撞车
计算机科学
力场(虚构)
纳米技术
工程类
人工智能
材料科学
程序设计语言
作者
Igor Poltavsky,Anton Charkin-Gorbulin,Mirela Puleva,Grégory Fonseca,Ilyes Batatia,Nicholas J. Browning,Stefan Chmiela,Mengnan Cui,J. Thorben Frank,Stefan Heinen,Bing Huang,Silvan Käser,Adil Kabylda,Danish Khan,Carolin Müller,Alastair J. A. Price,Kai Riedmiller,Kai Töpfer,Tsz Wai Ko,Markus Meuwly
出处
期刊:Chemical Science
[The Royal Society of Chemistry]
日期:2025-01-01
卷期号:16 (8): 3720-3737
被引量:8
摘要
Assessing the performance of modern machine learning force fields across diverse chemical systems to identify their strengths and limitations within the TEA Challenge 2023.
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