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◆ Chemical Reviews2025-11-03· Transformative learning

A Computational Renaissance in High-Energy Density Materials (HEDMs) Research

Haixiang Gao, Jane S. Murray, Jean’ne M. Shreeve

原始摘要(英文原文)· Original abstract
This review chronicles rapid advances in computational approaches in high-energy-density materials (HEDMs), which display a tradeoff between performance and safety that poses challenges from molecular to system levels. We illustrate the transformative fusion of predictive theory and modern experimentation─which is driving the transition of HEDM science from empirical discovery to data-driven rational design. The analysis begins with the physics-based foundation of the field, illustrating how quantum chemistry and multiscale dynamics provide insight into stability and emergent behavior from an energetic perspective. At the heart of our analysis lies the iterative feedback loop between simulation and experimental validation, a core element of this emerging paradigm. The review ultimately frames the critical questions and opportunities that will define the future of the field, as we move toward a new generation of HEDMs that are potentially safer, more sustainable, and higher-performing energetic materials.
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A Computational Renaissance in High-Energy Density Materials (HEDMs) Research — 科研速览 Science Skim