{"title":"材料基因组工程前沿的前景","authors":"Jianxin Xie","doi":"10.1002/mgea.17","DOIUrl":null,"url":null,"abstract":"<p>Materials genome engineering represents the new frontier of materials research, and is disrupting the conventional “trial and error” paradigm for materials innovation. In the present perspective, the author reflects on the major achievements already made in five sub-domains, including high-efficiency materials computation and design, revolutionary experimental technologies, materials big data technologies, research and development of advanced materials, and industrial applications. Furthermore, the author lays out five crucial directions of future efforts for maturing the relevant technologies. These directions include cross-scale modeling and computational design, artificial intelligence for materials science, automatic and intelligent experimentation, digital twin, and data resource management and sharing.</p>","PeriodicalId":100889,"journal":{"name":"Materials Genome Engineering Advances","volume":"1 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mgea.17","citationCount":"0","resultStr":"{\"title\":\"Prospects of materials genome engineering frontiers\",\"authors\":\"Jianxin Xie\",\"doi\":\"10.1002/mgea.17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Materials genome engineering represents the new frontier of materials research, and is disrupting the conventional “trial and error” paradigm for materials innovation. In the present perspective, the author reflects on the major achievements already made in five sub-domains, including high-efficiency materials computation and design, revolutionary experimental technologies, materials big data technologies, research and development of advanced materials, and industrial applications. Furthermore, the author lays out five crucial directions of future efforts for maturing the relevant technologies. These directions include cross-scale modeling and computational design, artificial intelligence for materials science, automatic and intelligent experimentation, digital twin, and data resource management and sharing.</p>\",\"PeriodicalId\":100889,\"journal\":{\"name\":\"Materials Genome Engineering Advances\",\"volume\":\"1 2\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mgea.17\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Materials Genome Engineering Advances\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/mgea.17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials Genome Engineering Advances","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/mgea.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prospects of materials genome engineering frontiers
Materials genome engineering represents the new frontier of materials research, and is disrupting the conventional “trial and error” paradigm for materials innovation. In the present perspective, the author reflects on the major achievements already made in five sub-domains, including high-efficiency materials computation and design, revolutionary experimental technologies, materials big data technologies, research and development of advanced materials, and industrial applications. Furthermore, the author lays out five crucial directions of future efforts for maturing the relevant technologies. These directions include cross-scale modeling and computational design, artificial intelligence for materials science, automatic and intelligent experimentation, digital twin, and data resource management and sharing.