DPA-2: a large atomic model as a multi-task learner

The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demonstrated the capability to conduct large-scale, long-duration simulations with the accuracy of ab initio electronic stru...

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Veröffentlicht in:	arXiv.org 2024-08
Hauptverfasser:	Zhang, Duo, Liu, Xinzijian, Zhang, Xiangyu, Zhang, Chengqian, Cai, Chun, Bi, Hangrui, Du, Yiming, Qin, Xuejian, Peng, Anyang, Huang, Jiameng, Bowen, Li, Shan, Yifan, Zeng, Jinzhe, Zhang, Yuzhi, Liu, Siyuan, Li, Yifan, Chang, Junhan, Wang, Xinyan, Zhou, Shuo, Liu, Jianchuan, Luo, Xiaoshan, Wang, Zhenyu, Jiang, Wanrun, Wu, Jing, Yang, Yudi, Yang, Jiyuan, Yang, Manyi, Fu-Qiang, Gong, Zhang, Linshuang, Shi, Mengchao, Fu-Zhi Dai, York, Darrin M, Liu, Shi, Zhu, Tong, Zhong, Zhicheng, Lv, Jian, Cheng, Jun, Weile Jia, Chen, Mohan, Ke, Guolin, Weinan, E, Zhang, Linfeng, Wang, Han
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Distillation Electron microscopes Electronic structure Industrial applications Modelling Potential energy Simulation
Online-Zugang:	Volltext
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