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Updated: Sep 19, 2025

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization
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数据集在机器学习原子间潜能算法之间的可转移性

Samuel P Niblett1, Panagiotis Kourtis2, Ioan-Bogdan Magdău2

  • 1Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K.

Journal of chemical theory and computation
|June 5, 2025
PubMed
概括

在机器学习模型之间传输训练数据加速了基础机器学习原子间潜力 (FMLIP) 的发展. 虽然人为设计的数据集传输很好,但自动生成的数据集没有,这突显了需要系统特定数据来进行准确的分子模拟的需要.

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