Evolutionary Crystal Structure Prediction and Novel High-Pressure Phases

  • Artem R. Oganov
  • Yanming Ma
  • Andriy O. Lyakhov
  • Mario Valle
  • Carlo Gatti
Conference paper
Part of the NATO Science for Peace and Security Series B: Physics and Biophysics book series (NAPSB)

Abstract

Prediction of stable crystal structures at given pressure-temperature conditions, based only on the knowledge of the chemical composition, is a central problem of condensed matter physics. This extremely challenging problem is often termed “crystal structure prediction problem”, and recently developed evolutionary algorithm USPEX (Universal Structure Predictor: Evolutionary Xtallography) made an important progress in solving it, enabling efficient and reliable prediction of structures with up to ~40 atoms in the unit cell using ab initio methods. Here we review this methodology, as well as recent progress in analyzing energy landscape of solids (which also helps to analyze results of USPEX runs). We show several recent applications – (1) prediction of new high-pressure phases of CaCO3, (2) search for the structure of the polymeric phase of CO2 (“phase V”), (3) high-pressure phases of oxygen, (4) exploration of possible stable compounds in the Xe–C system at high pressures, (5) exotic high-pressure phases of elements boron and sodium.

Keywords

Local Optimization Energy Landscape Electron Localization Function Candidate Structure Structure Search 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

ARO thanks R. Hoffmann, W. Grochala, R.J. Hemley and R.M. Hazen for exciting discussions. ARO also gratefully acknowledges financial support from the Research Foundation of Stony Brook University and from Intel Corporation. YM’s work is supported by the China 973 Program under Grant No. 2005CB724400, the National Natural Science Foundation of China under grant No. 10874054, the NSAF of China under Grant No. 10676011, and the 2007 Cheung Kong Scholars Programme of China. We acknowledge support from the National Science Foundation of China for the Research Fellowship for International Young Scientists (grant No. 10910263) and thank the Joint Supercomputer Center (Russian Academy of Sciences, Moscow) and CSCS (Manno) for providing supercomputer time. USPEX code is available on request from ARO.

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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Artem R. Oganov
    • 1
    • 2
  • Yanming Ma
    • 3
  • Andriy O. Lyakhov
    • 1
  • Mario Valle
    • 4
  • Carlo Gatti
    • 5
  1. 1.Department of Geosciences, Department of Physics and Astronomy, and New York Center for Computational SciencesState University of New YorkStony BrookUSA
  2. 2.Geology DepartmentMoscow State UniversityMoscowRussia
  3. 3.National Lab of Superhard MaterialsJilin UniversityChangchunP. R. China
  4. 4.Data Analysis and Visualization Group, Swiss National Supercomputing Centre CSCS)Cantonale Galleria 2Switzerland
  5. 5.CNR-ISTM, Istituto di Scienze e Tecnologie Molecolarivia Golgi 19Italy

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