Approximate energy minimization for large Lennard-Jones clusters

Yuefan Deng, Carlos Rivera

Research output: Contribution to journalArticlepeer-review


We have designed a simple method to place particles on lattices, concentric shells and icosahedral concentric layers for minimizing the total energy of Lennard-Jones clusters, approximately, by analytical means. The most significant difference of our schemes from others is the dramatic reduction of parameters, which allows the study of large clusters, not possible otherwise. We present the derivation of formulae for minimal per-particle energy and for inter-particle distance. We also present their asymptotic values for large number of particles.

Original languageEnglish (US)
Pages (from-to)325-341
Number of pages17
JournalJournal of Global Optimization
Issue number4
StatePublished - Apr 2000


  • Asymptotic convergence
  • Global optimization
  • Lennard-Jones clusters

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research
  • Control and Optimization
  • Applied Mathematics


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