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cond-mat.mtrl-sci2026
Ab initio-based Deep-Learning Prediction of Carrier Mobility in Strongly Anharmonic Materials
Juan Zhang, Boheng Zhao, Yang Li +4
Predicting charge transport in strongly anharmonic materials, particularly ultralow thermal conductors, remains a major challenge for first-principles methods. In such systems, per…
cond-mat.mtrl-sci2026
DeepH-pack: A general-purpose neural network package for deep-learning electronic structure calculations
Yang Li, Yanzhen Wang, Boheng Zhao +15
In computational physics and materials science, first-principles methods, particularly density functional theory, have become central tools for electronic structure prediction and…