A framework for quantifying uncertainty in DFT energy corrections

Abstract In this work, we demonstrate a method to quantify uncertainty in corrections to density functional theory (DFT) energies based on empirical results. Such corrections are commonly used to improve the accuracy of computational enthalpies of formation, phase stability predictions, and other en...

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Autores principales:	Amanda Wang, Ryan Kingsbury, Matthew McDermott, Matthew Horton, Anubhav Jain, Shyue Ping Ong, Shyam Dwaraknath, Kristin A. Persson
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/01cbcca218d344ddb52db613c074fb03
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id	oai:doaj.org-article:01cbcca218d344ddb52db613c074fb03
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spelling	oai:doaj.org-article:01cbcca218d344ddb52db613c074fb032021-12-02T16:31:52ZA framework for quantifying uncertainty in DFT energy corrections10.1038/s41598-021-94550-52045-2322https://doaj.org/article/01cbcca218d344ddb52db613c074fb032021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-94550-5https://doaj.org/toc/2045-2322Abstract In this work, we demonstrate a method to quantify uncertainty in corrections to density functional theory (DFT) energies based on empirical results. Such corrections are commonly used to improve the accuracy of computational enthalpies of formation, phase stability predictions, and other energy-derived properties, for example. We incorporate this method into a new DFT energy correction scheme comprising a mixture of oxidation-state and composition-dependent corrections and show that many chemical systems contain unstable polymorphs that may actually be predicted stable when uncertainty is taken into account. We then illustrate how these uncertainties can be used to estimate the probability that a compound is stable on a compositional phase diagram, thus enabling better-informed assessments of compound stability.Amanda WangRyan KingsburyMatthew McDermottMatthew HortonAnubhav JainShyue Ping OngShyam DwaraknathKristin A. PerssonNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Amanda Wang Ryan Kingsbury Matthew McDermott Matthew Horton Anubhav Jain Shyue Ping Ong Shyam Dwaraknath Kristin A. Persson A framework for quantifying uncertainty in DFT energy corrections
description	Abstract In this work, we demonstrate a method to quantify uncertainty in corrections to density functional theory (DFT) energies based on empirical results. Such corrections are commonly used to improve the accuracy of computational enthalpies of formation, phase stability predictions, and other energy-derived properties, for example. We incorporate this method into a new DFT energy correction scheme comprising a mixture of oxidation-state and composition-dependent corrections and show that many chemical systems contain unstable polymorphs that may actually be predicted stable when uncertainty is taken into account. We then illustrate how these uncertainties can be used to estimate the probability that a compound is stable on a compositional phase diagram, thus enabling better-informed assessments of compound stability.
format	article
author	Amanda Wang Ryan Kingsbury Matthew McDermott Matthew Horton Anubhav Jain Shyue Ping Ong Shyam Dwaraknath Kristin A. Persson
author_facet	Amanda Wang Ryan Kingsbury Matthew McDermott Matthew Horton Anubhav Jain Shyue Ping Ong Shyam Dwaraknath Kristin A. Persson
author_sort	Amanda Wang
title	A framework for quantifying uncertainty in DFT energy corrections
title_short	A framework for quantifying uncertainty in DFT energy corrections
title_full	A framework for quantifying uncertainty in DFT energy corrections
title_fullStr	A framework for quantifying uncertainty in DFT energy corrections
title_full_unstemmed	A framework for quantifying uncertainty in DFT energy corrections
title_sort	framework for quantifying uncertainty in dft energy corrections
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/01cbcca218d344ddb52db613c074fb03
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A framework for quantifying uncertainty in DFT energy corrections

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