity L length Nu Nusselt number P pressure P time averaged pressure Pr Prandtl number q heat flux Re Reynolds number T temperature T time averaged temperature t0 variation in temperature u0 variation in velocity v_ volume flow rate v time averaged velocity W pumping power w velocity

Greek letters φ volume fraction μ viscosity ρ density

Subscripts bf base fluid hnf hybrid nanofluid

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1384.

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

A Absorbance intensity, 258 Absorption fraction in solar weight, 218 Ag-alumina/blood hybrid unit, 244 245 Agarose phantoms, 244 245 Agglomeration, 114 116 Aggregation of nanoparticles, 257 Aging, 54 55 Ag-MgO/H2O hybrid nanofluid, 182 Alkanethiol molecules, lithography, 65f Al2O3/AIN transformer oil-based nanofluids, 239 Al2O3-Cu hybrid NPs, 235 236 Al2O3-TiO2/Therminol-55 oil, 218 219 Alumina-graphene/water hybrid nanofluids, 231 232 Alumina-molybdenum/water hybrid nanofluids, 231 232 Alumina 2 silica nanoparticles, 267 Aluminum alloy AA6061-T6, 232 Aluminum nitride (AIN) NPs/ethylene glycol hybrid nanofluids, 227 228 Aluminum oxide, 19 nanoparticles, 7 8, 238 American Society of Heating, Refrigerating, and Air Conditioning Engineers (ASHRAE) handbook, 117 119 Amphoteric surfactants, 86 87, 259 Anionic surfactants, 259 ANN. See Artificial neural network (ANN) model ANSYS fluent software, 241 Anton Paar MCR92 with concentric cylinder (CC39), 117 119 APCVD. See Atmospheric pressure chemical vapor deposition (APCVD) Apparent viscosity, 13 14 Applications of hybrid nanofluids automotive industry, 236 238 biomedical, 243 245 coolant in machining and manufacturing, 229 234 electronic cooling, 234 236 generator cooling, 238 heat exchanger, 224 228 heat pipes, 228 229 in machining process, 235t nuclear system cooling, 240 243 refrigeration and heating, ventilation and air conditioning applications, 223 224

solar energy, 218 222 space, ships, and defense, 245 transformer cooling, 238 240 Artificial atoms, 6, 6f Artificial neural network (ANN) model, 111, 260 Atmospheric pressure chemical vapor deposition (APCVD), 58 60, 58f Attritor ball mill, 72 73, 74f Au-CNT nanoparticles, 19 Automotive industry, hybrid nanofluids, 236 238

B Bachler formula, 35 36 Ball-to-particle mass ratio, 72 Basefluid, 104 105, 184 186 CNTs, 184 185 Cu-Zn hybrid nanofluid, 185 GNPs, 184 185, 185f selection, 78 83, 184 185, 272 thermal conductivity, 80t percentage enhancement in, 186f Bio microelectronic mechanical system, 243 Boiling heat transfer, 11 Bottom-up methods, nanoparticles synthesis, 50 64 chemical vapor deposition (CVD), 55 60 atomic layer chemical vapor deposition, 58 60 metal organic chemical vapor deposition, 58 plasma-enhanced chemical vapor deposition, 58 thermal chemical vapor deposition, 57 types, 57 hydrothermal method, 60 64 sol 2 gel process, 50 55, 53f applications, 53f gel, formation, 54 55 homogenous solution, preparation, 52 sol, formation, 52 54 stages, 56f types and their products, 54f Brookfield DV3T digital viscometer, 117 119 Brookfield LVDV III Ultra Rheometer, 117 119 Brownian diffusion, 36 39 coefficient, 33 35 Brownian force, 25 Brownian motion, 52 54 kinetic energy, 101 102

281

282

Index

Brownian motion (Continued) of nanoparticles, 194 197 of particles, 25

C Calibration liquid, 127 128 CAP 2000 cone, 117 119 Carbon base, 18 Carbon nanotubes (CNTs), 3 4, 19, 83, 103, 184 185. See also Multiwall carbon nanotubes (MWCNTs) Catalyst, specific area, 8 9 Cationic surfactants, 259 Ceramic base, 18 Ceramic compounds, 15 Cetyltrimethylammonium bromide (CTAB), 17, 111, 190 CFD. See Computational fluid dynamics (CFD) Chemical stability and diffusion, 19 Chemical vapor deposition (CVD), 55 60 atomic layer chemical vapor deposition, 58 60 low-pressure chemical vapor deposition, 59f metal organic chemical vapor deposition, 58 plasma-enhanced chemical vapor deposition, 58 thermal chemical vapor deposition, 57 types, 57, 57f Clustering effect, 203 204 Clustering phenomenon, 28 29 CNTs. See Carbon nanotubes (CNTs) Coefficient of Soret, 26 Coefficient of thermophoresis diffusion, 27 Colloids, stability of, 16 Commercial resistors, 67 Compressibility, 21 22 Computational fluid dynamics (CFD), 269 Concentration intensification, 180 182 Condenser, 228 Conduction, fundamental of, 10 11 Convection, 11 in nanofluids, analysis, 29 40 diffusion model, 29 32 particle migration effect, 32 40 Convection heat transfer (CHT), 11, 144 Conventional heat transfer fluids, 2 Coolant in machining and manufacturing, hybrid nanofluids, 229 234 Copper-ethylene glycol nanofluid, 17 18 Copper oxide nanoparticles, 80 Copper titania hybrid nanocomposites, 225 Coriolis density meters, 130 131 Critical heat flux, 240 Cryopreservation protocols, 243 Cryosurgery technique, 244 Cu-Ag/H2O hybrid nanofluid, 180 182

Cu-CNT nanoparticles, 19 CuO/antimony doped tin oxide (ATO) HyNF, 218 Cu-Titania/water hybrid nanofluids, 227 CVD. See Chemical vapor deposition (CVD)

D Darcy number, 167 Decomposition, 52 54 Deionized water hybrid, 116 Density, 130 131 experimental results, 131 fundamental of, 14 measurement techniques, 130 131 theory, 131 Derjaguin, Landau, Verway, and Overbeek (DLVO), 16, 256 257 Diesel electric generator (DEG), 238 Diffusion, 29 coefficient, 30 31 model, convection in nanofluids, 29 32 Diffusiophoresis, 26, 36 39 Dilatant fluids, 14 Dilution, 21 22 Dimensional vorticity, 146 Dimensionless stream function, 146 Dispersion coefficient, 164 Distribution of particles, 27, 28f DLVO. See Derjaguin, Landau, Verway, and Overbeek (DLVO) Dodecyl trimethyl ammonium bromide, 17 Dufour phenomenon, 26 Dynamic light scattering, 191 192 Dynamic viscosity, 146

E EBL. See Electron beam lithography (EBL) EG-based hybrid nanofluids, 123 124 Electrical conductivity, 160 Electric charge on particle surface, 24 Electromagnetic wave, structure, 12f Electron beam lithography (EBL), 67 69, 69f Electron beam nanolithography, 67 69, 69f Electronic cooling, hybrid nanofluids, 234 236 Electron micrograph, 191 192 Electrostatic repulsion, 16, 260 Engine oil cooling system, 237 Entropy generation analysis, hybrid nanofluids, 236 Environmental refractive index, 12 Ethylene glycol-based graphene NPs, 238 Ethylene glycol (EG), 20, 101 102, 256, 263 264 Eulerian 2 Eulerian multiphase approach, 166 Evaporator, 228

Index

Exergy efficiency, volume fraction and flow rate, 221f

F Fe3O4-Ag/EG hybrid nanofluid, 119 Fick’s laws of diffusion, 26 Finite element method (FEM), 147 148 Flow rate on coolant outlet temperature, 227 Fluids microscale additives in, 2 3 nanoscale additives in, 3 4 Foaming, 17 Forced convection heat transfer, 158 166 alumina and graphene, unitary nanofluid, 161 162 cryogenic CO2-based minimum quantity lubrication (MQL) techniques, 162 163 entropy generation, 161 162 hybrid nanofluid in different arenas, 158, 158f isotherms and streamlines, 159 160, 159f hybrid nanolubricant, 162 163 Nusselt number and friction factor, 160 161, 160f single-phase and two-phase, 163 166 titania and ferric oxide, nanofluids, 162 water-based hybrid nanofluid, 160 162 Fourier transmission infrared spectroscopy (FTIR), 191 192 Free dimension, 4 Friction, 21 22 factor, 270 Fuel cell temperature, 240 243 Fuel rods control volume, 242f geometry, 241

G Galilean thermometer, 1 2 Generator cooling, hybrid nanofluids, 238 Gibbs free energy, 55 GNPs. See Graphene nanoplatelets (GNPs) GO/Co3O4 hybrid nanofluids, 118t Gold, 7 8 Graphene, 3 4 Graphene nanoplatelets (GNPs), 184 185, 185f Graphene nanoplatelets 2 silver (GNP 2 Ag) hybrid nanofluid, 265 Graphene oxide nanosheets, 219 Gum Arabic (GA), 111, 114 116, 190

H Hamilton and Crosser model, 105 110 Hands-free cleansing gels, 8

Hartmann number, 147 149, 166 167 Heat capacity, 127 130 experimental results, 129 130 fundamental of, 14 15 measurement techniques, 127 128 theory, 128 129 Heat conduction coefficient, 10 11 Heat exchanger efficiency, 239f hybrid nanofluids, 224 228 Heat flux cooling, 245 Heating, ventilation and air conditioning (HVAC) system, 223, 225t Heat pipes, hybrid nanofluids, 228 229 Heat transfer coefficient, 4, 240f enhancement, 2, 163 in nuclear reactor, 240 rate, 10 11 through radiation, 13 Heat transferring media, 144 convection heat transfer (CHT) fluid, 144 forced convection, 158 166 hybrid nanofluid, 144 nanofluid advantages and disadvantages tradeoff, 145f natural convection, 145 157 plasmonic nanofluid, 144 in porous media, 166 167 theoretical studies and models for prediction, 167 High-pressure homogenizer, 85 86, 86f History heat transfer enhancement, conventional methods, 2 microscale additives in fluids, 2 3 nanoscale additives in fluids, 3 4 nanoscale particles and nanofluids, 4 9 Homogeneous shear mixes, 18 HVAC system. See Heating, ventilation and air conditioning (HVAC) system Hybrid nanocomposites, 263, 264t Hybrid nanofluids (HyNF), 15 40 applications, 218 245 and base fluid, 267, 272 efficiency, 216 as heat transferring media. See Heat transferring media hybrid nanocomposites, 264t isotherms and streamlines, 159f nanomaterials selection, 272 nanoparticles dispersion in, 261 264 hybrid nanocomposites, 263 pairs of nanoparticles, 263

283

284

Index

Hybrid nanofluids (HyNF) (Continued) nanoparticles pairs and nanocomposites used, 263t Nusselt number, 168t pairs of nanoparticles used for, 264t pH control of, 272 273 preparation method, 83 88 single-step method, 83 84 two step method, 85 88 pumping power ratio, 267f, 268f pumping power studies and approach on, 265 271 water based hybrid nanofluids, 266 271, 266t stability, 256 260, 258t enhancement procedures, 258 260 surfactants for, 259 thermal conductivity, 262t modeling techniques, 261 thermal properties, 15 thermophysical and rheological properties, 132 134 types, 256f viscosity modeling techniques for, 260 261 water-based, 164 166 Hybrid nanolubricants, 265 Hybrid nanoparticles, 104 105 and conventional nanoparticles, 18 20 stability, 17 Hydrophilic (wetting fluid), 132 Hydrophobic nanoparticles, 83 Hydrophobic (nonwetting fluid), 132 Hydrothermal method, nanoparticles synthesis, 60 64 heating methods in, 63 64 mold, 62 organic additives, 62 steps, 63f substrate-based methods, 63 types, 62 64

I Image transfer method, lithography, 64 66 Industrial realization, hybrid nanofluids, 181f Inertia, 36 39 Intermolecular forces, 21 22 Iron-based NPs, 243

K Knudsen number, 22

L Lithography. See also Nanolithography active nanocharacterization using STM, 70f

alkanethiol molecules, 65f electron beam nanolithography, 67 69, 69f image transfer method, 64 66 molecular and nanostructured architecture, 64 optical lithography, 66 67 parallel replication, 64 66 patterning strategy, 64 66 schematic visualization, 71f serial writing, 64 66 SPL, 64 66 SPM, 64 66, 69 72 techniques, 64 Local Nusselt number, 147 148 Low-pressure chemical vapor deposition, 59f

M Magnetic bipolar forces, 16 Magnetic number, 166 167 Magnetic vibrators, 18 Magnetohydrodynamics (MHD), 110 111 Magnetron sputtering system, 259 Magnus effect, 36 39 Mass flux equation, 34f Mass fraction, nanoparticles, 129 Maxwell model, hybrid nanofluids, 105 Measurement techniques, 258 260 Mechanical alloying technique, 72 Metal alkoxide, 50 52 Metal base nanocomposites, 18 Metal nanoparticles, 3 4 Metal organic chemical vapor deposition (MOCVD), 58, 60f Metal oxides, 3 4 nanoparticles, 19 MgO-MWCNT/EG, Newtonian blend, 119 MgOMWCNTs/ethylene glycol, 238 Microchannels, 20, 21f Microelectromechanical systems, 20 21 Microscale additives in fluids, 2 3 Microscale heat transfer, 20 22 Milling process, 72 75 attritor ball mill, 72 73, 74f plantarry mill, 75, 76f tumber horizontal, 74 75, 74f vibratory ball mill, 72, 73f Minimum quantity lubrication (MQL), 229, 231, 232f Modified magnetron sputtering system, 85 86, 87f Molecular collision rate, 101 102 Molecular dynamical method, 21 22 Molecular dynamics (MD), 21 22 Molecular precursor, 50 52 Molybdenum-desulfide hybrid nanofluids, 233 234

Index

Momentum equilibrium, 35 36 Monte Carlo method, 21 22 MQL. See Minimum quantity lubrication (MQL) Multiwall carbon nanotubes (MWCNTs), 183, 216, 259, 265. See also Carbon nanotubes (CNTs)

N Nanocharacterization using STM, 70f Nanocomposite molecules interlinking breakage, 147 Nanocryosurgery, 244 Nanofluid and hybrid nanofluid, 15 40 hybrid nanoparticles and conventional nanoparticles, 18 20 microscale heat transfer, 20 22 nanoscale heat transfer, 22 40 Brownian motion of particles, 25 convection in nanofluids, analysis, 29 40 diffusiophoresis, 26 electric charge on particle surface, 24 formation of solid layer at the interface surface, 23 24 nanoparticles, clustering, 27 29 particle flow, characteristics of, 26 27 particle shape, distribution, size, and mass formation, 27 thermal conductivity, 23 thermophoresis, 25 26 Nanofluids convection in, 29 40 inlet temperature, 227 stability, 16 thermal conductivity, 28f, 75 77 Nanolithography, 64 72. See also Lithography Nanomixture, 111 Nanoparticles agglomeration, 183 aluminum oxide, 7 8 Au-CNT, 19 as catalysts and chemical reactions, 9f clustering, 27 29 combination, 83 composition, 15 concentration, 180 184, 182f Cu-CNT, 19 dispersion in, 261 264 hybrid nanocomposites, 263 pairs of nanoparticles, 263 enhanced fluid, 269 hybrid and conventional, 18 20 loading on viscosity, hybrid nanofluid, 183f magnetic properties in, 8f metal, 3 4

metal oxide, 19 pairs and nanocomposites used, 263t properties, 75 77 pure fluids, thermophysical properties of, 77t synthesis, 50, 51f system performance, effect on, 184f thermal conductivity, 77t thermophysical properties, 20 volume fraction, effect of, 77 78 Nanoparticles synthesis, 50 75, 88 91 bottom-up method, 50 64 top-down method, 64 75 Nanorefrigerant, 224 Nanoscale additives in fluids, 3 4 Nanoscale heat transfer, 22 40 Brownian motion of particles, 25 convection in nanofluids, analysis, 29 40 diffusiophoresis, 26 electric charge on particle surface, 24 formation of solid layer at the interface surface, 23 24 microparticles and nanoparticles, 23t nanofluid superiority, 23 nanoparticles, clustering, 27 29 particle flow, characteristics of, 26 27 particle shape, distribution, size, and mass formation, 27 thermal conductivity, 23 thermophoresis, 25 26 Nanoscale particles and nanofluids, 4 9 antibacterial properties, 8 applications, 4 catalytic properties, 8 9 electrons excitation, 6f energy balance distance, 5 energy structures, 5 nanostructured materials, 4 optical properties, 6 8 properties, 6 9 top-down and bottom-up production methods, 5f NanoSperseAQ, 111 Nanostructures, top-down and bottom-up production methods, 5f Natural convection heat transfer, 145 157 aspect ratio effect and particle concentration, 148 finite volume method, 145 146 hybrid nanofluids as heat transfer media, 146f magnetic effect, 147 148 Nusselt number (Nu), 145 146 particle concentration, 147 physical models and parameters ranges, 150, 151t Rayleigh number, 148 149

285

286

Index

Natural convection heat transfer (Continued) thermophysical properties, 149 150 water-based copper (Cu) nanofluid, 145 146 Newtonian fluids, 14, 117 119 Newton’s cooling law, 11 Non-ionic surfactants, 259 Non-Newtonian fluids, 14, 117 119 Non-Newtonian hybrid nanofluid, 119 Nonwetting fluid, 132 Notter 2 Rouse equation, 270 Nusselt number, 31, 33f, 226 227 hybrid nanofluids, 168t

O Oil-based hybrid nanofluids, 123 124 Oleic acid, 17, 111, 237 Optical lithography, 66 67, 68f Optical wavelength, 13

P Paar PhysicaMCR 300, 117 119 Parallel replication, 64 66 Particle flow, characteristics of, 26 27 Particle migration effect, convection in nanofluids, 32 40 Particle shape, 197 201 cylindrical shaped nanoparticles, 199 200 distribution, size, and mass formation, 27 entropy generation minimalization, 199 200 heat transfer performance and thermophysical properties, 199 200 nanofluids stability, 199 Nusselt number of nanofluids, 199f thermal conductivity of nanofluids, 198f Particle size, 191 194 gold nanofluid, 192 193 performance and, 194 stability, 194 thermal conductivity of nanofluids, 193f Particle volume fraction, 105, 145 146, 149f Patterning strategy, lithography, 64 66 PEC. See Performance evaluation criterion (PEC) Pe´clet number, 36, 37f distribution of particles, effect on, 38f temperature and particle size, effect of, 38f viscosity, effect on, 37f PEG, 111 Performance effecting parameters basefluid, 184 186 Brownian motion of nanoparticles, 194 197 clustering effect, 203 204 nanoparticle concentration, 180 184 particle shape, 197 201 particle size, 191 194

pH value, 201 202 sonication time, 187 190 surfactant addition, 190 temperature, 186 187 Performance evaluation criterion (PEC), 270 271, 271f pH control of hybrid nanofluids, 272 273 nanofluid, 88 Photocatalytic properties, 8 Photoconversion efficiency, nanofluids, 220f Photons, 12 13 Photothermal efficiency, 219 Photovoltaic thermal (PV/T) system efficiency, 218 pH value, 201 202 Planck’s constant, 12 13 Plantarry mill, 75, 76f Plasma-enhanced chemical vapor deposition, 58 Plasmonic hybrid nanofluids, 221 Plate viscometer by Brookfield, 117 119 Polymer compounds, 15 Polypyrrole-carbon nanotubes (CNTs), 216 Polyvinyl pyrrolidone (PVP), 17, 190 Porosity, 147 148, 166 167 coefficient, 166 167 Porous media, heat transferring media in, 166 167 Preparation method, 88 91 base fluid, selection, 78 83 hybrid nanofluid, 83 88 single-step method, 83 84 two step method, 85 88 nanoparticles characterization, 75 78 combination, 83 nanoparticles synthesis, 50 75 bottom-up method, 50 64 top-down method, 64 75 Pressure drop, 180 Probe wire, 103 Pumping power, 270 ratio, 267f, 268f studies and approach on, 265 271, 266t

Q Quantum confinement, 5

R Radiation, 11 fundamental, 11 13 heat transfer, 13 Rayleigh numbers, 148, 167

Index

Refrigeration and heating, ventilation and air conditioning applications, 223 224 Repulsion electrostatic repulsion, 16, 16f steric repulsion, 16, 16f types, 16, 16f Rheometers, 117 119

S Saffman lift force, 27 Scanning probe lithography (SPL), 64 66 Scanning probe microscopy (SPM), 64 66, 69 72 SDBS. See Sodium dodecyl benzene sulfonate (SDBS) Sedimentation, 22, 114 116 rate, spherical particles, 15 16 Serial writing, 64 66 Shape factor, 105 Shear movements, 22 Silica alumina hybrid nanofluid, 115f Silicon oxide, 2 3 Single-step method, hybrid nanofluids preparation, 83 84 Single wall carbon nanotube (SWCNT), 259 SN634038, A&D vibro viscometer-Japan, 117 119 Sodium deoxycholate (SDC), 111 Sodium dodecyl benzene sulfonate (SDBS), 17, 111, 190, 259 Sodium dodecyl sulfate (SDS), 17, 190 Solar absorber, 219 Solar collectors, 13 Solar energy, hybrid nanofluids, 218 222, 222t Solar spectrum, 11 Sol 2 gel process, 50 55, 53f applications, 53f gel, formation, 54 55 homogenous solution, preparation, 52 sol, formation, 52 54 stages, 56f types and their products, 54f Solid and annular fuel, 241f Solid volume fraction, 105 Sonication time, 187 190 CNT-based nanofluids, 188 189 on particle size, 189f stability and MWCNT 2 water nanofluid, thermal conductivity, 189f thermal conductivity enhancement, 187 188 ultrasonication frequency, 187 viscosity enhancement, 189 190 Specific area, 8 9 Specific heat, 75 77

capacity, 14 15 Spherical-shaped nanoparticles, 123 SPL. See Scanning probe lithography (SPL) SPM. See Scanning probe microscopy (SPM) Stability, 111, 114 116, 256 257 colloids, 16 hybrid nanofluids, 256 260, 258t hybrid nanoparticles, 17 nanofluid, 16, 187 Steric repulsion, 16, 260 Strength ratio, magnetic forces, 166 167 Surface-active agents, 17 Surface-enhanced effect, nanostructured materials, 4f Surfactant, 17 18, 111, 201 addition, 86 88, 190 agents, 17 Surfactant-free solution, 259

T Taguchi-based L9 orthogonol array, 233 TEM. See Transmission electron microscopy (TEM) Temperature, 186 187 relative viscosity, 186 187 on solar collector’s efficiency employing nanofluid, 188f viscosity ratio and SiO2-MWCNT/SAE40 viscosity, 187f Tetrakisdimethylaminotitanium, 58 Tetramethylammonium hydroxide, 114 116 Thermal chemical vapor deposition, 57 Thermal conductivity, 10, 19, 23, 101 117 base fluids selection, 80t coefficient, 3t, 30, 80 experimental results, 113 117 hybrid nanofluids, 262t measurement techniques, 103 modeling techniques, hybrid nanofluids, 261 nanofluids, 28f, 75 77 nanoparticles, 77t, 196f nanoscale heat transfer, 23 pH value and, 201 ratio, 180 182 steady-state parallel plate method, 103 theory, 104 113 3ω method, 103 transient hot wire method, 103 values, 103 values for unitary and hybrid nanofluids, 133f viscosity conductivity, 2 3 Thermal diffusion coefficient, 29 Thermal diffusivity, 146, 160, 166 167 Thermal expansion coefficient, 146, 160

287

288

Index

Thermal resistance, 229 Thermal sensor, 103 Thermal wavelength, 13 Therminol-55 oil, 218 219 Thermofluids, 184 Thermophoresis, 25 27, 36 39 schematic, 26f Thermophysical and rheological properties challenges, 135 136 density, 130 131 heat capacity, 127 130 thermal conductivity, 101 117 unitary and hybrid nanofluids, 132 134 viscosity, 117 127 wetting, 132 TiO2-Cu nanoparticles, 19 Titanium oxide, 2 3, 8 Top-down methods, nanoparticles synthesis, 64 75 milling process, 72 75 nanolithography, 64 72 Transformer cooling, hybrid nanofluids, 238 240 Transmission electron microscopy (TEM), 257 Transport quantity, 146 T-type probe method, 103 Tumber horizontal, 74 75, 74f Turbulence modeling, 269 270 Tween-20 surfactant, 190 Two step method, hybrid nanofluids preparation, 85 88, 85f high-pressure homogenizer, 85 86, 86f modified magnetron sputtering system, 85 86, 87f pH control nanofluid, 88 surfactant addition, 86 88 ultrasonic vibration, 88

U Ultrafine aluminum oxide, 2 3 Ultrasonication frequency, 187 Ultrasonic density meters, 130 131 Ultrasonic probe, 90f Ultrasonic vibrations, 18, 88, 89f Unitary and hybrid nanofluids, 132 134

Unitary nanofluids, 129, 132 134 characteristics, 133 134 density, 134 UV spectroscopy, 191 192

V Van der Waals forces, 16 Vapor compression refrigeration performance, 224 Vibratory ball mill, 72, 73f Viscosity, 117 127, 180 diffusion, 21 22 experimental results, 123 127 fundamental of, 13 14 measurement techniques, 117 119 modeling techniques, hybrid nanofluids, 260 261 relations for hybrid nanofluids, 122t and shear stress, 126f theory, 119 123 Volumetric heat transfer resources, 165 VVER-1000 nuclear reactor, 240 241

W Water/antifreezing-based nanofluids, 237 Water-based hybrid nanofluids, 19 20, 123 124, 164 166, 266 271, 266t Water 2 EG mixtures, 123 124 Water-free solvent, 52 54 Wavelengths energy spectra, 13, 13f and frequency, 11 12 Wet gel, 54 55 Wetting, 132 Working fluids, 218

Y Yu-Choi model, 105

Z Zeta potential, 257 258 Zinc oxide, 8 ZnO-Ag/water hybrid nanofluid, thermal conductivity, 195f ZnO-MWCNT/engine oil mixture, 119