Automated calculation and convergence of defect transport tensors

Abstract Defect diffusion is a key process in materials science and catalysis, but as migration mechanisms are often too complex to enumerate a priori, calculation of transport tensors typically have no measure of convergence and require significant end-user intervention. These two bottlenecks preve...

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Autores principales:	Thomas D. Swinburne, Danny Perez
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765
Acceso en línea:	https://doaj.org/article/b43319cc531a461c817636df06ce17aa
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spelling	oai:doaj.org-article:b43319cc531a461c817636df06ce17aa2021-12-02T11:43:49ZAutomated calculation and convergence of defect transport tensors10.1038/s41524-020-00463-82057-3960https://doaj.org/article/b43319cc531a461c817636df06ce17aa2020-12-01T00:00:00Zhttps://doi.org/10.1038/s41524-020-00463-8https://doaj.org/toc/2057-3960Abstract Defect diffusion is a key process in materials science and catalysis, but as migration mechanisms are often too complex to enumerate a priori, calculation of transport tensors typically have no measure of convergence and require significant end-user intervention. These two bottlenecks prevent high-throughput implementations essential to propagate model-form uncertainty from interatomic interactions to predictive simulations. In order to address these issues, we extend a massively parallel accelerated sampling scheme, autonomously controlled by Bayesian estimators of statewide sampling completeness, to build atomistic kinetic Monte Carlo models on a state-space irreducible under exchange and space group symmetries. Focusing on isolated defects, we derive analytic expressions for drift and diffusion coefficients, providing a convergence metric by calculating the Kullback–Leibler divergence across the ensemble of diffusion processes consistent with the sampling uncertainty. The autonomy and efficacy of the method is demonstrated on surface trimers in tungsten and Hexa-interstitials in magnesium oxide, both of which exhibit complex, correlated migration mechanisms.Thomas D. SwinburneDanny PerezNature PortfolioarticleMaterials of engineering and construction. Mechanics of materialsTA401-492Computer softwareQA76.75-76.765ENnpj Computational Materials, Vol 6, Iss 1, Pp 1-7 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765
spellingShingle	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765 Thomas D. Swinburne Danny Perez Automated calculation and convergence of defect transport tensors
description	Abstract Defect diffusion is a key process in materials science and catalysis, but as migration mechanisms are often too complex to enumerate a priori, calculation of transport tensors typically have no measure of convergence and require significant end-user intervention. These two bottlenecks prevent high-throughput implementations essential to propagate model-form uncertainty from interatomic interactions to predictive simulations. In order to address these issues, we extend a massively parallel accelerated sampling scheme, autonomously controlled by Bayesian estimators of statewide sampling completeness, to build atomistic kinetic Monte Carlo models on a state-space irreducible under exchange and space group symmetries. Focusing on isolated defects, we derive analytic expressions for drift and diffusion coefficients, providing a convergence metric by calculating the Kullback–Leibler divergence across the ensemble of diffusion processes consistent with the sampling uncertainty. The autonomy and efficacy of the method is demonstrated on surface trimers in tungsten and Hexa-interstitials in magnesium oxide, both of which exhibit complex, correlated migration mechanisms.
format	article
author	Thomas D. Swinburne Danny Perez
author_facet	Thomas D. Swinburne Danny Perez
author_sort	Thomas D. Swinburne
title	Automated calculation and convergence of defect transport tensors
title_short	Automated calculation and convergence of defect transport tensors
title_full	Automated calculation and convergence of defect transport tensors
title_fullStr	Automated calculation and convergence of defect transport tensors
title_full_unstemmed	Automated calculation and convergence of defect transport tensors
title_sort	automated calculation and convergence of defect transport tensors
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/b43319cc531a461c817636df06ce17aa
work_keys_str_mv	AT thomasdswinburne automatedcalculationandconvergenceofdefecttransporttensors AT dannyperez automatedcalculationandconvergenceofdefecttransporttensors
_version_	1718395364084547584

Automated calculation and convergence of defect transport tensors

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