Discrete element modeling for predicting thermal conductivity in polymer composites with experimental validation

Abstract

In recent years, the increasing power density of electronic devices has led to significant heat generation in power chips and power modules, necessitating the development of materials with enhanced thermal conductivity. Among the various newly developed materials, polymer matrix composites have emerged as promising candidates for addressing thermal management challenges due to their favorable thermal and mechanical properties. However, accurate and efficient numerical modeling of heat transfer behavior in such composite systems remains an ongoing research challenge. In this study, we present a numerical modeling approach based on the Discrete Element Method (DEM) to investigate the thermal behavior of polymer-based composite materials. A benchmark problem is established to validate the accuracy and reliability of the proposed DEM-based thermal model. Simulation results show good agreement with experimental measurements for both pure epoxy resin and epoxy composites filled with thermally conductive particles. The proposed model also provides reliable estimates of the effective thermal conductivity, particularly when realistic particle size heterogeneity is incorporated. Furthermore, our results demonstrate that the particle size distribution plays a critical role in determining the composite’s overall thermal conductivity. Among the tested distributions, the log-normal case yielded the closest agreement with experimental data, as it most accurately reflects the microscale variability found in real composites. These findings highlight the potential of DEM as a powerful tool for simulating and optimizing the thermal performance of composite materials.