An improved sampling strategy for global energy minimization of multi-component systems

Richard Otis, Maria Emelianenko, Zi Kui Liu

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Effective initial sampling plays an important role in capturing key details about the energy surfaces of multi-component, multi-sublattice phases for the purposes of accurate convergence toward the global minimum energy configuration of a given system. It is shown that, when using the appropriate statistical distribution, both quasi-random and pseudo-random sampling methods compare well with the standard uniform grid-based technique. Moreover, the combination of random sampling with uniform grid points, while maintaining sampling performance for equilibrium calculations in the Al-Co-Cr system, significantly increases performance for a fictive 10-component system.

Original languageEnglish (US)
Pages (from-to)282-291
Number of pages10
JournalComputational Materials Science
Volume130
DOIs
StatePublished - Apr 1 2017

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Chemistry(all)
  • Materials Science(all)
  • Mechanics of Materials
  • Physics and Astronomy(all)
  • Computational Mathematics

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