3D X-Ray Tomography-Driven Descriptor Framework for Predicting Thermal Conductivity of Polymer Composites.

ABSTRACT: Polymer composites filled with ceramic particles are widely studied as thermal interface materials (TIMs), yet thermal conductivity gains do not scale linearly with filler loading. Experimental inconsistencies suggest hidden structural factors governing heat transport. Here, 3D X-ray tomography is combined with quantitative morphometry to identify descriptors that control conduction in alumina-polydimethylsiloxane (PDMS) composites. Five composites with varying filler loadings (60-82.5 vol%) and four alumina size fractions (90, 20, 3, and 0.6 µm)-including one Bayesian-optimized formulation-are reconstructed to visualize particle networks and polymer domains. Local thickness analysis revealed how thin polymer ligaments enable continuous pathways, while tortuosity (τ) mapping showed how clu

SUBMITTER: An H 

PROVIDER: S-EPMC12716219 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature