(451d) A Comprehensive Study of Thermal Conductivities of Aligned Single-and Multi-Walled Carbon Nanotube Nanocomposites Considering Carbon Nonotube Morphology Effects

To date, effects of complex morphology of carbon nanotube (CNT) arrays on the effective thermal conductivities of the CNT-nanocomposites is still unknown both experimentally and through analysis. Real morphological features such as CNT spatial agglomeration, waviness, and inter-CNT contact in a bundle and/or with a high CNT volume fraction need to be considered. An off-Lattice Monte-Carlo simulation method using a random walk algorithm, which is faster than molecular dynamics and finite element methods, was successfully developed to investigate comprehensively the thermal conductivities and the non-isotropic heat conduction of aligned single- and multi-walled carbon nanotube (CNT) nanocomposites having CNTs parallel and perpendicular to the heat flux. The developed model also takes into account several essential CNT morphology effects on heat conduction of the CNT nanocomposites such as different CNT orientations, size and type (single vs. multi-wall), volume fraction (1-20vol%), the CNT-matrix and CNT-CNT thermal boundary resistances, and inter-CNT contact degree (0-100%) and the CNT distribution. It is found that when the CNT?CNT thermal contact is taken into account, the maximum effective thermal conductivity of the nanocomposites having their CNTs parallel to the heat flux decreases by ∼4 times and ∼2 times for the single-walled and the multi-walled CNTs, respectively, at 20% CNT volume fraction. The simulation results also show the role of CNT-CNT contact significantly affects the effective transport properties including anisotropy ratios. With better CNT-CNT contact, the heat transport through the CNT-CNT is more important than through the CNT-matrix-CNT. The successfully developed models have being applied for predicting the thermal conductivity within a wide range of CNT volume fractions and thermal boundary resistance between the CNTs and idealized biological fluids, suspensions, polymers and solid materials, possibly even metals This computational work can be a useful tool for the experimental workers judging fabrication techniques and materials selection.

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