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An efficient genetic algorithm for structure prediction at the nanoscale

Lazauskas, T; Sokol, AA; Woodley, SM; (2017) An efficient genetic algorithm for structure prediction at the nanoscale. Nanoscale , 9 (11) pp. 3850-3864. 10.1039/c6nr09072a. Green open access

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Abstract

We have developed and implemented a new global optimization technique based on a Lamarckian genetic algorithm with the focus on structure diversity. The key process in the efficient search on a given complex energy landscape proves to be the removal of duplicates that is achieved using a topological analysis of candidate structures. The careful geometrical prescreening of newly formed structures and the introduction of new mutation move classes improve the rate of success further. The power of the developed technique, implemented in the Knowledge Led Master Code, or KLMC, is demonstrated by its ability to locate and explore a challenging double funnel landscape of a Lennard-Jones 38 atom system (LJ38). We apply the redeveloped KLMC to investigate three chemically different systems: ionic semiconductor (ZnO)1–32, metallic Ni13 and covalently bonded C60. All four systems have been systematically explored on the energy landscape defined using interatomic potentials. The new developments allowed us to successfully locate the double funnels of LJ38, find new local and global minima for ZnO clusters, extensively explore the Ni13 and C60 (the buckminsterfullerene, or buckyball) potential energy surfaces.

Type: Article
Title: An efficient genetic algorithm for structure prediction at the nanoscale
Open access status: An open access version is available from UCL Discovery
DOI: 10.1039/c6nr09072a
Publisher version: https://dx.doi.org/10.1039/C6NR09072A
Language: English
Additional information: This article is licensed under a Creative Commons Attribution 3.0 Unported Licence (http://creativecommons.org/licenses/by/3.0/).
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Chemistry
URI: https://discovery.ucl.ac.uk/id/eprint/1546001
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