Issue 33, 2015

The Birmingham parallel genetic algorithm and its application to the direct DFT global optimisation of IrN (N = 10–20) clusters

Abstract

A new open-source parallel genetic algorithm, the Birmingham parallel genetic algorithm, is introduced for the direct density functional theory global optimisation of metallic nanoparticles. The program utilises a pool genetic algorithm methodology for the efficient use of massively parallel computational resources. The scaling capability of the Birmingham parallel genetic algorithm is demonstrated through its application to the global optimisation of iridium clusters with 10 to 20 atoms, a catalytically important system with interesting size-specific effects. This is the first study of its type on Iridium clusters of this size and the parallel algorithm is shown to be capable of scaling beyond previous size restrictions and accurately characterising the structures of these larger system sizes. By globally optimising the system directly at the density functional level of theory, the code captures the cubic structures commonly found in sub-nanometre sized Ir clusters.

Graphical abstract: The Birmingham parallel genetic algorithm and its application to the direct DFT global optimisation of IrN (N = 10–20) clusters

Supplementary files

Article information

Article type
Paper
Submitted
08 Jun 2015
Accepted
17 Jul 2015
First published
22 Jul 2015
This article is Open Access
Creative Commons BY license

Nanoscale, 2015,7, 14032-14038

The Birmingham parallel genetic algorithm and its application to the direct DFT global optimisation of IrN (N = 10–20) clusters

J. B. A. Davis, A. Shayeghi, S. L. Horswell and R. L. Johnston, Nanoscale, 2015, 7, 14032 DOI: 10.1039/C5NR03774C

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