Computational Materials Science2022,Vol.20710.DOI:10.1016/j.commatsci.2022.111302

High-throughput generation of potential energy surfaces for solid interfaces

Wolloch, Michael Losi, Gabriele Chehaimi, Omar Yalcin, Firat Ferrario, Mauro Righi, Maria Clelia
Computational Materials Science2022,Vol.20710.DOI:10.1016/j.commatsci.2022.111302

High-throughput generation of potential energy surfaces for solid interfaces

Wolloch, Michael 1Losi, Gabriele 2Chehaimi, Omar 2Yalcin, Firat 1Ferrario, Mauro 3Righi, Maria Clelia2
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作者信息

  • 1. Univ Vienna
  • 2. Alma Mater Studiorum Univ Bologna
  • 3. Univ Modena & Reggio Emilia
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Abstract

A robust, modular, and ab initio high-throughput workflow is presented to automatically match and char-acterize solid-solid interfaces using density functional theory calculations with automatic error corrections. The potential energy surface of the interface is computed in a highly efficient manner, exploiting the high-symmetry points of the two mated surfaces. A database is automatically populated with results to ensure that already available data are not unnecessarily recomputed. Computational parameters and slab thicknesses are converged automatically to minimize computational cost while ensuring accurate results. The surfaces are matched according to user-specified maximal cross-section area and mismatches. Example results are presented as a proof of concept and to show the capabilities of our approach that will serve as the basis for many more interface studies.

Key words

High-throughput/Interfaces/Potential energy surface/Density functional theory/Tribology/ELASTIC-MODULI/INFRASTRUCTURE/1ST-PRINCIPLES/TEMPERATURE/ADHESIVE/FRICTION

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出版年

2022
Computational Materials Science

Computational Materials Science

EISCI
ISSN:0927-0256
被引量4
参考文献量56
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