Issue 3, 2015

Pool-BCGA: a parallelised generation-free genetic algorithm for the ab initio global optimisation of nanoalloy clusters

Abstract

The Birmingham cluster genetic algorithm is a package that performs global optimisations for homo- and bimetallic clusters based on either first principles methods or empirical potentials. Here, we present a new parallel implementation of the code which employs a pool strategy in order to eliminate sequential steps and significantly improve performance. The new approach meets all requirements of an evolutionary algorithm and contains the main features of the previous implementation. The performance of the pool genetic algorithm is tested using the Gupta potential for the global optimisation of the Au10Pd10 cluster, which demonstrates the high efficiency of the method. The new implementation is also used for the global optimisation of the Au10 and Au20 clusters directly at the density functional theory level.

Graphical abstract: Pool-BCGA: a parallelised generation-free genetic algorithm for the ab initio global optimisation of nanoalloy clusters

Article information

Article type
Paper
Submitted
25 Sep 2014
Accepted
01 Dec 2014
First published
01 Dec 2014
This article is Open Access
Creative Commons BY license

Phys. Chem. Chem. Phys., 2015,17, 2104-2112

Author version available

Pool-BCGA: a parallelised generation-free genetic algorithm for the ab initio global optimisation of nanoalloy clusters

A. Shayeghi, D. Götz, J. B. A. Davis, R. Schäfer and R. L. Johnston, Phys. Chem. Chem. Phys., 2015, 17, 2104 DOI: 10.1039/C4CP04323E

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