Comprehensive genetic algorithm for ab initio global optimisation of clusters. Issue 10 (2nd July 2016)

• Record Type: Journal Article
• Authors: Zhao, Jijun; Shi, Ruili; Sai, Linwei; Huang, Xiaoming; Su, Yan
• Is Part Of: Molecular simulation. Volume 42:Issue 10(2016)
• Page Start: 809
• Page End: 819
• Publication Date: 2016-07-02
• Subjects: Cluster -- global optimisation -- genetic algorithm -- structure; Molecular dynamics -- Computer simulation -- Periodicals; Statistical mechanics -- Computer simulation -- Periodicals; 539.6
• DOI: 10.1080/08927022.2015.1121386
• Languages: English
• ISSNs: 0892-7022

Abstract

Abstract: Cluster, as the aggregate of a few to thousands of atoms or molecules, bridges the microscopic world of atoms and molecules and the macroscopic world of condensed matters. The physical and chemical properties of a cluster are determined by its ground state structure, which is significantly different from its bulk structure and sensitively relies on the cluster size. As a well-known nondeterministic polynomial-time hard problem, determining the ground state structure of a cluster is a challenging task due to the extreme complexity of high-dimensional potential energy surface (PES). Genetic algorithm (GA) is an efficient global optimisation method to explore the PES of clusters. Recently, we have developed a GA-based programme, namely comprehensive genetic algorithm (CGA), and incorporated it with ab initio calculations. Using this programme, the lowest energy structures of a variety of elemental and compound clusters with different types of chemical bonding have been determined, and their physical properties have been investigated and compared with experimental data. In this article, we will describe the technique details of CGA programme and present an overview of its successful applications.