npj Computational Materials (Aug 2017)

Construction of ground-state preserving sparse lattice models for predictive materials simulations

  • Wenxuan Huang,
  • Alexander Urban,
  • Ziqin Rong,
  • Zhiwei Ding,
  • Chuan Luo,
  • Gerbrand Ceder

DOI
https://doi.org/10.1038/s41524-017-0032-0
Journal volume & issue
Vol. 3, no. 1
pp. 1 – 9

Abstract

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Materials simulations: Constructing models guaranteed to preserve the ground states A method has been developed for performing materials simulations without needing to perform manual parameter tuning for the ground-state. First-principles density functional theory calculations are one of the most commonly used tools for computational materials science research but they cannot easily be applied to large structures that contain many thousands of atoms. In such systems, cluster expansion models are often used but they have a problem: manual parameter tuning is required to preserve the ground-state --- important as this usually governs the materials properties. An international team of researchers led by Gerbrand Ceder from Massachusetts Institute of Technology, the University of California Berkeley and Lawrence Berkeley National Laboratory now present a procedure for constructing cluster expansion models that can preserve the ground states without any need for tuning.