Uncovering the thermal conductivity of graphene nanoplatelet composites with interlayers using a Monte Carlo model

Abstract

Abstract This paper uses a Monte Carlo method to study the thermal conductivity of graphene nanoplatelet (GNP) composites. Firstly, a large number of GNPs are randomly set in a representative volume element. Then, based on a temperature satisfying the Laplace equation in a matrix, a coated surface (CS) is set up on each GNP surface, and the temperature of the CS and GNP can be obtained by the walk-on-spheres (WoS) method. Finally, the WoS method continues to be applied to calculate the heat flux density of the composite materials, further obtaining the thermal conductivity of the composites. We add the influence of interlayers in random walks. We incorporate the influence of interlayers in the WoS process, and the points that walk onto the interlayer surface have a very low probability of reaching the GNP due to the extremely low thermal conductivity of the interlayer. The calculated results are consistent with the experimental data. The model also studies the effects of the size, orientation, and aggregation of GNPs on the thermal conductivity of composite materials.