Granular Jamming and Thermal Modeling in Faceted Particle Packings

Thermally conductive polymer composites, particularly those that include graphitic filler particles, are promising candidates for thermal management in electronic devices. The effective thermal properties of these composites are a function of the morphology, intrinsic thermal properties of the filler particles, and the interparticle contact network. For instance, anisotropic thermal conductivity within the graphitic flakes may be exploited to fabricate composites with bulk anisotropic thermal conductivity through preferential alignment of the flakes. Previously, we experimentally characterized the effective thermal conductivity of graphite-flake epoxy composites using infrared (IR) microscopy and observed a 16-fold enhancement in the effective thermal conductivity of graphite-flake epoxy composite relative to neat epoxy. In this paper, we use discrete element simulations of granular mechanics to evaluate the effect of external mechanical stresses on the microstructural anisotropy of packings of hexagonal platelet particles, characterized by a fabric tensor. We investigate the bulk thermal conductivity anisotropy through a random network model. Applying pressure and shear emulates the forces acting on particles during processing (e.g., shear induced by a doctor blade and normal forces exerted during compaction). We hypothesize that the critical filler volume fraction for percolation is governed by particle aspect ratio.