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The effect of nanoparticle aggregation on the thermal conductivity of nanocomposites or nanofluids is typically nonnegligible. A universal model (Maxwell model) including nanoparticle aggregation is modified in order to predict the thermal conductivity of nanocomposites more accurately. The predicted thermal conductivities of silica and titania nanoparticle powders are compared first with that measured by a hot-wire method and then with those in previous experimental works. The results show that there is good agreement between our model and experiments, and that nanoparticle aggregation in a nanocomposite enhances the thermal conductivity greatly and should not be ignored. Because it considers the effect of aggregation, our model is expected to yield precise predictions of the thermal conductivity of composites.

The hot-wire method is applied in this paper to probe the thermal conductivity (TC) of Cu and Ni nanoparticle packed beds (NPBs). A different decrease tendency of TC versus porosity than that currently known is discovered. The relationship between the porosity and nanostructure is investigated to explain this unusual phenomenon. It is found that the porosity dominates the TC of the NPB in large porosities, while the TC depends on the contact area between nanoparticles in small porosities. Meanwhile, the Vickers hardness (HV) of NPBs is also measured. It turns out that the enlarged contact area between nanoparticles is responsible for the rapid increase of HV in large porosity, and the saturated nanoparticle deformation is responsible for the small increase of HV in low porosity. With both TC and HV considered, it can be pointed out that a structure of NPB with a porosity of 0.25 is preferable as a thermoelectric material because of the low TC and the higher hardness. Although Cu and Ni are not good thermoelectric materials, this study is supposed to provide an effective way to optimize thermoelectric figure of merit (ZT) and HV of nanoporous materials prepared by the cold-pressing method.