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Author

R. Ullberg

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Preprint Aug 2026

Differential Learning for Robust Prediction of Thermal Stability with Application to Energetic Materials

Predicting thermal stability during handling and storage is essential for the design of safe and reliable energetic materials. However, experimental measurements vary significantly across laboratories due to differences in protocols and analysis methods, making it difficult to train reliable predictive models. We addre...

M. Davis, R. Ullberg, J. Schroeder et al. · 0 citations
Jul 2026

Data-Driven Material Design: Harnessing High-Throughput Simulations and AI

This work will present the current work on inverse material design, where AI methods—particularly generative pretrained transformers—are used to predict new material candidates based on desired properties, pushing the boundaries of materials innovation.

I. Gonzales, R. Ullberg, Andrew H Salij et al. · 0 citations

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