AI for Science期刊第二期文章出版
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文章介绍
Edward Hirst, Tancredi Schettini Gherardini and Alexander G Stapleton
Ardavan Mehdizadeh and Peter Schindler
Focus Issue on Machine Learning Potentials and Mapping of Atomic Structures
TorchSim: an efficient atomistic simulation engine in PyTorch
Orion Cohen, Janosh Riebesell, Rhys Goodall, Adeesh Kolluru, Stefano Falletta, Joseph Krause, Jorge Colindres, Gerbrand Ceder and Abhijeet S Gangan
Graph learning metallic glass discovery from Wikipedia
Kaichen Ouyang, Shiyun Zhang, Song-Ling Liu, Jiachuan Tian, Yuanhao Li, Hua Tong, Hai-Yang Bai, Wei-Hua Wang and Yuan-Chao Hu
Universal machine learning potentials for systems with reduced dimensionality
Giulio Benedini, Antoine Loew, Matti Hellström, Silvana Botti and Miguel A L Marques
Focus Issue on Machine Learning Potentials and Mapping of Atomic Structures
Yang-Hui He, Vishnu Jejjala, Mishra Challenger and Em Sharnoff
Xinyuan Liang, Renxi Liu and Mohan Chen
期刊介绍
- AI for Science是一本跨学科、国际同行评审的钻石开放获取期刊，致力于发表具有重大影响力的原创研究、综述和观点文章，聚焦人工智能（AI）在推动科学创新方面的变革性应用。本刊由IOP出版社和中国科学院东莞材料科学与技术研究所合办。