4.7 Article

Tight-Binding Approximation-Enhanced Global Optimization

期刊

JOURNAL OF CHEMICAL THEORY AND COMPUTATION
卷 14, 期 5, 页码 2797-2807

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jctc.8b00039

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资金

  1. Swedish Research Council [201605234]
  2. Chalmers Area of Advance Nano
  3. C3SE (Goteborg) via a SNIC grant
  4. Swedish Energy Agency
  5. AB Volvo
  6. ECAPS AB
  7. Haldor Topsoe A/S
  8. Scania CV AB
  9. Volvo Car Corporation AB
  10. Wartsila Finland Oy
  11. Danish Council for Independent Research Natural Sciences [0602-02566B]
  12. VILLUM FONDEN (Investigator grant) [16562]
  13. COST action [CM1104]
  14. Chalmers Area of Advance Transport

向作者/读者索取更多资源

Solving and predicting atomic structures from first principles methodologies is limited by the computational cost of exploring the search space, even when relatively inexpensive density functionals are used. Here, we present an efficient approach where the search is performed using density functional tight-binding, with an automatic adaptive parametrization scheme for the repulsive pair potentials. We successfully apply the method to the genetic algorithm optimization of bulk carbon, titanium dioxide, palladium oxide, and calcium hydroxide, and we assess the stability of the unknown crystal structure of palladium hydroxide.

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