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Parametrically constrained geometry relaxations for high-throughput materials science

Publication ,  Journal Article
Lenz, MO; Purcell, TAR; Hicks, D; Curtarolo, S; Scheffler, M; Carbogno, C
Published in: npj Computational Materials
December 1, 2019

Reducing parameter spaces via exploiting symmetries has greatly accelerated and increased the quality of electronic-structure calculations. Unfortunately, many of the traditional methods fail when the global crystal symmetry is broken, even when the distortion is only a slight perturbation (e.g., Jahn-Teller like distortions). Here we introduce a flexible and generalizable parametric relaxation scheme and implement it in the all-electron code FHI-aims. This approach utilizes parametric constraints to maintain symmetry at any level. After demonstrating the method’s ability to relax metastable structures, we highlight its adaptability and performance over a test set of 359 materials, across 13 lattice prototypes. Finally we show how these constraints can reduce the number of steps needed to relax local lattice distortions by an order of magnitude. The flexibility of these constraints enables a significant acceleration of high-throughput searches for novel materials for numerous applications.

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Published In

npj Computational Materials

DOI

EISSN

2057-3960

Publication Date

December 1, 2019

Volume

5

Issue

1

Related Subject Headings

  • 5104 Condensed matter physics
  • 4016 Materials engineering
  • 3407 Theoretical and computational chemistry
 

Citation

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Lenz, M. O., Purcell, T. A. R., Hicks, D., Curtarolo, S., Scheffler, M., & Carbogno, C. (2019). Parametrically constrained geometry relaxations for high-throughput materials science. Npj Computational Materials, 5(1). https://doi.org/10.1038/s41524-019-0254-4
Lenz, M. O., T. A. R. Purcell, D. Hicks, S. Curtarolo, M. Scheffler, and C. Carbogno. “Parametrically constrained geometry relaxations for high-throughput materials science.” Npj Computational Materials 5, no. 1 (December 1, 2019). https://doi.org/10.1038/s41524-019-0254-4.
Lenz MO, Purcell TAR, Hicks D, Curtarolo S, Scheffler M, Carbogno C. Parametrically constrained geometry relaxations for high-throughput materials science. npj Computational Materials. 2019 Dec 1;5(1).
Lenz, M. O., et al. “Parametrically constrained geometry relaxations for high-throughput materials science.” Npj Computational Materials, vol. 5, no. 1, Dec. 2019. Scopus, doi:10.1038/s41524-019-0254-4.
Lenz MO, Purcell TAR, Hicks D, Curtarolo S, Scheffler M, Carbogno C. Parametrically constrained geometry relaxations for high-throughput materials science. npj Computational Materials. 2019 Dec 1;5(1).

Published In

npj Computational Materials

DOI

EISSN

2057-3960

Publication Date

December 1, 2019

Volume

5

Issue

1

Related Subject Headings

  • 5104 Condensed matter physics
  • 4016 Materials engineering
  • 3407 Theoretical and computational chemistry