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Investigation and identification of physical mechanism for enhanced thermal conductivity in nanofluids using molecular level modeling
Investigation and identification of physical mechanism for enhanced thermal conductivity in nanofluids using molecular level modeling
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Investigation and identification of physical mechanism for enhanced thermal conductivity in nanofluids using molecular level modeling
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Investigation and identification of physical mechanism for enhanced thermal conductivity in nanofluids using molecular level modeling
Investigation and identification of physical mechanism for enhanced thermal conductivity in nanofluids using molecular level modeling
Dissertation

Investigation and identification of physical mechanism for enhanced thermal conductivity in nanofluids using molecular level modeling

2008
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Overview
Over the last decade a significant research effort has been committed to exploring the thermal transport properties of colloidal suspensions of nanosized solid particles (nanofluids). Initial experiments with Cu-water nanofluids measured up to a 40% increase in thermal conductivity for a mere 0.3% volume fraction of ∼10 nanometer (nm) diameter Cu particles. This increase is significantly larger than predicted by effective medium theory (EMT) of a composite material comprised of well dispersed particles. However, other experimental work on various compositions of nanoparticles and fluids has demonstrated thermal conductivity increases more in line with EMT. A number of possible origins for such behavior have been proposed, but a consensus has yet to emerge. More of the literature attempts to find correlations based on EMT that fit the experimental data rather than exploring the underlying mechanism. The likely candidate theories of liquid layering at the particle-fluid interface, Brownian motion induced heat transfer and particle aggregation are thoroughly explored in this thesis. We undertake a systematic investigation of these most likely mechanisms for enhanced thermal conductivity in nanofluids utilizing various analytical modeling techniques including equilibrium and non-equilibrium molecular dynamics (MD). We demonstrate that aggregation of nanoparticles is the most likely mechanism for enhanced thermal conductivity. We also include the effect of Kapitza interfacial resistance and aggregate shape on nanofluid thermal conductivity. Using our aggregate models, we investigate nanofluid viscosity. Nanoparticle clusters are shown to increase the nanofluid viscosity by up to 75% at 5% volume fraction. Overall the nanofluid exhibits shear thinning behavior.
Publisher
ProQuest Dissertations & Theses
ISBN
0549815260, 9780549815266