Victor Milman , Alexander Perlov , Neil Spenley , Björn Winkler
{"title":"Accuracy of calculated elastic properties of inorganic materials: Density functional theory and machine-learned potentials","authors":"Victor Milman , Alexander Perlov , Neil Spenley , Björn Winkler","doi":"10.1016/j.mtla.2025.102503","DOIUrl":null,"url":null,"abstract":"<div><div>Elastic coefficients of a large set of inorganic compounds are calculated using the most popular expressions for the exchange–correlation functional in the density functional theory (DFT) formalism. We compiled an extensive database of experimental measurements for comparison with the calculated properties, and suggest that the meta-GGA RSCAN functional produces the most accurate description overall, followed by PBESOL or Wu-Cohen formulations. We show that the most commonly used functional, PBE, offers the least accurate representation of elastic properties. A popular machine-learning potential scheme, MACE, using MP-0b, OMAT-0, or MACE-MATPES-r2SCAN-0 models has an RMS error for bulk and shear modulus that is only 1.5–2 times worse than the best DFT result while being 3–4 orders of magnitude faster. We demonstrate that calculated elastic properties can be used in conjunction with empirical expressions for Vickers hardness and fracture toughness to produce reasonable estimates of these mechanical properties for engineering applications of covalent and ionic crystals.</div></div>","PeriodicalId":47623,"journal":{"name":"Materialia","volume":"43 ","pages":"Article 102503"},"PeriodicalIF":2.9000,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materialia","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2589152925001711","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Elastic coefficients of a large set of inorganic compounds are calculated using the most popular expressions for the exchange–correlation functional in the density functional theory (DFT) formalism. We compiled an extensive database of experimental measurements for comparison with the calculated properties, and suggest that the meta-GGA RSCAN functional produces the most accurate description overall, followed by PBESOL or Wu-Cohen formulations. We show that the most commonly used functional, PBE, offers the least accurate representation of elastic properties. A popular machine-learning potential scheme, MACE, using MP-0b, OMAT-0, or MACE-MATPES-r2SCAN-0 models has an RMS error for bulk and shear modulus that is only 1.5–2 times worse than the best DFT result while being 3–4 orders of magnitude faster. We demonstrate that calculated elastic properties can be used in conjunction with empirical expressions for Vickers hardness and fracture toughness to produce reasonable estimates of these mechanical properties for engineering applications of covalent and ionic crystals.
期刊介绍:
Materialia is a multidisciplinary journal of materials science and engineering that publishes original peer-reviewed research articles. Articles in Materialia advance the understanding of the relationship between processing, structure, property, and function of materials.
Materialia publishes full-length research articles, review articles, and letters (short communications). In addition to receiving direct submissions, Materialia also accepts transfers from Acta Materialia, Inc. partner journals. Materialia offers authors the choice to publish on an open access model (with author fee), or on a subscription model (with no author fee).