Skip to main content
SpringerLink
Log in

A review of uncertainties in the study of heat transfer properties of nanofluids

  • Review
  • Published:
Heat and Mass Transfer Aims and scope Submit manuscript

Abstract

Nanofluids are important heat transfer mediums with great potential in industry applications because of its high thermal conductivity when adding metal or metalloid nanoparticles, which has better heat transfer characteristics and controllability than the base liquid. However, there are great uncertainties, deviations and anomalies in the computational model, experimental results and theoretical analysis when conducting research on the thermal physical properties, convective heat transfer performance and heat transfer mechanism of nanofluids. This poses a great challenge to the precise and active controllability of nanofluids when considering their own parameters and external excitation. Also, these inevitable problems may cause certain confusions on the follow-up study of nanofluids. Based on these phenomena, this paper systematically reviews the recent researches on heat transfer performance of nanofluids. The thermophysical characteristics, convective heat transfer coefficient, stability and heat transfer mechanism of suspension mixed nanofluids were summarized and compared. It is hoped that it can provide effective references and guidance for researchers to study the heat transfer performance of nanofluids, and also provide new ideas for future researches on the heat transfer performance of nanofluids.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Abbreviations

k :

Thermal conductivity [W·m-1·K-1]

k 1 :

Thermal conductivity of clusters [W·m-1·K-1]

k eff :

Nanofluid thermal conductivity [W·m-1·K-1]

k pe :

Composite thermal conductivity [W·m-1·K-1]

T :

Temperature [K]

△t :

Time step [s]

d :

Diameter [mm]

r :

Radius [mm]

t :

Boundary layer thickness [mm]

c p :

Specific heat capacity of nanoparticles [J·kg-1·K-1]

Nu :

Nussle number

kb :

Boltzmann constant

Pr :

Prandtl number

Re :

Reynolds number

N :

Empirical shape factor (H-C model)

V :

Computational Domain

s :

Particle Mobility

n :

Parameters related to base fluid

m :

Particle-related parameters

A, B :

Formula parameters

\(\eta\) :

Liquid viscosity [kg·m-1·s-1]

\(\eta_{eff}\) :

Nanofluid viscosity [kg·m-1·s-1]

\(\varphi\) :

Volume fraction

\(\xi\) :

Shape factor

\(\Gamma\) :

Degree of nanoparticle diffusion

\(\tau,\alpha_{1,2,3}\beta,\gamma\) :

Formula parameters

pm:

Cluster body

f:

Base fluid

p:

Nanoparticles

1:

Boundary Layer

References

  1. Shuai Y, Lougou BG, Zhang H, Zhao JP, Ahouannou C, Tan HP (2021) Heat transfer analysis of solar-driven high-temperature thermochemical reactor using NiFe-Aluminate RPCs. Int J Hydrogen Energy 46:10104–10118

    Article  Google Scholar 

  2. Lougou BG, Shuai Y, Pan R, Chaffa G, Tan H (2018) Heat transfer and fluid flow analysis of porous medium solar thermochemical reactor with quartz glass cover. Int J Heat Mass Transf 127:61–74

    Article  Google Scholar 

  3. Wang HY, Pang MX, Diao YD, Zhao YH (2022) Heat transfer characteristics and flow features of nanofluids in parallel flat minichannels. Powder Technol 402:117321

    Article  Google Scholar 

  4. Abdolbaqi MK, Azmi WH, Mamat R, Sharma KV, Najafi G (2016) Experimental investigation of thermal conductivity and electrical conductivity of bioglycol-water mixture based Al2O3 nanofluid. Appl Therm Eng 102:932–941

    Article  Google Scholar 

  5. Graves JE, Latvytė E, Greenwood A, Emekwuru NG (2019) Ultrasonic preparation, stability and thermal conductivity of a capped copper-methanol nanofluid. Ultrason Sonochem 55:25–31

    Article  Google Scholar 

  6. Kanti P, Sharma KV, Ramachandra CG, Gurumurthy M (2021) Numerical study on fly ash–Cu hybrid nanofluid heat transfer characteristics. IOP Conference Series: Mater Sci Eng 1013:24–25

    Article  Google Scholar 

  7. Tong Y, Boldoo T, Ham J, Redcho HC (2020) Improvement of photo-thermal energy conversion performance of MWCNT/Fe3O4 hybrid nanofluid compared to Fe3O4 nanofluid. Energy 196:1–13

    Article  Google Scholar 

  8. Sankar P, Venkatachalapathy S, Asirvatham LG (2020) Thermal performance enhancement studies using graphite nanofluid for heat transfer applications. Heat Transf 49:3013–3029

    Article  Google Scholar 

  9. Wong KV, Leon OD (2010) Applications of Nanofluids: Current and Future. Adv Mech Eng 2:1652–1660

    Article  Google Scholar 

  10. Vicki WV, Abdullah MZ, Gunnasegaran P (2020) Effect of volume concentration and nanofluid temperature on the thermal conductivity of mono and hybrid Al2O3-TiO2 nanofluid. Proceedings of Green Design and Manufacture

  11. Karthikeyan NR, Philip J, Raj B (2008) Effect of clustering on the thermal conductivity of nanofluids. Mater Chem Phys 109:50–55

    Article  Google Scholar 

  12. Cacua K, Ordoez F, Zapata C, Herrera B, Sierra RB (2019) Surfactant concentration and pH effects on the zeta potential values of alumina nanofluids to inspect stability. Colloid Surfaces A 583:123960

    Article  Google Scholar 

  13. Li YJ, Qin ZB, Zou ZJ, Hou LA (2020) Study on influence of dispersants on stability, thermal conductivity and viscosity of BN/EG nanofluids. IOP Conference Series: Materials Science and Engineering 774:012118

    Article  Google Scholar 

  14. Hussein AM, Bakar RA, Kadirgama K (2014) Study of forced convection nanofluid heat transfer in the automotive cooling system, Case Stud. Therm Eng 2:50–61

    Google Scholar 

  15. Buongiorno J, Hu LW (2009) Nanofluid heat transfer enhancement for nuclear reactor applications. Asme Second International Conference on Micro/nanoscale Heat and Mass Transfer

  16.  Sohel MR, Khaleduzzaman SS, Saidur R, Hepbasli A, Sabri MFM, Mahbubul IM (2014) An experimental investigation of heat transfer enhancement of a minichannel heat sink using Al2O3–H2O nanofluid. Int J Heat Mass Transf 74:164–172

  17. Jamei M, Karbasi M, Dehkordi MM et al (2022) Estimating the density of hybrid nanofluids for thermal energy application: Application of non-parametric and evolutionary polynomial regression data-intelligent techniques. Measurement 189:110524

    Article  Google Scholar 

  18. Sasmal C (2017) Effects of axis ratio, nanoparticle volume fraction and its size on the momentum and heat transfer phenomena from an elliptic cylinder in water-based CuO nanofluids. Powder Technol 313:272–286

    Article  Google Scholar 

  19. Zhang XL, Liu BL, Liu J, Wang XG, Zhang HB (2020) Experimental and numerical analysis of heat transfer and flow characteristic in parabolic ducts. Int J Heat Mass Transf 147:118912

    Article  Google Scholar 

  20. Mehrjou B, Heris SZ, Mohamadifard K (2015) Experimental study of CuO/water nanofluid turbulent convective heat transfer in square cross-section duct. Exp Heat Transf 28:282–297

    Article  Google Scholar 

  21. Heris SZ, Etemad SG, Esfahany MS (2006) Experimental investigation of oxide nanofluids under laminar flow convective heat transfer. Int Commun Heat Mass Transf 33:529–535

    Article  Google Scholar 

  22. Liao L, Liu Z (2009) Forced convective flow drag and heat transfer characteristics of carbon nanotube suspensions in a horizontal small tube. Heat Mass Transf 45:1129–1136

    Article  Google Scholar 

  23. Ferrouillat S, Bontemps A, Ribeiro JP, Gruss JA, Soriano O (2011) Hydraulic and heat transfer study of SiO2/water nanofluids in horizontal tubes with imposed wall temperature boundary conditions. Int J Heat Fluid Fl 32:424–439

    Article  Google Scholar 

  24. Selvam C, Balaji T, Lal DM, Harish S (2017) Convective heat transfer coefficient and pressure drop of water-ethylene glycol mixture with graphene nanoplatelets. Exp Therm Fluid Sci 80:67–76

    Article  Google Scholar 

  25. Ceylan A, Jastrzembski K, Shah SI (2006) Enhanced solubility Ag-Cu nanoparticles and their thermal transport properties. Metall Mater Trans A 37:2033–2038

    Article  Google Scholar 

  26. Lee SS, Choi SUS, Li S, Eastman JA (1999) Measuring thermal conductivity of fluids containing oxide nanoparticles. J Heat Transf 121:280–289

    Article  Google Scholar 

  27. Eastman JA, Choi SUS (1997) Enhanced thermal conductivity through development of nanofluids. MRS Proc 457:3–11

    Article  Google Scholar 

  28. Wen D, Ding Y (2005) Formulation of nanofluids for natural convective heat transfer applications. Int J Heat Fluid Fl 26:855–864

    Article  Google Scholar 

  29. Cieslinski JT, Kozak P (2018) Experimental investigation of forced convection of water/EG-Al2O3 nanofluids inside horizontal tub. E3S Web of Conferences 70(1–5)

  30. Singh J, Kumar R, Gupta M, Kumar H (2020) Thermal conductivity analysis of GO-CuO/DW hybrid nanofluid. Mater today 28:1714–1718

    Google Scholar 

  31. Maheshwary PB, Handa CC, Nemade KR (2017) A comprehensive study of effect of concentration, particle size and particle shape on thermal conductivity of titania/water based nanofluid. Appl Therm Eng 119:79–88

    Article  Google Scholar 

  32. Chon CH, Kihm KD, Lee SP, Choi SUS (2005) Empirical correlation finding the role of temperature and particle size for nanofluid (Al2O3) thermal conductivity enhancement. Appl Phys Lett 87:153107

    Article  Google Scholar 

  33. Masuda H, Ebata A, Teramae K, Hishinuma N (1993) Alteration of thermal conductivity and viscosity of liquid by dispersing ultra-fine particles (dispersion of γ-Al2O3, SiO2 and TiO2 ultra-fine particles). Netsu Bussei 7:227–233

    Article  Google Scholar 

  34. Esfe MH, Saedodin S, Wongwises S, Toghraie D (2015) An experimental study on the effect of diameter on thermal conductivity and dynamic viscosity of Fe/water nanofluids. J Therm Anal Calorim 119:1817–1824

    Article  Google Scholar 

  35. Xing M, Yu J, Wang R (2016) Experimental investigation and modelling on the thermal conductivity of CNTs based nanofluids. Int J Therm Sci 104:404–411

    Article  Google Scholar 

  36. Xie HQ, Wang JC, Xi TG, Liu Y, Ai F, Wu QR (2002) Thermal conductivity enhancement of suspensions containing nanosized alumina particles. J Appl Phys 91:4568–4572

    Article  Google Scholar 

  37. Hong TK, Yang HS, Choi CJ (2005) Study of the enhanced thermal conductivity of Fe nanofluids. J Appl Phys 97:280–441

    Article  Google Scholar 

  38. Hwang Y, Lee JK, Lee CH, Jung Y, Cheong SI, Lee CG, Ku BC, Jang SP (2007) Stability and thermal conductivity characteristics of nanofluids. Thermochim Acta 455:70–74

    Article  Google Scholar 

  39. Jeong DD, Nelson J, Hu HH, Liu YJ (1992) Competition between inertial pressures and normal stresses in the flow induced anisotropy of solid particles. Theor Appl Rheol 60–64

  40. Xie H, Wang J, Xi T, Liu Y (2002) Thermal conductivity of suspensions containing nanosized SiC particles. Int J Thermophys 23:571–580

    Article  Google Scholar 

  41. Beck MP, Yuan Y, Warrier P, Teja AS (2009) The effect of particle size on the thermal conductivity of alumina nanofluids. J Nanopart Res 11:1129–1136

    Article  Google Scholar 

  42. Zhang X, Gu H, Fujii M (2006) Effective thermal conductivity and thermal diffusivity of nanofluids containing spherical and cylindrical nanoparticles. J Appl Phys 100:044325-044325–044335

    Google Scholar 

  43. Hamid M, Usman M, Zubair T, Haq RU, Wang W (2018) Shape effects of MoS2 nanoparticles on rotating flow of nanofluid along a stretching surface with variable thermal conductivity: A Galerkin approach. Int J Heat Mass Transf 124:706–714

    Article  Google Scholar 

  44. Kim HJ, Lee SH, Lee JH, Jang SP (2015) Effect of particle shape on suspension stability and thermal conductivities of water-based bohemite alumina nanofluids. Energy 90:1290–1297

    Article  Google Scholar 

  45. Kim SH, Choi SR, Kim D (2007) Thermal conductivity of metal-oxide nanofluids: particle size dependence and effect of laser irradiation. J Heat Transf 129:298–307

    Article  Google Scholar 

  46. Beck MP, Yuan Y, Warrier P, Teja AS (2010) The thermal conductivity of alumina nanofluids in water, ethylene glycol, and ethylene glycol+water mixtures. J Nanopart Res 12:1469–1477

    Article  Google Scholar 

  47. Agarwal R, Verma K, Agrawal NK, Duchaniya RK, Singh R (2016) Synthesis, characterization, thermal conductivity and sensitivity of CuO nanofluids. Appl Therm Eng 102:1024–1036

    Article  Google Scholar 

  48. Liu MS, Lin CC, Huang IT, Wang CC (2005) Enhancement of thermal conductivity with carbon nanotube for nanofluids. Int Commun Heat Mass Transf 32:1202–1210

    Article  Google Scholar 

  49. Duangthongsuk W, Wongwises S (2009) Measurement of temperature-dependent thermal conductivity and viscosity of TiO2-water nanofluids. Exp Therm Fluid Sci 33:706–714

    Article  Google Scholar 

  50. Turgut A, Tavman I, Chirtoc M, Schuchmann HP, Sauter C, Tavman S (2009) Thermal conductivity and viscosity measurements of water-based TiO2 nanofluids. Int J Thermophys 30:1213–1226

    Article  Google Scholar 

  51. Jwo CS, Chang H, Teng TP, Kao MJ, Gao YT (2007) A study on the effects of temperature and volume fraction on thermal conductivity of copper oxide nanofluid. J Nanosci Nanotechno 7:2161–2166

    Article  Google Scholar 

  52. Shahsavar A, Salimpour MR, Saghafian M, Shafii MB (2015) An experimental study on the effect of ultrasonication on thermal conductivity of ferrofluid loaded with carbon nanotubes. Thermochim Acta 617:102–110

    Article  Google Scholar 

  53. Jalali H, Abbassi H (2020) Analysis of the influence of viscosity and thermal conductivity on heat transfer by Al2O3-water nanofluid. Fluid Mech Mater Process 16:181–198

    Google Scholar 

  54. Wei Y, Huaqing X, Chen L, Yang L (2010) Investigation on the thermal transport properties of ethylene glycol-based nanofluids containing copper nanoparticles. Powder Technol 197:218–221

    Article  Google Scholar 

  55. Tamjid E, Guenther BH (2010) Rheology and colloidal structure of silver nanoparticles dispersed in diethylene glycol. Powder Technol 197:49–53

    Article  Google Scholar 

  56. Zhang XL, Zhang YL (2021) Experimental study on enhanced heat transfer and flow performance of magnetic nanofluids under alternating magnetic field. Int J Therm Sci 164:106897

    Article  Google Scholar 

  57. Zhang ZQ, Sheng Q, Wang RJ, Zhu ZF (2019) Effect of aggregation morphology of nanoparticles on thermal conductivity of nanofluid. Acta Phys Sin 68:05441

    Google Scholar 

  58. Almitani KH, Abu-Hamdeh NH, Etedali S, Etedali S, Abdollahi A, Golmohamadzadeh A (2020) Effects of surfactant on thermal conductivity of aqueous silica nanofluids. J Mol Liq 327:114883

    Article  Google Scholar 

  59. Nese K (2020) Cakmak, The impact of surfactants on the stability and thermal conductivity of graphene oxide de-ionized water nanofluids. J Therm Anal Calorim 139:1895–1902

    Article  Google Scholar 

  60. Chakraborty S, Sarkar I, Behera DK, Pal SK, Chakraborty S (2016) Experimental investigation on the effect of dispersant addition on thermal and rheological characteristics of TiO2 nanofluid. Powder Technol 307:10–24

    Article  Google Scholar 

  61. Hordy N, Coulombe S, Meunier JL (2013) Plasma functionalization of carbon nanotubes for the synthesis of stable aqueous nanofluids and poly (vinyl alcohol) nanocomposites. Plasma Process Polym 2:110–118

    Article  Google Scholar 

  62. Li XF, Zhu DS, Wang XJ, Wang N, Li H (2008) Thermal conductivity enhancement dependent pH and chemical surfactant for Cu-H2O nanofluids Thermochim Acta 469:98–103

  63. Çolak AB (2022) Analysis of the effect of arrhenius activation energy and temperature dependent viscosity on non-newtonian maxwell nanofluid bio-convective flow with partial slip by artificial intelligence approach. Chem Thermodyn Therm Anal 6:100039

    Article  Google Scholar 

  64. Chen H, Ding Y, He Y, Tan C (2007) Rheological behaviour of ethylene glycol based titania nanofluids. Chem Phys Lett 444:333–337

    Article  Google Scholar 

  65. Ayub A, Sabir Z, Shah SZH, Wahab HA, Sadat R, Ali MR (2022) Effects of homogeneous-heterogeneous and Lorentz forces on 3-D radiative magnetized cross nanofluid using two rotating disks. Int Commun Heat Mass Transf 130:105778

    Article  Google Scholar 

  66. Pop LM, Odenbach S (2006) Investigation of the microscopic reason for the magnetoviscous effect in ferrofluids studied by small angle neutron scattering. J Phys Condens Matter 18:2785–2802

    Article  Google Scholar 

  67. Nguyen CT, Desgranges F, Galanis N, Roy G, Mare T, Boucher S, Mintsa HA (2008) Viscosity data for Al2O3-water nanofluid-hysteresis: is heat transfer enhancement using nanofluids reliable. Int J Therm Sci 47:103–111

    Article  Google Scholar 

  68. Li H, Wang L, He Y, Hu Y, Zhu J, Jiang B (2015) Experimental investigation of thermal conductivity and viscosity of ethylene glycol based ZnO nanofluids. Appl Therm Eng 88:363–368

    Article  Google Scholar 

  69. Said Z, Saidur R, Hepbasli A, Rahim NA (2014) New thermophysical properties of water based TiO2 nanofluid-the hysteresis phenomenon revisited. Int Commun Heat Mass Transf 58:85–95

    Article  Google Scholar 

  70. Aberoumand S, Jafarimoghaddam A, Moravej M, Aberoumand H, Javaherdeh K (2016) Experimental study on the rheological behavior of silver- heat transfer oil nanofluid and suggesting two empirical based correlations for thermal conductivity and viscosity of oil based nanofluids. Appl Therm Eng 101:362–372

    Article  Google Scholar 

  71. Einstein A (1906) Eine neue bestimmung der moleküldimensionen. Ann Phys 324:289–306

    Article  MATH  Google Scholar 

  72. Brinkman HC (1952) The viscosity of concentrated suspensions and solutions. J Chem Phys 20:571–571

    Article  Google Scholar 

  73. Batchelor GK (1977) The effect of Brownian motion on the bulk stress in a suspension of spherical particles. J Fluid Mech 83:93–117

    Article  MathSciNet  Google Scholar 

  74. Kulkarni DP, Das DK, Chukwu GA (2006) Temperature dependent rheological property of copper oxide nanoparticles suspension (nanofluid). J Nanosci Nanotechno 6:1150–1154

    Article  Google Scholar 

  75. Hosseini SM, Moghadassi AR, Henneke DE (2010) A new dimensionless group model for determining the viscosity of nanofluids. J Therm Anal Calorim 100:873–877

    Article  Google Scholar 

  76. Meybodi MK, Daryasafar A, Koochi MM, Moghadasi J, Meybodi RB, Ghahfarokhi AK (2016) A novel correlation approach for viscosity prediction of water based nanofluids of Al2O3, TiO2, SiO2 and CuO. J Taiwan Inst Chem Eng 58:19–27

    Article  Google Scholar 

  77. Aberoumand S, Jafarimoghaddam A, Moravej M, Aberoumand H, Javaherdeh K (2016) Experimental study on the rheological behavior of silver-heat transfer oil nanofluid and suggesting two empirical based correlations for thermal conductivity and viscosity of oil based nanofluids. Appl Therm Eng 101:362–372

    Article  Google Scholar 

  78. Heidari E, Sobati MA, Movahedirad S (2016) Accurate prediction of nanofluid viscosity using a multilayer perceptron artificial neural network (MLP-ANN). Chemometr Intell Lab 155:73–85

    Article  Google Scholar 

  79. Wei L, Arasteh H, Abdollahi A, Parsian A, Taghipour A, Mashayekhi R, Tlili I (2020) Locally weighted moving regression: A non-parametric method for modeling nanofluid features of dynamic viscosity. Physica A 550

  80. Bayat J, Nikseresht AH (2011) Investigation of the different base fluid effects on the nanofluids heat transfer and pressure drop. Heat Mass Transf 47:1089–1099

    Article  Google Scholar 

  81. Dibaei M, Kargarsharifabad H (2017) New achievements in Fe3O4 nanofluid fully developed forced convection heat transfer under the effect of a magnetic field: An Experimental Study. J Heat Mass Transf Res 4:1–11

    Google Scholar 

  82. Ebrahimi S, Saghravani SF (2018) Experimental study of the thermal conductivity features of the water based Fe3O4/CuO nanofluid. Heat Mass Transf 54:1–10

    Article  Google Scholar 

  83. Sundar LS, Naik MT, Sharma KV, Singh MK, Reddy TCS (2012) Experimental investigation of forced convection heat transfer and friction factor in a tube with Fe3O4 magnetic nanofluid. Exp Therm Fluid Sci 37:65–71

    Article  Google Scholar 

  84. Afrand M, Toghraie D, Sina N (2016) Experimental study on thermal conductivity of water-based Fe3O4 nanofluid: Development of a new correlation and modeled by artificial neural network. Int Commun Heat Mass Transf 75:262–269

    Article  Google Scholar 

  85. Sundar LS, Singh MK, Sousa A (2013) Investigation of thermal conductivity and viscosity of Fe3O4 nanofluid for heat transfer applications. Int Commun Heat Mass Transf 44:7–14

    Article  Google Scholar 

  86. Sundar LS, Singh MK, Sousa A (2013) Thermal conductivity of ethylene glycol and water mixture based Fe3O4 nanofluid. Int Commun Heat Mass Transf 49:17–24

    Article  Google Scholar 

  87. Ebaid M, Al-Bsoul M, Ghrair AM (2019) Effect of magnetic field on heat transfer enhancement using Fe3O4 nanofluids in a heated pipe. 16th IEEE International Multi-Conference on Systems

  88. Sha L, Ju Y, Hua Z (2017) The influence of the magnetic field on the convective heat transfer characteristics of Fe3O4/water nanofluids. Appl Therm Eng 126:108–116

    Article  Google Scholar 

  89. Hatami N, Banari AK, Malekzadeh A, Pouranfard AR (2016) The effect of magnetic field on nanofluids heat transfer through a uniformly heated horizontal tube. Phys Lett A 381:510–515

    Article  Google Scholar 

  90. Li Q, Xuan YM, Wang J (2005) Experimental investigations on transport properties of magnetic fluids. Exp Therm Fluid Sci 30:109–116

    Article  Google Scholar 

  91. Philip J, Shima PD, Raj B (2007) Enhancement of thermal conductivity in magnetite based nanofluid due to chainlinke structures. Appl Phys Lett 91:203108(1–3)

  92. Asirvatham LG, Vishal N, Gangatharan SK, Lal DM (2009) Experimental study on forced convective heat transfer with low volume fraction of CuO/Water Nanofluid. Energies 2:97–119

    Article  Google Scholar 

  93. Li DD, Zhao WL, Liu ZM, Zhu BJ (2011) Experimental investigation of heat transfer enhancement of the heat pipe using CuO-Water nanofluid. Adv Mater Res 160:507–512

    Article  Google Scholar 

  94. Saeedinia M, Akhavan-Behabadi MA, Razi P (2012) Thermal and rheological characteristics of CuO-Base oil nanofluid flow inside a circular tube–ScienceDirect. Int Commun Heat Mass Transf 39:152–159

    Article  Google Scholar 

  95. Gangadevi R, Senthilraja S, Vinayagam BK (2021) Investigations of hybrid PV/spiral flow solar collector with CuO/water nanofluid-an experimental study. Int J Energy Technol Pol 17:481–493

    Article  Google Scholar 

  96. Suresh S, Chandrasekar M, Sekhar SC (2011) Experimental studies on heat transfer and friction factor characteristics of CuO/water nanofluid under turbulent flow in a helically dimpled tube. Heat Mass Transf 35:542–549

    Google Scholar 

  97. Eastman JA, Choi US, Li S, Thompson J (1996) Enhanced thermal conductivity through the development of nanofluids. MRS Online Proc Libr 457:3–11

    Article  Google Scholar 

  98. Derakhshan MM, Akhavan-Behabadi MA, Mohseni SG (2015) Experiments on mixed convection heat transfer and performance evaluation of MWCNT-Oil nanofluid flow in horizontal and vertical microfin tubes-Science Direct. Exp Therm Fluid Sci 61:241–248

    Article  Google Scholar 

  99. Asadi A, Asadi M, Rezaniakolaei A, Rosendahl LA, Afrand M, Wongwises S (2018) Heat transfer efficiency of Al2O3-MWCNT/thermal oil hybrid nanofluid as a cooling fluid in thermal and energy management applications: An experimental and theoretical investigation. Int J Heat Mass Transf 117:474–486

    Article  Google Scholar 

  100. Gholamalizadeh E, Pahlevanzadeh F, Ghani K, Karimipour A, Safaei MR (2019) Simulation of water/FMWCNT nanofluid forced convection in a microchannel filled with porous material under slip velocity and temperature jump boundary conditions. Int J Numer Method H 30:2329–2349

    Article  Google Scholar 

  101. Umer IS, Rajashekhar P, Marneni N (2019) Experimental investigation of natural convection heat transfer characteristics in MWCNT-thermal oil nanofluid. J Therm Anal Calorim 135:1197–1209

    Article  Google Scholar 

  102. Narankhishig Z, Ham J, Lee H, Cho H (2021) Convective heat transfer characteristics of nanofluids including the magnetic effect on heat transfer enhancement - a review. Appl Therm Eng 193:116987

    Article  Google Scholar 

  103. Sedighi M, Mohebbi A (2014) Investigation of nanoparticle aggregation effect on thermal properties of nanofluid by a combined equilibrium and non-equilibrium molecular dynamics simulation. J Mol Liq 197:14–22

    Article  Google Scholar 

  104. Fu R, Liu ZY, Chen YY, Yan YY (2019) Experimental investigation of turbulent forced heat transfer of Fe3O4 ethylene glycol-water nanofluid with highly disaggregated particles. Therm Sci Eng Progr 10:1–9

    Article  Google Scholar 

  105. Angayarkanni SA, Philip J (2015) Review on thermal properties of nanofluids: recent developments. Adv Colloid Interface Sci 225:146–176

    Article  Google Scholar 

  106. Bigdeli MB, Fasano M, Cardellini A, Chiavazzo E, Asinari P (2016) A review on the heat and mass transfer phenomena in nanofluid coolants with special focus on automotive applications. Renew Sustain Ener Rev 60:1615–1633

    Article  Google Scholar 

  107. Zhang XL, Wang YC, Li M, Wang SD, Li XL (2017) Improved flow and heat transfer characteristics for heat exchanger by using a new humped wavy fin. Appl Therm Eng 124:510–520

    Article  Google Scholar 

  108. Song D, Jing D, Ma W, Zhang X (2019) Effect of particle aggregation on thermal conductivity of nanofluids: Enhancement of phonon MFP. J Appl Phys 125:015103

    Article  Google Scholar 

  109. Wei W, Chao J, Hu X, Han Q, Liu S, Zhou Y (2016) Fractal analysis of the effect of particle aggregation distribution on thermal conductivity of nanofluids. Phys Lett A 380:2953–2956

    Article  Google Scholar 

  110. Subramaniam CG (2019) On the effective thermal conductivity of nanofluids with fractal aggregation. J Heat Transf 4:1–4

    Google Scholar 

  111. Suleimanov BA, Abbasov HF (2016) Effect of copper nanoparticle aggregation on the thermal conductivity of nanofluids. Russ J Phys Chem 90:420–428

    Article  Google Scholar 

  112. Chen HS, Ding YL, Tan CQ (2007) Rheological behaviour of nanofluids. New J Phys 9:367

    Article  Google Scholar 

  113. Kumar A, Gangawane KM (2022) Effect of precipitating agents on the magnetic and structural properties of the synthesized ferrimagnetic nanoparticles by co-precipitation method. Powder Technol 401:117298

    Article  Google Scholar 

  114. Mahbubul IM, Shahrul IM, Khaleduzzaman SS, Saidur R, Amalina MA, Turgut A (2015) Experimental investigation on effect of ultrasonication duration on colloidal dispersion and thermophysical properties of alumina–water nanofluid. Int J Heat Mass Transf 88:73–81

    Article  Google Scholar 

  115. Wiriyasart S, Suksusron P, Hommalee C, Siricharoenpanich A, Naphon P (2021) Heat transfer enhancement of thermoelectric cooling module with nanofluid and ferrofluid as base fluids. Case Stud Therm Eng 24:100877

    Article  Google Scholar 

  116. Azmi W, Sharma K, Mamat R, Najafi G, Mohamad M (2016) The enhancement of effective thermal conductivity and effective dynamic viscosity of nanofluids-a review. Renew Sustain Ener Rev 53:1046–1058

    Article  Google Scholar 

  117. Keblinski P, PHillpot SR, Choi SUS, Eastman JA (2002) Mechanism of heat flow in suspensions of nano-sized particles (nanofluids). Int J Heat Mass Transf 45:855–863

  118. Babaei H, Keblinski P, Khodadadi JM (2013) Thermal conductivity enhancement of paraffins by increasing the alignment of molecules through adding CNT/graphene. Int J Heat Mass Transf 58(1–2):209–216

    Article  Google Scholar 

  119. Mugica I, Poncet S (2020) A critical review of the most popular mathematical models for nanofluid thermal conductivity. J Nanopart Res 22:113

    Article  Google Scholar 

  120. Shah NA, Tosin O, Shah R, Salah B, Chung JD (2021) Brownian motion and thermophoretic diffusion effects on the dynamics of MHD upper convected maxwell nanofluid flow past a vertical surface. Phys Scripta 96:125722

    Article  Google Scholar 

  121. Ruzicka MC (2008) On dimensionless numbers. Chem Eng Res Des 86:835–868

    Article  Google Scholar 

  122. Gad-el-Hak M (2004) Transport phenomena in microdevices, ZAMM-J. Appl Math Mech 84:494–498

    MATH  Google Scholar 

  123. Buschmann MH, Azizian R, Kempe T, Julia JE, Cuenca RM, Sunden B, Wu Z, Seppala A, Nissila TA (2018) Correct interpretation of nanofluid convective heat transfer. Int J Therm Sci 129:504–531

    Article  Google Scholar 

  124. Zhang XL, Wang YC, Jia RZ, Wan R (2017) Investigation on heat transfer and flow characteristics of heat exchangers with different trapezoidal ducts. Int J Heat Mass Transf 110:863–872

    Article  Google Scholar 

  125. Keblinski P, Prasher R, Eapen J (2008) Thermal conductance of nanofluids: is the controversy over. J Nanopart Res 10:1089–1097

    Article  Google Scholar 

  126. Eapen J, Rusconi R, Piazza R, Yip S (2008) The classical nature of thermal conduction in nanofluids. J Heat Transf 132:369–380

    Google Scholar 

  127. Maxwell JCA (2014) A treatise on electricity and magnetism. Nature 182:478–480

    Google Scholar 

  128. Bruggeman DAG (1935) Berechnung verschiedener physikalisher konstanten von heterogenen substanzen. Ann Phys 24:636–664

    Article  Google Scholar 

  129. Lord R (1892) On the influence of obstacles arranged in rectangular order upon the properties of a medium. Philos Mag Ser 34:481–502

    Article  MATH  Google Scholar 

  130. Hamilton RL, Crosser OK (1962) Thermal conductivity of heterogeneous two-component systems. Ind Eng Chem Fund 1:27–40

    Article  Google Scholar 

  131. Zhang XL, Wang YC, Zhao DW, Guo J (2017) Improved thermal performance of heat exchanger with TiO2 nanoparticles coated on the surfaces. Appl Therm Eng 112:1153–1162

    Article  Google Scholar 

  132. Leong KC, Yang C, Murshed S (2006) A model for the thermal conductivity of nanofluids-The effect of interfacial layer. J Nanopart Res 8:245–254

    Article  Google Scholar 

  133. Yoo DH, Hong KS, Yang HS (2007) Study of thermal conductivity of nanofluids for the application of heat transfer fluids. Thermochim Acta 455:66–69

    Article  Google Scholar 

  134. Alipour R, Ghoranneviss M, Mirzaee M, Jafari A (2014) The direct effect of interfacial nanolayers on thermal conductivity of nanofluids. Heat Mass Transf 50:1727–1735

    Article  Google Scholar 

  135. Yang L, Xu X (2017) A renovated Hamilton-Crosser model for the effective thermal conductivity of CNTs nanofluids. Int Commun Heat Mass Transf 81:42–50

    Article  Google Scholar 

  136. Patel HE, Das SK, Sundararajan TA, Nair AS, Pradeep T (2003) Thermal conductivities of naked and monolayer protected metal nanoparticle based nanofluids: Manifestation of anomalous enhancement and chemical effects. Appl Phys Lett 83:2931–2933

    Article  Google Scholar 

  137. Koo J, Kleinstreuer C (2005) Impact analysis of nanoparticle motion mechanisms on the thermal conductivity of nanofluids. Int Commun Heat Mass Transf 32:1111–1118

    Article  Google Scholar 

  138. Azizian R, Doroodchi E, Moghtaderi B (2012) Effect of nanoconvection caused by Brownian Motion on the enhancement of thermal conductivity in nanofluids. Ind Eng Chem Res 51:1782–1789

    Article  Google Scholar 

  139. Osman S, Sharifpur M, Meyer JP (2019) Experimental investigation of convection heat transfer in the transition flow regime of aluminum oxide-water nanofluids in a rectangular channel. Int J Heat Mass Transf 133:895–902

    Article  Google Scholar 

  140. Li JH, Zhang XL, Xu B, Yuan MY (2021) Nanofluid research and applications: a review. Int Commun Heat Mass Transf 127:105543

    Article  Google Scholar 

  141. Das SK, Putra N, Thiesen P, Roetzel W (2003) Temperature dependence of thermal conductivity enhancement for nanofluids. J Heat Transf 125:567–574

    Article  Google Scholar 

  142. Li CH, Peterson GP (2006) Experimental investigation of temperature and volume fraction variations on the effective thermal conductivity of nanoparticle suspensions (nanofluids). J Appl Phys 99:084314

    Article  Google Scholar 

  143. Ahmadi MH, Mirlohi A, Nazari MA, Ghasempour R (2018) A review of thermal conductivity of various nanofluids. J Mol Liq 265:181–188

    Article  Google Scholar 

  144. Timofeeva EV, Gavrilov AN, Mccloskey JM, Tolmachev YV, Sprunt S, Lopatina LM, Selinger JV (2007) Thermal conductivity and particle agglomeration in alumina nanofluids: Experiment and theory. Phys Rev E 76:061203

    Article  Google Scholar 

  145. Prasher R, Bhattacharya P, Phelan PE (2005) Thermal conductivity of nanoscale colloidal solutions (nanofluids). Phys Rev Lett 94:025901

    Article  Google Scholar 

  146. Jain S, Patel HE, Das SK (2009) Brownian dynamic simulation for the prediction of effective thermal conductivity of nanofluid. J Nanopart Res 4:767–773

    Article  Google Scholar 

  147. Abbaspoursani K, Allahyari M, Rahmani M (2011) An improved model for prediction of the effective thermal conductivity of nanofluids. J Eng Technol 58:234–237

    Google Scholar 

  148. Dong S, Chen X (2017) An improved model for thermal conductivity of nanofluids with effects of particle size and Brownian motion. J Therm Anal Calorim 129:1–9

    Article  Google Scholar 

  149. Evans W (2006) Role of Brownian motion hydrodynamics on nanofluid thermal conductivity. Appl Phys Lett 88:219–482

    Article  Google Scholar 

  150. Zhang XL, Zhang YL, Liu ZM, Liu J (2020) Analysis of heat transfer and flow characteristics in typical cambered ducts. Int J Therm Sci 150:106226

    Article  Google Scholar 

  151. Gao JW, Zheng RT, Ohtani H, Zhu DS, Chen G (2009) Experimental investigation of heat conduction mechanisms in nanofluids. Clue on clustering, Nano Lett 12:4128–4132

    Article  Google Scholar 

  152. Zhang XL, Zhang YL (2021) Heat transfer and flow characteristics of Fe3O4-water nanofluids under magnetic excitation. Int J Therm Sci 163:106826

    Article  Google Scholar 

  153. Bao Y (2008) Thermal conductivity equations based on Brownian motion in suspensions of nanoparticles (nanofluids). J Heat Transf 130:156–161

    Google Scholar 

  154. Ahmed Z, Bhargav A (2020) Effect of aggregation morphology on thermal conductivity and viscosity of Al2O3-CO2 nanofluid: A molecular dynamics approach. Nanosci Technol 12

  155. Zhou D, Wu H (2014) A thermal conductivity model of nanofluids based on particle size distribution analysis. Appl Phys Lett 105:1–4

    Google Scholar 

  156. Selvakumar RD, Dhinakaran S (2016) A multi-level homogenization model for thermal conductivity of nanofluids based on particle size distribution (PSD) analysis. Powder Technol 301:310–317

    Article  Google Scholar 

  157. Liu M, Ding C, Wang J (2016) Modeling of thermal conductivity of nanofluids considering aggregation and interfacial thermal resistance. RSC Adv 6:3571–3577

    Article  Google Scholar 

  158. Younes H, Christensen G, Luan X, Hong H, Smith P (2012) Effects of alignment, pH, surfactant, and solvent on heat transfer nanofluids containing Fe2O3 and CuO nanoparticles. J Appl Phys 111:064308

    Article  Google Scholar 

  159. Philip J, Shima PD (2012) Thermal properties of nanofluids. Adv Colloid Inter Sci 183:30–45

    Article  Google Scholar 

  160. Babita SK, Sharma SM (2016) Gupta, Preparation and evaluation of stable nanofluids for heat transfer application: a review. Exp Therm Fluid Sci 79:202–212

    Article  Google Scholar 

  161. Choi SUS, Zhang ZG, Yu W, Lockwood FE, Grulke EA (2001) Anomalous thermal conductivity enhancement in nanotube suspensions. Appl Phys Lett 79:2252–2254

    Article  Google Scholar 

  162. Israelachvili JN (1992) Intermolecular and surface forces, Academic Press

  163. Yu CJ, Richter AG, Datta A, Durbin MK, Dutta P (2000) Molecular layering in a liquid on a solid substrate: an X-ray reflectivity study. Physica B 283:27–31

    Article  Google Scholar 

  164. Keblinski P, Phillpot SR, Choi S, Eastman JA (2002) Mechanisms of heat flow in suspensions of nano-sized particles (nanofluids). Int J Heat Mass Transf 45:855–863

    Article  MATH  Google Scholar 

  165. Xue Q, Xu WM (2005) A model of thermal conductivity of nanofluids with interfacial shells. Mater Chem Phys 90:298–301

    Article  Google Scholar 

  166. Yu W, Choi S (2004) The role of interfacial layers in the enhanced thermal conductivity of nanofluids: A renovated Maxwell model. J Nanopart Res 6:355–361

    Article  Google Scholar 

  167. Kotia A, Borkakoti S, Deval P, Ghosh SK (2017) Review of interfacial layer’s effect on thermal conductivity in nanofluid. Heat Mass Transf 53:2199–2209

    Article  Google Scholar 

  168. Tausif SM, Kalidas D, Kumar KP (2018) Consequences of nanoparticle diameter and solid-liquid interfacial layer on the SWCNT/EO nanofluid flow over various shaped thin slendering needles. Chinese J Phys 45:2439–2447

    Google Scholar 

  169. Rizvi IH, Jain A, Ghosh SK, Mukherjee PS (2013) Mathematical modelling of thermal conductivity for nanofluid considering interfacial nano-layer. Heat Mass Transf 49:595–600

    Article  Google Scholar 

  170. Pasrija R, Srivastava S (2014) The interfacial layer and the thermal conductivity of nanofluid. Heat Transf-Asian Re 43:288–296

  171. Jiang H, Li H, Xu Q, Shi L (2014) Effective thermal conductivity of nanofluids considering interfacial nano-shells. Mater Chem Phys 148:195–200

    Article  Google Scholar 

  172. Barai DP, Bhanvase BA, Pandharipande SL (2022) Artificial neural network for prediction of thermal conductivity of rGO–metal oxide nanocomposite-based nanofluids. Neural Comput Appl 34:271–282

    Article  Google Scholar 

  173. Yadav D, Naruka DS, Singh PK (2020) Employing ANN model for prediction of thermal conductivity of CNT nanofluids. International Conference on Contemporary Computing and Applications

  174. Rostami S, Toghraie D, Shabani B, Sina N, Barnoon P (2020) Measurement of the thermal conductivity of MWCNT-CuO/water hybrid nanofluid using artificial neural networks (ANNs). J Therm Anal Calorim 143:1097–1105

    Article  Google Scholar 

  175. Rostami S, Kalbasi R, Sina N, Goldanlou AS (2020) Forecasting the thermal conductivity of a nanofluid using artificial neural networks. J Therm Anal Calorim 145:2095–2104

    Article  Google Scholar 

  176. Lougou BG, Han DM, Zhang H, Jiang B, Anees J, Ahouannou C, Zhao J, Shuai Y (2020) Numerical and experimental analysis of reactor optimum design and solar thermal-chemical energy conversion for multidisciplinary applications – ScienceDirect. Energy Convers Manage 213:112870

    Article  Google Scholar 

  177. Lougou BG, Shuai Y, Zhang H, Ahouannou C, Zhao J, Kounouhewa BB, Tan H (2020) Thermochemical CO2 reduction over NiFe2O4@alumina filled reactor heated by high-flux solar simulator. Energy 197:117267

    Article  Google Scholar 

  178. Yong S, Hao Z, Lougou BG, Jiang B, Mustafa A, Wang C, Wang F, Zhao J (2021) Solar-driven thermochemical redox cycles of ZrO2 supported NiFe2O4 for CO2 reduction into chemical energy. Energy 222:120073

    Google Scholar 

Download references

Acknowledgements

Financial support is provided by the China Postdoctoral Science Foundation (2020M682206), Taishan Scholar Program of Shandong (ts201712054), Natural Science Foundation of Shandong Province (ZR2019MEE072), and National Natural Science Foundation of China (51806114).

Author information

Authors and Affiliations

  1. iSMART, Qingdao University of Technology, Qingdao, 266520, China

    Xilong Zhang

  2. School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao, 266520, China

    Xilong Zhang & Junhao Li

Authors
  1. Xilong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Junhao Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Junhao Li.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Highlight

•  Comprehensively and systematically review experiments related to heat transfer of nanofluids.

•  Through the comparison of experimental results, it was found that there were differences and inconsistencies in experimental results.

•  Analysis of differences in research results and identification of causes through analysis.

•  Review the application of neural networks and machine learning in the study of heat transfer of nanofluids.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, X., Li, J. A review of uncertainties in the study of heat transfer properties of nanofluids. Heat Mass Transfer 59, 621–653 (2023). https://doi.org/10.1007/s00231-022-03276-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00231-022-03276-1

Keywords

Search

Navigation