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Computational analysis of factors influencing thermal conductivity of nanofluids

Okeke, G, Witharana, S, Antony, SJ and Ding, Y (2011) Computational analysis of factors influencing thermal conductivity of nanofluids. Journal of Nanoparticle Research, 13 (12). 6365 - 6375. ISSN 1572-896X

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Abstract

Numerical investigations are conducted to study the effect of factors such as particle clustering and interfacial layer thickness on thermal conductivity of nanofluids. Based on this, parameters including Kapitza radius, and fractal and chemical dimension which have received little attention by previous research are rigorously investigated. The degree of thermal enhancement is analysed for increasing aggregate size, particle concentration, interfacial thermal resistance, and fractal and chemical dimensions. This analysis is conducted for water-based nanofluids of Alumina (Al2O3), CuO and Titania (TiO2) nanoparticles where the particle concentrations are varied up to 4vol%. Results from the numerical work are validated using available experimental data. For the case of aggregate size, particle concentration and interfacial thermal resistance; the aspect ratio (ratio of radius of gyration of aggregate to radius of primary particle, Rg/a) is varied between 2 to 60. It was found that the enhancement decreases with interfacial layer thickness. Also the rate of decrease is more significant after a given aggregate size. For a given interfacial resistance, the enhancement is mostly sensitive to Rg/a <20 indicated by the steep gradients of data plots. Predicted and experimental data for thermal conductivity enhancement are in good agreement. On the influence of fractal and chemical dimensions (dl and df) of Alumina-water nanofluid, the Rg/a was varied between 2-8, dl between 1.2-1.8 and df between 1.75-2.5. For a given concentration, the enhancement increased with the reduction of dl or df . It appears a distinctive sensitivity of the enhancement to df, in particular in the range 2-2.25, for all values of Rg/a. However the sensitivity of dl was largely depended on the value of Rg/a. The information gathered from present work on the sensitivity of thermal conductivity enhancement to aggregate size, particle concentration, interfacial resistance, and fractal and chemical dimensions will be useful in manufacturing highly thermally conductive nanofluids. Further research on the refine cluster evolution dynamics as a function of particle-scale properties is underway.

Item Type: Article
Keywords: nanofluids, modelling
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Process, Environmental and Materials Engineering (Leeds) > Institute for Particle Science and Engineering (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 12 Sep 2011 12:59
Last Modified: 15 Sep 2014 03:53
Published Version: http://dx.doi.org/10.1007/s11051-011-0389-9
Status: Published
Publisher: Springer
Identification Number: 10.1007/s11051-011-0389-9
URI: http://eprints.whiterose.ac.uk/id/eprint/43261

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