Thermal Transport of AlN/Graphene/3C-SiC Typical Heterostructures with Different Crystallinities of Graphene

Enhancement of Mechanical Properties of High-Thermal-Conductivity Composites Comprising Boron Nitride and Poly(methyl methacrylate) Resin through Material Design Utilizing Hansen Solubility Parameters

Materials for heat sinks in automotive heat dissipation systems must demonstrate both high thermal conductivity and stress resistance during assembly. This research proposes a composite material, comprised of thermally conductive ceramic fillers and matrix resins, as a suitable option for such application. The strategy for designing this material interface is directed with Hansen solubility parameters (HSP). A composite material featuring a honeycomb-like structure made of poly(methyl methacrylate) (PMMA) and boron nitride (BN) particles was successfully fabricated through press molding. This yielded a continuous BN network exhibiting high thermal conductivity and moderate mechanical strength. The HSP evaluation led to the suggestion of introducing highly polar functional groups into the matrix resin to enhance the affinity between PMMA resin and BN fillers. In line with this recommendation, a nitrile (CN) group─a highly polar group─was introduced to PMMA (CN-PMMA), significantly enhancing the composite's maximum bending stress without noticeably degrading other properties. Surface HSP evaluation through contact angle measurements revealed an "interface enrichment effect", with the CN groups concentrating at the resin-filler interface and effectively interacting with the surface functional groups on the BN particles, which resulted in an increase in the maximum bending stress. These findings emphasize the advantage of employing HSP methodologies in designing high-performance composite materials.

Prediction and Control of Thermal Transport at Defective State Gr/h-BN Heterojunction Interfaces

The control of interfacial thermal conductivity is the key to two-dimensional heterojunction in semiconductor devices. In this paper, by using non-equilibrium molecular dynamics (NEMD) simulations, we analyze the regulation of interfacial thermal energy transport in graphene (Gr)/hexagonal boron nitride (h-BN) heterojunctions and reveal the variation mechanism of interfacial thermal energy transport. The calculated results show that 2.16% atomic doping can effectively improve interfacial heat transport by more than 15.6%, which is attributed to the enhanced phonon coupling in the mid-frequency region (15-25 THz). The single vacancy in both N and B atoms can significantly reduce the interfacial thermal conductivity (ITC), and the ITC decreases linearly with the increase in vacancy defect concentration, mainly due to the single vacancy defects leading to an increased phonon participation rate (PPR) below 0.4 in the low-frequency region (0-13 THz), which shows the phonon the localization feature, which hinders the interfacial heat transport. Finally, a BP neural network algorithm is constructed using machine learning to achieve fast prediction of the ITC of Gr/h-BN two-dimensional heterogeneous structures, and the results show that the prediction error of the model is less than 2%, and the method will provide guidance and reference for the design and optimization of the ITC of more complex defect-state heterogeneous structures.