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Updated: Jun 29, 2025

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
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Published on: April 12, 2019

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机器学习的Kohn-Sham哈密尔顿绘图用于非adiabatic分子动力学

Mohammad Shakiba1, Alexey V Akimov1

  • 1Department of Chemistry, University at Buffalo, The State University of New York, Buffalo, New York 14260, United States.

Journal of chemical theory and computation
|April 6, 2024
PubMed
概括

我们开发了一种机器学习方法,快速绘制大型原子系统的电子哈密尔顿数. 这种方法加速了数量级的计算,同时保持了动态模拟的高精度.

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