1 citations · 1 across the 3 of their papers we have counts for
3 papers
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…
Multi-Task Multi-Fidelity Learning of Properties for Energetic Materials
Robert J. Appleton, Daniel Klinger, Brian H. Lee +6
Data science and artificial intelligence are playing an increasingly important role in the physical sciences. Unfortunately, in the field of energetic materials data scarcity limit…
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…