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Issue 42, 2015
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Quasi-combinatorial energy landscapes for nanoalloy structure optimisation

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Abstract

We formulate nanoalloy structure prediction as a mixed-variable optimisation problem, where the homotops can be associated with an effective, quasi-combinatorial energy landscape in permutation space. We survey this effective landscape for a representative set of binary systems modelled by the Gupta potential. In segregating systems with small lattice mismatch, we find that homotops have a relatively straightforward landscape with few local optima – a scenario well-suited for local (combinatorial) optimisation techniques that scale quadratically with system size. Combining these techniques with multiple local-neighbourhood structures yields a search for multiminima, and we demonstrate that generalised basin-hopping with a metropolis acceptance criterion in the space of multiminima can then be effective for global optimisation of binary and ternary nanoalloys.

Graphical abstract: Quasi-combinatorial energy landscapes for nanoalloy structure optimisation

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Publication details

The article was received on 28 Feb 2015, accepted on 08 May 2015 and first published on 08 May 2015


Article type: Paper
DOI: 10.1039/C5CP01198A
Citation: Phys. Chem. Chem. Phys., 2015,17, 28331-28338
  • Open access: Creative Commons BY license
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    Quasi-combinatorial energy landscapes for nanoalloy structure optimisation

    D. Schebarchov and D. J. Wales, Phys. Chem. Chem. Phys., 2015, 17, 28331
    DOI: 10.1039/C5CP01198A

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