DeePMD-kit v2: A software package for deep potential models

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material scien...

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Vydané v:	The Journal of chemical physics Ročník 159; číslo 5
Hlavní autori:	Zeng, Jinzhe, Zhang, Duo, Lu, Denghui, Mo, Pinghui, Li, Zeyu, Chen, Yixiao, Rynik, Marián, Huang, Li'ang, Li, Ziyao, Shi, Shaochen, Wang, Yingze, Ye, Haotian, Tuo, Ping, Yang, Jiabin, Ding, Ye, Li, Yifan, Tisi, Davide, Zeng, Qiyu, Bao, Han, Xia, Yu, Huang, Jiameng, Muraoka, Koki, Wang, Yibo, Chang, Junhan, Yuan, Fengbo, Bore, Sigbjørn Løland, Cai, Chun, Lin, Yinnian, Wang, Bo, Xu, Jiayan, Zhu, Jia-Xin, Luo, Chenxing, Zhang, Yuzhi, Goodall, Rhys E A, Liang, Wenshuo, Singh, Anurag Kumar, Yao, Sikai, Zhang, Jingchao, Wentzcovitch, Renata, Han, Jiequn, Liu, Jie, Jia, Weile, York, Darrin M, E, Weinan, Car, Roberto, Zhang, Linfeng, Wang, Han
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 07.08.2023
ISSN:	1089-7690, 1089-7690
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