An unbiased population-based search for the geometry optimization of Lennard–Jones clusters: 2 ≤ N ≤ 372

Authors

  • Wayne Pullan

    Corresponding author
    1. School of Information and Communication Technology, Griffith University, Gold Coast, Qld., 4215, Australia
    • School of Information and Communication Technology, Griffith University, Gold Coast, Qld., 4215, Australia
    Search for more papers by this author

Abstract

This article presents the results obtained using an unbiased Population Based Search (PBS) for optimizing Lennard–Jones clusters. PBS is able to repeatedly obtain all putative global minima, for Lennard–Jones clusters in the range 2 ≤ N ≤ 372, as reported in the Cambridge Cluster Database. The PBS algorithm incorporates and extends key techniques that have been developed in other Lennard–Jones optimization algorithms over the last decade. Of particular importance are the use of cut-and-paste operators, structure niching (using the cluster strain energy as a metric), two-phase local search, and a new operator, Directed Optimization, which extends the previous concept of directed mutation. In addition, PBS is able to operate in a parallel mode for optimizing larger clusters. © 2005 Wiley Periodicals, Inc. J Comput Chem 26: 899–906, 2005

Ancillary