Santiago Miret, N. M. Anoop Krishnan, Benjamin Sanchez-Lengeling, Marta Skreta, Vineeth Venugopal and Jennifer N. Wei
{"title":"Perspective on AI for accelerated materials design at the AI4Mat-2023 workshop at NeurIPS 2023","authors":"Santiago Miret, N. M. Anoop Krishnan, Benjamin Sanchez-Lengeling, Marta Skreta, Vineeth Venugopal and Jennifer N. Wei","doi":"10.1039/D4DD90010C","DOIUrl":null,"url":null,"abstract":"<p >Applications of advanced artificial intelligence (AI) methods in the materials science domain has grown significantly in recent years resulting in numerous research efforts spanning diverse aspects of materials design, materials synthesis, and materials characterization. The AI for Accelerated Materials Design (AI4Mat) workshop at NeurIPS 2023 featured many of the ongoing major research themes by bringing together an international interdisciplinary community of researchers and enthusiasts across academia, industry, and national labs. The goal of these discussions was to highlight cutting-edge work from active researchers in these fields and uncover major impactful research problems that the community can jointly address. In this article, the AI4Mat-2023 organizing committee showcases the major developments in the field as well as ongoing research challenges where innovative solutions can bring transformative changes to the state-of-the-art in applying AI for accelerated materials design. The editors of <em>Digital Discovery</em> are pleased to feature this overview, and a selection of these manuscripts, in a new themed collection.</p>","PeriodicalId":72816,"journal":{"name":"Digital discovery","volume":" 6","pages":" 1081-1085"},"PeriodicalIF":6.2000,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2024/dd/d4dd90010c?page=search","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital discovery","FirstCategoryId":"1085","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2024/dd/d4dd90010c","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Applications of advanced artificial intelligence (AI) methods in the materials science domain has grown significantly in recent years resulting in numerous research efforts spanning diverse aspects of materials design, materials synthesis, and materials characterization. The AI for Accelerated Materials Design (AI4Mat) workshop at NeurIPS 2023 featured many of the ongoing major research themes by bringing together an international interdisciplinary community of researchers and enthusiasts across academia, industry, and national labs. The goal of these discussions was to highlight cutting-edge work from active researchers in these fields and uncover major impactful research problems that the community can jointly address. In this article, the AI4Mat-2023 organizing committee showcases the major developments in the field as well as ongoing research challenges where innovative solutions can bring transformative changes to the state-of-the-art in applying AI for accelerated materials design. The editors of Digital Discovery are pleased to feature this overview, and a selection of these manuscripts, in a new themed collection.