Classification of atomic environments via the Gromov–Wasserstein distance
Classification of atomic environments via the Gromov–Wasserstein distance
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DOI：
10.1016/j.commatsci.2020.110144
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发表时间：
2020-11
影响因子：
3.3
通讯作者：
Sakura Kawano;J. Mason
中科院分区：
文献类型：
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作者：
Sakura Kawano;J. Mason
解释分子动力学模拟通常涉及对局部原子环境的自动分类，以确定感兴趣的区域。现有的方法通常仅限于少数参考结构，并且只包括有关当地化学成分的有限信息。这项工作建议使用Gromov-Wasserstein （GW）距离的一种变体，以一种对原子位移、缺失原子和化学成分差异敏感的方式，量化局部原子环境和一组任意参考环境之间的差异。这涉及到将局部原子环境描述为有限的度量度量空间，这样做还有一个额外的优点，即不要求局部环境以原子为中心，也不需要对材料类做出任何假设。数值算例说明了该算法的有效性和通用性。
Interpreting molecular dynamics simulations usually involves automated classification of local atomic environments to identify regions of interest. Existing approaches are generally limited to a small number of reference structures and only include limited information about the local chemical composition. This work proposes to use a variant of the Gromov–Wasserstein (GW) distance to quantify the difference between a local atomic environment and a set of arbitrary reference environments in a way that is sensitive to atomic displacements, missing atoms, and differences in chemical composition. This involves describing a local atomic environment as a finite metric measure space, which has the additional advantages of not requiring the local environment to be centered on an atom and of not making any assumptions about the material class. Numerical examples illustrate the efficacy and versatility of the algorithm.