A robust, modular, and ab initio high-throughput workflow is presented to automatically match and characterize 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.

Michael Wolloch, Gabriele Losi, Omar Chehaimi, Firat Yalcin, Mauro Ferrario, Maria Clelia Righi (2022). High-throughput generation of potential energy surfaces for solid interfaces. COMPUTATIONAL MATERIALS SCIENCE, 207, 1-10 [10.1016/j.commatsci.2022.111302].

High-throughput generation of potential energy surfaces for solid interfaces

Maria Clelia Righi
2022

Abstract

A robust, modular, and ab initio high-throughput workflow is presented to automatically match and characterize 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.
2022
Michael Wolloch, Gabriele Losi, Omar Chehaimi, Firat Yalcin, Mauro Ferrario, Maria Clelia Righi (2022). High-throughput generation of potential energy surfaces for solid interfaces. COMPUTATIONAL MATERIALS SCIENCE, 207, 1-10 [10.1016/j.commatsci.2022.111302].
Michael Wolloch; Gabriele Losi; Omar Chehaimi; Firat Yalcin; Mauro Ferrario; Maria Clelia Righi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/889654
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