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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…
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…
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…