active learning 1atomic environment extraction 1density functional theory 1machine learning interatomic potentials 1molecular dynamics 1
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cond-mat.mtrl-sci2026
Extracting Atomic Environments for Machine Learning Interatomic Potentials
Jared C. Stimac, Fei Zhou, Kyle Bushick +4
The paper benchmarks methods for extracting small atomic environments from large-scale simulations to enable DFT calculations for training machine‑learning interatomic potentials,…
cond-mat.mtrl-sci2024
Electron mobility of SnO2 from first principles
Amanda Wang, Kyle Bushick, Nick Pant +6
The transparent conducting oxide SnO2 is a wide bandgap semiconductor that is easily n-type doped and widely used in various electronic and optoelectronic applications. Experimenta…