Sanggyu Chong1, Tong Jiang2, Michelangelo Domina1

  • 1Laboratory of Computational Science and Modeling, Institute of Materials, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.

PubMed
概括

机器学习的原子间潜力 (MLIP) 隐含地学习能量贡献. 这项研究揭示了MLIPs发展自己的身体秩序趋势,影响准确性和可概括性.

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