时刻张量潜力和等价张量网络潜力,具有明确的分散相互作用
Olga Chalykh1, Dmitry Korogod1,2, Ivan S Novikov1,2,3,4
1Skolkovo Institute of Science and Technology, Skolkovo Innovation Center, Bolshoy Boulevard 30, Moscow 143026, Russian Federation.
The Journal of chemical physics
|October 2, 2025
概括
显式分散相互作用 (D2 / D3 校正) 显著增强机器学习液体建模的原子间潜力 (MLIP). D2校正提供了与D3相似的准确性,而计算成本较低.
科学领域:
- 计算化学的计算化学
- 材料科学 材料科学 材料科学
- 机器学习 机器学习
背景情况:
- 机器学习原子间潜力 (MLIP) 对于模拟分子系统至关重要.
- 准确的建模需要捕捉各种原子间力,包括分散相互作用.
研究的目的:
- 评估显式分散校正 (D2,D3) 对MLIP精度的影响.
- 评估液态四化碳,甲和的MLIP性能.
- 为了比较D2和D3校正和不同切断半径的有效性.
主要方法:
- 将D2和D3分散校正纳入动量张量潜力和等价张量网络潜力.
- 基准测量MLIP准确度与初始二元结合曲线的比较.
- 使用实验密度和辐射分布函数进行验证.
主要成果:
- 显式分散校正显著提高了MLIP的准确性,特别是在标准切断半径 (5-6 Å) 上.
- 将切断半径延长到7.5 Å进一步提高了四化碳和甲的准确性.
- D2 校正提供了与 D3 校正相当的准确性,但计算成本降低.
- 准确的托鲁建模需要明确的分散合并.
结论:
- 明确的分散相互作用对于精确的分子液体MLIP至关重要.
- D2校正为D3提供了一个计算效率高的替代方案,以实现高精度.
- 带有分散校正的MLIP显示出与理论和实验数据的良好一致.
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