Influence of ambient temperature and structural parameters on thermal conductivity of carbon nanotube arrays after secondary segmentation

Abstract

Vertically arranged carbon nanotube (CNT) arrays have good flexibility, elasticity, and thermal conductivity. As a new type of thermal interface materials (TIMs), it is increasingly used in heat conduction applications. The thermal conductivity of CNT arrays is an order of magnitude higher than that of traditional silicone oil and solid-state interface composites. However, their thermal properties are susceptible to the ambient temperature and internal structural parameters, and the underlying influence mechanism remains unclear. This lack of understanding hinders the design and application of CNT arrays in practical settings. Therefore, a secondary segmentation method was proposed to establish the structural model of CNT microcolumn arrays. Then, the thermal properties of the array material were simulated, and the influence of different environmental temperatures and structural parameters on thermal properties were analyzed. Simultaneously, the dynamic thermal conductivity of the CNT array was explored by thermal cyclic loading. Simulation results indicate that the increase of structural parameters have a positive effect on the thermal conductivity of the array at different ambient temperatures, but the low temperature environment is more conducive to the improvement. Furthermore, the influence of different array densities predicted by the model on thermal properties is consistent with the corresponding experimental results, which illustrates the feasibility of the segmentation method of the model and provides a new theoretical method for studying the thermal properties of CNT arrays.