{"title":"材料信息学和可持续性——紧急案例","authors":"H. Melia, Eric S. Muckley, J. Saal","doi":"10.1017/dce.2021.19","DOIUrl":null,"url":null,"abstract":"Abstract The development of transformative technologies for mitigating our global environmental and technological challenges will require significant innovation in the design, development, and manufacturing of advanced materials and chemicals. To achieve this innovation faster than what is possible by traditional human intuition-guided scientific methods, we must transition to a materials informatics-centered paradigm, in which synergies between data science, materials science, and artificial intelligence are leveraged to enable transformative, data-driven discoveries faster than ever before through the use of predictive models and digital twins. While materials informatics is experiencing rapidly increasing use across the materials and chemicals industries, broad adoption is hindered by barriers such as skill gaps, cultural resistance, and data sparsity. We discuss the importance of materials informatics for accelerating technological innovation, describe current barriers and examples of good practices, and offer suggestions for how researchers, funding agencies, and educational institutions can help accelerate the adoption of urgently needed informatics-based toolsets for science in the 21st century.","PeriodicalId":34169,"journal":{"name":"DataCentric Engineering","volume":" ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2021-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Materials informatics and sustainability—The case for urgency\",\"authors\":\"H. Melia, Eric S. Muckley, J. Saal\",\"doi\":\"10.1017/dce.2021.19\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The development of transformative technologies for mitigating our global environmental and technological challenges will require significant innovation in the design, development, and manufacturing of advanced materials and chemicals. To achieve this innovation faster than what is possible by traditional human intuition-guided scientific methods, we must transition to a materials informatics-centered paradigm, in which synergies between data science, materials science, and artificial intelligence are leveraged to enable transformative, data-driven discoveries faster than ever before through the use of predictive models and digital twins. While materials informatics is experiencing rapidly increasing use across the materials and chemicals industries, broad adoption is hindered by barriers such as skill gaps, cultural resistance, and data sparsity. We discuss the importance of materials informatics for accelerating technological innovation, describe current barriers and examples of good practices, and offer suggestions for how researchers, funding agencies, and educational institutions can help accelerate the adoption of urgently needed informatics-based toolsets for science in the 21st century.\",\"PeriodicalId\":34169,\"journal\":{\"name\":\"DataCentric Engineering\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2021-11-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"DataCentric Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1017/dce.2021.19\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"DataCentric Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/dce.2021.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Materials informatics and sustainability—The case for urgency
Abstract The development of transformative technologies for mitigating our global environmental and technological challenges will require significant innovation in the design, development, and manufacturing of advanced materials and chemicals. To achieve this innovation faster than what is possible by traditional human intuition-guided scientific methods, we must transition to a materials informatics-centered paradigm, in which synergies between data science, materials science, and artificial intelligence are leveraged to enable transformative, data-driven discoveries faster than ever before through the use of predictive models and digital twins. While materials informatics is experiencing rapidly increasing use across the materials and chemicals industries, broad adoption is hindered by barriers such as skill gaps, cultural resistance, and data sparsity. We discuss the importance of materials informatics for accelerating technological innovation, describe current barriers and examples of good practices, and offer suggestions for how researchers, funding agencies, and educational institutions can help accelerate the adoption of urgently needed informatics-based toolsets for science in the 21st century.