Melting of crystalline material is a common physical phenomenon,yet it remains elusive owing to the diversity in physical pictures.In this work,we proposed a deep learning architecture to learn the physical states(sol...Melting of crystalline material is a common physical phenomenon,yet it remains elusive owing to the diversity in physical pictures.In this work,we proposed a deep learning architecture to learn the physical states(solid-or liquidphase)from the atomic trajectories of the bulk crystalline materials with four typical lattice types.The method has ultrahigh accuracy(higher than 95%)for the classification of solid-liquid atoms during the phase transition process and is almost insensitive to temperature.The atomic physical states are identified from atomic behaviors without considering any characteristic threshold parameter,which yet is necessary for the classical methods.The phase transition of bulk crystalline materials can be correctly predicted by learning from the atomic behaviors of different materials,which confirms the close correlation between atomic behaviors and atomic physical states.These evidences forecast that there should be a more general undiscovered physical quantity implicated in the atomic behaviors and elucidate the nature of bulk crystalline melting.展开更多
基金Project supported by the China Postdoctoral Science Foundation(Grant No.2019M663935XB)the Natural Science Foundation of Shaanxi Province,China(Grant No.2019JQ-261)the National Natural Science Foundation of China(Grant Nos.11802225 and 51878548)
文摘Melting of crystalline material is a common physical phenomenon,yet it remains elusive owing to the diversity in physical pictures.In this work,we proposed a deep learning architecture to learn the physical states(solid-or liquidphase)from the atomic trajectories of the bulk crystalline materials with four typical lattice types.The method has ultrahigh accuracy(higher than 95%)for the classification of solid-liquid atoms during the phase transition process and is almost insensitive to temperature.The atomic physical states are identified from atomic behaviors without considering any characteristic threshold parameter,which yet is necessary for the classical methods.The phase transition of bulk crystalline materials can be correctly predicted by learning from the atomic behaviors of different materials,which confirms the close correlation between atomic behaviors and atomic physical states.These evidences forecast that there should be a more general undiscovered physical quantity implicated in the atomic behaviors and elucidate the nature of bulk crystalline melting.
