Detecting and Quantifying Geometric Features in Large Series of Cluster Structures
Detecting and Quantifying Geometric Features in Large Series of Cluster Structures
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DOI：
10.1515/zpch-2015-0743
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发表时间：
2016-05-01
影响因子：
2.5
通讯作者：
Lorenz, Tommy
中科院分区：
文献类型：
--
作者：
Joswig, Jan-Ole;Lorenz, Tommy
检测和量化的几何特征，在大系列的集群结构是本论文的重点。三个所谓的相似性函数，已经提出了较早的比较和他们的能力指向高度对称的集群。这些函数量化了不同簇结构之间或簇与体结构之间的相似性。作为一个例子，我们已经选择了一个连续系列的Lennard Jones集团结构与350至1000个原子。这些系统的相似性功能相比，其他描述的相对稳定性，集群的形状和壳建筑，被发现是非常有用和可靠的。
Detecting and quantifying geometric features in large series of cluster structures is in the focus of the present paper. Three so-called similarity functions that have been presented earlier are compared and their ability to point to highly symmetric clusters is shown. These functions quantify the similarity between different cluster structures or between a cluster and bulk structures. As an example, we have chosen a continuous series of Lennard Jones cluster structures with 350 to 1000 atoms. The similarity functions of these systems are compared to other descriptions of relative stability, cluster shape and shell building and are found to be very useful and reliable.