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Issue 33, 2015
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The Birmingham parallel genetic algorithm and its application to the direct DFT global optimisation of IrN (N = 10–20) clusters

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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

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Publication details

The article was received on 08 Jun 2015, accepted on 17 Jul 2015 and first published on 22 Jul 2015


Article type: Paper
DOI: 10.1039/C5NR03774C
Nanoscale, 2015,7, 14032-14038
  • Open access: Creative Commons BY license
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    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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