New developments in evolutionary structure prediction algorithm USPEX

Andriy O. Lyakhov, Artem R. Oganov, Harold T. Stokes, Qiang Zhu

Research output: Contribution to journalArticlepeer-review

768 Citations (Scopus)

Abstract

We present new developments of the evolutionary algorithm USPEX for crystal structure prediction and its adaptation to cluster structure prediction. We show how to generate randomly symmetric structures, and how to introduce 'smart' variation operators, learning about preferable local environments. These and other developments substantially improve the efficiency of the algorithm and allow reliable prediction of structures with up to ∼200 atoms in the unit cell. We show that an advanced version of the Particle Swarm Optimization (PSO) can be created on the basis of our method, but PSO is strongly outperformed by USPEX. We also show how ideas from metadynamics can be used in the context of evolutionary structure prediction for escaping from local minima. Our cluster structure prediction algorithm, using the ideas initially developed for crystals, also shows excellent performance and outperforms other state-of-the-art algorithms.

Original languageEnglish
Pages (from-to)1172-1182
Number of pages11
JournalComputer Physics Communications
Volume184
Issue number4
DOIs
Publication statusPublished - Apr 2013
Externally publishedYes

Keywords

  • Cluster structure prediction
  • Crystal structure prediction
  • Evolutionary algorithms
  • Fingerprint function
  • Genetic algorithms
  • Global optimization
  • Particle swarm optimization

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