Accessible Unlicensed Requires Authentication Published by Oldenbourg Wissenschaftsverlag March 14, 2016

Detecting and Quantifying Geometric Features in Large Series of Cluster Structures

Jan-Ole Joswig and Tommy Lorenz

Abstract

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.

Acknowledgement

The authors acknowledge financial support by the Deutsche Forschungsgemeinschaft (DFG) for M-era.NET project ICENAP and computational time by the Center for Information Services and High Performance Computing (ZIH) within the project QDSIM. One of the authors (JOJ) is most grateful to Michael Springborg for his friendship, professional support, and enjoyable discussions.

Received: 2015-12-4
Accepted: 2016-2-3
Published Online: 2016-3-14
Published in Print: 2016-5-28

©2016 Walter de Gruyter Berlin/Boston