Nano-Interconnected 1D/2D Boron Nitride Hybrid Networks: Unlocking Superior Thermal Conductivity in Electrically Insulating Thermal Interface Nanocomposites Based on Hybrid Thermal Percolation Model

Abstract

Due to its high thermal and low electrical conductivities, boron nitride (BN) has emerged as an optimal filler for thermal interface materials (TIMs) that prevent thermal condensation of nanostructures without causing shutdown due to electron tunneling. The polymer composite based on the BN hybrid strategy can be considered an optimal option as an electrically insulating and heat-dissipating TIM. However, there is a paucity of systematic experiments and theoretical approaches investigating the optimal content and ratio of BN hybrid fillers, which are key factors in synergistically improving thermal conductivity (TC). In this study, a hybrid thermal percolation model is developed by modifying the Foygel model to investigate the synergistic improvement in systematically measured TC. The model effectively determines the optimal hybrid filler composition and the resultant performance enhancement. Furthermore, the impact of BN surface and interface chemistry is comprehensively analyzed in conjunction with the filler network structure. The highest isotropic TC (10.93 W m(-1)<middle dot>K) is achieved by optimizing the formation of nano-interconnections between the hybrid 1D BN nanotube and 2D hexagonal BN (h-BN), representing a significant improvement of 1582% and 118% over the TC of pure epoxy and the composite containing the optimized h-BN network, respectively.