Malik Wagih , Tianjiao Lei , Daniel Ng , Christopher A. Schuh
{"title":"Grain boundary segregation in BCC vanadium-based alloys: Quantum-accurate computed segregation spectra and targeted experimental validations","authors":"Malik Wagih , Tianjiao Lei , Daniel Ng , Christopher A. Schuh","doi":"10.1016/j.actamat.2025.121169","DOIUrl":null,"url":null,"abstract":"<div><div>Grain boundaries are critically important to the material performance of fusion reactor materials such as vanadium, particularly mechanical properties and irradiation resistance. A key challenge to the design and control of grain boundaries in vanadium alloys is the lack of quantitative data on grain boundary segregation. In this study, we combine computational and experimental methods to address this gap. Using a machine learning-accelerated quantum mechanics/molecular mechanics approach, we calculated the segregation spectra for 28 transition metal elements in polycrystalline vanadium, and validated these predictions experimentally for a subset of solutes that sample a range of segregation behavior, specifically zirconium, titanium, and tungsten, using analytical transmission electron microscopy. The agreement between experiment and theory highlights the predictive capability of our approach. Critically, this work provides a comprehensive database of quantum-accurate solute segregation enthalpies in vanadium, enabling the development of advanced alloys for fusion reactors applications.</div></div>","PeriodicalId":238,"journal":{"name":"Acta Materialia","volume":"294 ","pages":"Article 121169"},"PeriodicalIF":8.3000,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Materialia","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1359645425004574","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Grain boundaries are critically important to the material performance of fusion reactor materials such as vanadium, particularly mechanical properties and irradiation resistance. A key challenge to the design and control of grain boundaries in vanadium alloys is the lack of quantitative data on grain boundary segregation. In this study, we combine computational and experimental methods to address this gap. Using a machine learning-accelerated quantum mechanics/molecular mechanics approach, we calculated the segregation spectra for 28 transition metal elements in polycrystalline vanadium, and validated these predictions experimentally for a subset of solutes that sample a range of segregation behavior, specifically zirconium, titanium, and tungsten, using analytical transmission electron microscopy. The agreement between experiment and theory highlights the predictive capability of our approach. Critically, this work provides a comprehensive database of quantum-accurate solute segregation enthalpies in vanadium, enabling the development of advanced alloys for fusion reactors applications.
期刊介绍:
Acta Materialia serves as a platform for publishing full-length, original papers and commissioned overviews that contribute to a profound understanding of the correlation between the processing, structure, and properties of inorganic materials. The journal seeks papers with high impact potential or those that significantly propel the field forward. The scope includes the atomic and molecular arrangements, chemical and electronic structures, and microstructure of materials, focusing on their mechanical or functional behavior across all length scales, including nanostructures.