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通过使用神经网络潜能,从具有替代性障碍的扩展固体中的分子动力学模拟中直接导出异型原子位移参数

¹Department of Energy and Environment, National Institute of Advanced Industrial Science and Technology (AIST), 1-8-31, Midorigaoka, Ikeda, Osaka 563-8577, Japan.

Acta crystallographica. Section A, Foundations and advances

|June 13, 2025

概括

分子动力学模拟现在可以直接计算晶体的异构原子位移参数 (ADP). 这种方法提供了对原子分布的见解,特别是在有限的温度和无序的情况下,补充了实验晶体学.

科学领域:

晶体学和材料科学材料科学
计算材料科学科学计算材料科学
固态物理固态物理

背景情况:

原子位移参数 (ADP) 描述了晶体中晶格位点周围的原子分布.
像格子动力学这样的传统方法有局限性,特别是在无序或有限温度系统中.
准确的ADP对于理解晶体结构和材料特性至关重要.

研究的目的:

从古典分子动力学 (MD) 模拟中直接导出异型原子位移参数 (ADP).
通过使用通用机器学习潜力来计算ADPs的新型计算方法.
探索MD衍生ADPs对各种晶体材料的适用性,包括那些有障碍的材料.

主要方法:

利用具有通用机器学习潜力的经典分子动力学 (MD) 模拟.
在各种时间步骤中提取原子位置数据,以确定 (共价) 和原子分布.
该方法应用于扩展的固体:MgO,Ag8SnSe6,Na2In2Sn4和BaCu1.14In0.86P2.2.

主要成果:

直接从MD模拟中成功推导出异构型原子位移参数 (ADP).
证明了该方法处理具有替代失调和有限温度的晶体的能力.
观察到计算的ADP在绝对零温度时接近零,并且与波电位中的温度成比例,从而可以估计零点运动.

结论:

分子动力学模拟为计算ADPs提供了对格子动力学的可行替代方案.
由MD衍生的ADP可以提供有关原子分布的宝贵见解,特别是在复杂或无序系统中.
这种计算方法作为结构确定实验晶体学的一个补充工具.

关键词:

更多关于 ADPs 的文章不同类型的原子位移参数.分子动力学模拟,分子动力学模拟神经网络的潜力神经网络的潜力热电材料是一种热电材料.

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