The effect of surface roughness on phonon transport in a nanowire has often been described by treating the surface as flat with a specularity parameter ͑p͒ in the range between 0 and 1. A lower thermal conductivity limit is approached at p = 0 for diffuse surface. It is demonstrated here by Monte Carlo simulation that sawtooth roughness on a nanowire can cause phonon backscattering and suppress the thermal conductivity below the diffuse surface limit. The backscattering effect can be accounted for only by a negative p if the detail of the surface roughness is ignored.

No abstract

We have measured the thermal resistance of a 152‐nm-diameter carbon nanofiber before and after a platinum layer was deposited on the contacts between the nanofiber and the measurement device. The contact resistance was reduced by the platinum coating for about 9–13% of the total thermal resistance of the nanofiber sample before the platinum coating. At a temperature of 300K, the axial thermal conductivity of the carbon nanofiber is about three times smaller than that of graphite fibers grown by pyrolysis of natural gas prior to high-temperature heat treatment, and increases with temperature in the temperature range between 150K and 310K. The phonon mean free path was found to be about 1.5nm and approximately temperature-independent. This feature and the absence of a peak in the thermal conductivity curve indicate that phonon-boundary and phonon-defect scattering dominate over phonon-phonon Umklapp scattering for the temperature range.

We have assembled tin dioxide nanobelts with low-power microheaters for detecting dimethyl methylphosphonate (DMMP), a nerve agent simulant. The electrical conductance of a heated nanobelt increased for 5% upon exposure to 78 parts per billion DMMP in air. The nanobelt conductance recovered fully quickly after the DMMP was shut off, suggesting that the single-crystal nanobelt was not subject to poisoning often observed in polycrystalline metal oxide sensors. While the sensitivity can be improved via doping nanobelts with catalytic additives, directed assembly or growth of nanobelts on microsystems will potentially allow for the large-scale fabrication of nanosensor arrays.

A nanofluid is a fluid containing suspended solid particles, with sizes on the order of nanometers. Normally, nanofluids have higher thermal conductivities than their base fluids. Therefore, it is of interest to predict the effective thermal conductivity of such a nanofluid under different conditions, especially since only limited experimental data are available. We have developed a technique to compute the effective thermal conductivity of a nanofluid using Brownian dynamics simulation, which has the advantage of being computationally less expensive than molecular dynamics, and have coupled that with the equilibrium Green–Kubo method. By comparing the results of our calculation with the available experimental data, we show that our technique predicts the thermal conductivity of nanofluids to a good level of accuracy.