Detecting and Quantifying Geometric Features in Large Series of Cluster Structures

被引：6

作者：

Joswig, Jan-Ole ^{[1
]}

Lorenz, Tommy ^{[1
]}

机构：

[1] Tech Univ Dresden, Theoret Chem, D-01062 Dresden, Germany

来源：

ZEITSCHRIFT FUR PHYSIKALISCHE CHEMIE-INTERNATIONAL JOURNAL OF RESEARCH IN PHYSICAL CHEMISTRY & CHEMICAL PHYSICS | 2016年 / 230卷 / 5-7期

关键词：

Similarity Functions; GLOBAL OPTIMIZATION; GENETIC ALGORITHM;

D O I：

10.1515/zpch-2015-0743

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

摘要：

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.

引用

页码：1057 / 1066

页数：10

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