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cond-mat.mtrl-sci2025
Harnessing Machine Learning for Quantum-Accurate Predictions of Non-Equilibrium Behavior in 2D Materials
Yue Zhang, Robert J. Appleton, Kui Lin +5
Accurately predicting the non-equilibrium mechanical properties of two-dimensional (2D) materials is essential for understanding their deformation, thermo-mechanical properties, an…
cond-mat.mtrl-sci2023★ 1 cited
Mapping microstructure to shock-induced temperature fields using deep learning
Chunyu Li, Juan Carlos Verduzco, Brian H. Lee +2
The response of materials to dynamical, or shock, loading is important to planetary science, aerospace engineering, and energetic materials. Thermal-activated processes, including…