Npj Comput. Mater.: 拓扑图形序参量
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原子结构-性质关系构成了现代材料科学的基础，是新材料发现和优化现有系统的重要基础，准确描述这个关系对于晶体结构的预测、复杂缺陷网络的动态演化以及原子相互作用势的构建等至关重要，其中的关键是结合序参量或类似的数学量，用高效且具有物理意义的方法去表征材料中的原子排列。然而，这些表征通常不是那么简单的，特别是针对基本对称性难以确定的原子无序系统。近几十年来，有许多数学、物理方法被用于复杂原子结构的表征，但都存在一定的问题。
A graph-based order parameter, based on the topology of the graph itself, is introduced for the characterization of atomistic structures. The order parameter is universal to any material/chemical system and is transferable to all structural geometries. Four sets of data are used to validate both the generalizability and accuracy of the algorithm: (1) liquid lithium configurations spanning up to 300 GPa, (2) condensed phases of carbon along with nanotubes and buckyballs at ambient and high temperature, (3) a diverse set of aluminum configurations including surfaces, compressed and expanded lattices, point defects, grain boundaries, liquids, nanoparticles, all at nonzero temperatures, and (4) eleven niobium oxide crystal phases generated with ab initio molecular dynamics. We compare our proposed method to existing, state-of-the-art methods for the cases of aluminum and niobium oxide. Our order parameter uniquely classifies every configuration and outperforms all studied existing methods, opening the door for its use in a multitude of complex application spaces that can require fine structure-level characterization of atomistic graphs.
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