Alan Aspuru-Guzik, Austin Cheng, Marta Skreta, Cher Tian Ser, Andres Guzman-Cordero, Luca Thiede, Andreas Burger, Sergio Pablo-García, Abdulrahman Aldossary, Shi Xuan Leong, Felix Strieth-Kalthoff
{"title":"How to do impactful research in artificial intelligence for chemistry and materials science.","authors":"Alan Aspuru-Guzik, Austin Cheng, Marta Skreta, Cher Tian Ser, Andres Guzman-Cordero, Luca Thiede, Andreas Burger, Sergio Pablo-García, Abdulrahman Aldossary, Shi Xuan Leong, Felix Strieth-Kalthoff","doi":"10.1039/d4fd00153b","DOIUrl":null,"url":null,"abstract":"Machine learning has been pervasively touching many fields of science. Chemistry and materials science are no exception. While machine learning has been making a great impact, it is still not reaching its full potential or maturity. In this perspective, we first outline the pervasive current applications. Then, we discuss how machine learning researchers view and approach problems in the field. Finally, we provide our considerations for maximizing impact when researching machine learning for chemistry.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Faraday Discussions","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1039/d4fd00153b","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
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Abstract
Machine learning has been pervasively touching many fields of science. Chemistry and materials science are no exception. While machine learning has been making a great impact, it is still not reaching its full potential or maturity. In this perspective, we first outline the pervasive current applications. Then, we discuss how machine learning researchers view and approach problems in the field. Finally, we provide our considerations for maximizing impact when researching machine learning for chemistry.
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