Review of Heat Conduction in Nanofluids

[+] Author and Article Information
Jing Fan

Department of Mechanical Engineering,  University of Hong Kong, Pokfulam Road, Hong Kong

Liqiu Wang1

Department of Mechanical Engineering,  University of Hong Kong, Pokfulam Road, Hong Konglqwang@hku.hk


Corresponding author.

J. Heat Transfer 133(4), 040801 (Jan 10, 2011) (14 pages) doi:10.1115/1.4002633 History: Received December 31, 2009; Revised September 24, 2010; Published January 10, 2011

Nanofluids—fluid suspensions of nanometer-sized particles—are a very important area of emerging technology and are playing an increasingly important role in the continuing advances of nanotechnology and biotechnology worldwide. They have enormously exciting potential applications and may revolutionize the field of heat transfer. This review is on the advances in our understanding of heat-conduction process in nanofluids. The emphasis centers on the thermal conductivity of nanofluids: its experimental data, proposed mechanisms responsible for its enhancement, and its predicting models. A relatively intensified effort has been made on determining thermal conductivity of nanofluids from experiments. While the detailed microstructure-conductivity relationship is still unknown, the data from these experiments have enabled some trends to be identified. Suggested microscopic reasons for the experimental finding of significant conductivity enhancement include the nanoparticle Brownian motion, the Brownian-motion-induced convection, the liquid layering at the liquid-particle interface, and the nanoparticle cluster/aggregate. Although there is a lack of agreement regarding the role of the first three effects, the last effect is generally accepted to be responsible for the reported conductivity enhancement. The available models of predicting conductivity of nanofluids all involve some empirical parameters that negate their predicting ability and application. The recently developed first-principles theory of thermal waves offers not only a macroscopic reason for experimental observations but also a model governing the microstructure-conductivity relationship without involving any empirical parameter.

Copyright © 2011 by American Society of Mechanical Engineers
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Figure 1

TEM/SEM pictures of nanoparticles/nanotubes from “drying” samples of nanofluids (10,12-13): (a) elliptical Cu nanoparticles, (b) CePO4 nanofibers, (c) hollow CuS nanoparticles, (d) octahedral Cu2O nanoparticles, and (e) carbon nanotubes

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Figure 2

Comparison of experimental data on effective thermal conductivity of nanofluids

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Figure 3

Sketch of four potential mechanisms responsible for the reported conductivity enhancement: (a) liquid-layering, (b) particle aggregation, (c) particle Brownian motion, and (d) Brownian-motion-induced convection

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Figure 4

Temperature profiles for wetting and nonwetting liquids

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Figure 5

Comparison among Wiener bounds, H-S bounds, and 2D H-S bounds

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Figure 6

Comparison between experimental data and H-S bounds (solid line: H-S upper bound; dash line: H-S lower bound) (110-111)

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Figure 7

Schematic of the three-level homogenization theory by Prasher (77)

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Figure 8

Unit cells representing nanofluids containing in-line arrays of ((a) and (d)) circular cylinders, (b) square cylinders, (c) hollow cylinders, (e) staggered arrays of circular cylinders, ((f) and (g)) in-line arrays of circular particle aggregates, (h) cross cylinders, and (i) cross-particle networks

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Figure 9

Macroscale thermal coefficients for the two particles with the same surface-to-volume ratio, radius of gyration, and volume fraction (φ=0.05)

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Figure 10

Effective thermal conductivity of four nanofluids: a comparison between the numerical results and the 2D H-S upper bounds




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