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physics.chem-ph2026
Differential Learning for Robust Prediction of Thermal Stability with Application to Energetic Materials
Megan C. Davis, R. Seaton Ullberg, Jeremy N. Schroeder +5
Predicting thermal stability during handling and storage is essential for the design of safe and reliable energetic materials. However, experimental measurements vary significantly…
physics.chem-ph2026
Active Learning for Generalizable Detonation Performance Prediction of Energetic Materials
R. Seaton Ullberg, Megan C. Davis, Jeremy N. Schroeder +5
The discovery of new energetic materials is critical for advancing technologies from defense to private industry. However, experimental approaches remain slow and expensive while c…
physics.chem-ph2026
Generative Chemical Language Models for Energetic Materials Discovery
Andrew Salij, R. Seaton Ullberg, Megan C. Davis +5
The discovery of new energetic materials remains a pressing challenge hindered by limited availability of high-quality data. To address this, we have developed generative molecular…