R. Thapa , M.E. McKenzie , E. Musterman , J. Kaman , V. Dierolf , H. Jain
{"title":"Machine learning based insights of seeded congruent crystal growth of LiNbO3 in glass","authors":"R. Thapa , M.E. McKenzie , E. Musterman , J. Kaman , V. Dierolf , H. Jain","doi":"10.1016/j.actamat.2024.120115","DOIUrl":null,"url":null,"abstract":"<div><p>The seeded crystal growth of LiNbO<span><math><msub><mrow></mrow><mrow><mn>3</mn></mrow></msub></math></span> in glass under the isothermal conditions has been studied using a machine-learned clustering algorithm trained on a combination of static and dynamic structural features. Our findings contradict the sharp crystal-glass interface assumption of classical nucleation theory (CNT). The growth of the seed occurs via the attachment of a group of atoms rather than single atoms. The predictions from the machine-learned simulations helped us compare the growth rate of seeds across various initial seed-sizes and temperature. Simulations with multiple seeds show that the growth rate of a seed is enhanced by the presence of another seed in its vicinity.</p></div>","PeriodicalId":238,"journal":{"name":"Acta Materialia","volume":null,"pages":null},"PeriodicalIF":8.3000,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S135964542400466X/pdfft?md5=bdd65fc90a627d8c0da17774289d45ea&pid=1-s2.0-S135964542400466X-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Materialia","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S135964542400466X","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
The seeded crystal growth of LiNbO in glass under the isothermal conditions has been studied using a machine-learned clustering algorithm trained on a combination of static and dynamic structural features. Our findings contradict the sharp crystal-glass interface assumption of classical nucleation theory (CNT). The growth of the seed occurs via the attachment of a group of atoms rather than single atoms. The predictions from the machine-learned simulations helped us compare the growth rate of seeds across various initial seed-sizes and temperature. Simulations with multiple seeds show that the growth rate of a seed is enhanced by the presence of another seed in its vicinity.
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.