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A comparative study on local atomic configurations characterized by cluster-type-index method and Voronoi polyhedron method

机译:团簇指数法和Voronoi多面体法表征局部原子构型的比较研究

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摘要

To assess strengths and weaknesses of cluster-type-index method (CTIM) and Voronoi polyhedron method (VPM) in the characterization of local structures, the similarity and difference between CTIM clusters and Voronoi polyhedrons (VPs) in under-cooled liquids and rapidly solidified solids of silvers are analyzed from the configurational view of point. By tracking identification numbers of atoms, it is found that one kind of VPs usually corresponds to several kinds of CTIM clusters with same or higher coordination number of central atoms, and the local structures of fcc lattices and hcp lattices can hardly be distinguished from each other merely based on their Voronoi polyhedron indexes < 0, 12, 0, 0 >. In CTIM, the fcc and hcp basic clusters can be characterized by (12, 12/1421) and (12, 6/1421, 6/1422), respectively, but their total are less than the population of < 0, 12, 0, 0 > VPs in the same simulated system. A careful analysis of VPs with and without refinement reveals that the diminishment of shell atoms associated with tiny Voronoi polygons should be responsible for low coordination numbers of central atoms in VPs relative to their counterparts of CTIM clusters. The CTIM based on Honeycutt-Andersen (H-A) pair analysis can identify more kinds of atomic clusters, but its multi-indexes nature makes the feature extraction from various local atomic configurations more difficult. (C) 2016 Elsevier B.V. All rights reserved.
机译:为了评估簇类型指数法(CTIM)和Voronoi多面体法(VPM)在表征局部结构方面的优缺点,研究了CTIM簇与Voronoi多面体(VP)在过冷液体中并快速凝固之间的相似性和差异。从构型的角度分析了银的固体。通过跟踪原子的识别数,发现一种VP通常对应于具有相同或更高中心原子配位数的几种CTIM簇,并且fcc晶格和hcp晶格的局部结构很难区分。仅基于其Voronoi多面体索引<0、12、0、0>。在CTIM中,fcc和hcp基本群集的特征分别是(12,12/1421)和(12,6/1421,6/1422),但它们的总数小于<0、12、0的总体,0> VP在同一模拟系统中。对带有和不带有细化的VP的仔细分析表明,与微小的Voronoi多边形相关的壳原子的减少应该是VP中中心原子相对于CTIM簇对应物的配位数低的原因。基于Honeycutt-Andersen(H-A)对分析的CTIM可以识别更多种类的原子团簇,但是其多索引性质使得从各种局部原子构型中提取特征更加困难。 (C)2016 Elsevier B.V.保留所有权利。

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