Predicting thermal conductivity in energetic materials: A microstructural and elemental approach to phonon transport

Predicting how heat propagates through energetic materials is a cornerstone of industrial safety, yet the complex interplay between chemical identity and physical microstructure remains difficult to quantify. A robust predictive framework for thermal conductivity is introduced here, moving beyond simple empirical correlations by integrating molecular descriptors with macroscopic loading density. Analysis of a diverse dataset of 79 compounds demonstrates that thermal transport is governed by a delicate balance between particle connectivity and atomic-scale vibrations.​ A distinct "dual-role" mechanism emerges in the heat transfer process: while increased loading density facilitates phonon pathways by reducing insulating air gaps, specific atomic constituents act as either bridges or barriers to energy flow. Elements such as hydrogen and aluminum enhance conductivity by promoting coherent lattice vibrations, whereas heavier atoms like mercury introduce mass disorder that scatters phonons and reduces the mean free path. Furthermore, the model captures critical density thresholds where microstructural disruptions, such as grain boundary scattering, begin to offset the benefits of tight packing. By providing a mathematically transparent and physically grounded alternative to resource-intensive simulations, this work offers a rapid tool for the preliminary safety screening and intelligent design of next-generation energetic solids.