{"title":"材料信息学辅助下对新型无机材料的系统检索。","authors":"Yukari Katsura, Masakazu Akiyama, Haruhiko Morito, Masaya Fujioka, Tohru Sugahara","doi":"10.1080/14686996.2024.2428154","DOIUrl":null,"url":null,"abstract":"<p><p>We introduce our proprietary Materials Informatics (MI) technologies and our chemistry-oriented methodology for exploring new inorganic functional materials. Using machine learning on crystal structure databases, we developed 'Element Reactivity Maps' that displays the presence or the predicted formation probability of compounds for combinations of 80 × 80 × 80 elements. By analysing atomic coordinates with Delaunay tetrahedral decomposition, we established the concept of Delaunay Chemistry. This enabled us to design crystal structures by combining Delaunay tetrahedra of known compounds and to develop the 'Crystal Cluster Simulator' web system. We also developed the Starrydata2 web system to collect large-scale experimental data on material properties from plot images in academic papers. This dataset supported us to select candidate materials for new thermoelectric materials through various data analyses. In large-scale synthesis experiments involving over 7,000 samples, we discovered numerous new phases, including solid solutions of known structures in new combinations of elements. Using sodium metal in synthesis and our proprietary ion diffusion control technologies, we discovered new cage-like compounds by extracting monovalent cations from materials with nano-framework structures, as well as new intercalation compounds. The Element Reactivity Maps were also used to select barrier metals for device electrodes, and an autonomous contact resistance measurement system is under development.</p>","PeriodicalId":21588,"journal":{"name":"Science and Technology of Advanced Materials","volume":"26 1","pages":"2428154"},"PeriodicalIF":7.4000,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703499/pdf/","citationCount":"0","resultStr":"{\"title\":\"Systematic searches for new inorganic materials assisted by materials informatics.\",\"authors\":\"Yukari Katsura, Masakazu Akiyama, Haruhiko Morito, Masaya Fujioka, Tohru Sugahara\",\"doi\":\"10.1080/14686996.2024.2428154\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We introduce our proprietary Materials Informatics (MI) technologies and our chemistry-oriented methodology for exploring new inorganic functional materials. Using machine learning on crystal structure databases, we developed 'Element Reactivity Maps' that displays the presence or the predicted formation probability of compounds for combinations of 80 × 80 × 80 elements. By analysing atomic coordinates with Delaunay tetrahedral decomposition, we established the concept of Delaunay Chemistry. This enabled us to design crystal structures by combining Delaunay tetrahedra of known compounds and to develop the 'Crystal Cluster Simulator' web system. We also developed the Starrydata2 web system to collect large-scale experimental data on material properties from plot images in academic papers. This dataset supported us to select candidate materials for new thermoelectric materials through various data analyses. In large-scale synthesis experiments involving over 7,000 samples, we discovered numerous new phases, including solid solutions of known structures in new combinations of elements. Using sodium metal in synthesis and our proprietary ion diffusion control technologies, we discovered new cage-like compounds by extracting monovalent cations from materials with nano-framework structures, as well as new intercalation compounds. The Element Reactivity Maps were also used to select barrier metals for device electrodes, and an autonomous contact resistance measurement system is under development.</p>\",\"PeriodicalId\":21588,\"journal\":{\"name\":\"Science and Technology of Advanced Materials\",\"volume\":\"26 1\",\"pages\":\"2428154\"},\"PeriodicalIF\":7.4000,\"publicationDate\":\"2024-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703499/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science and Technology of Advanced Materials\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1080/14686996.2024.2428154\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science and Technology of Advanced Materials","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1080/14686996.2024.2428154","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Systematic searches for new inorganic materials assisted by materials informatics.
We introduce our proprietary Materials Informatics (MI) technologies and our chemistry-oriented methodology for exploring new inorganic functional materials. Using machine learning on crystal structure databases, we developed 'Element Reactivity Maps' that displays the presence or the predicted formation probability of compounds for combinations of 80 × 80 × 80 elements. By analysing atomic coordinates with Delaunay tetrahedral decomposition, we established the concept of Delaunay Chemistry. This enabled us to design crystal structures by combining Delaunay tetrahedra of known compounds and to develop the 'Crystal Cluster Simulator' web system. We also developed the Starrydata2 web system to collect large-scale experimental data on material properties from plot images in academic papers. This dataset supported us to select candidate materials for new thermoelectric materials through various data analyses. In large-scale synthesis experiments involving over 7,000 samples, we discovered numerous new phases, including solid solutions of known structures in new combinations of elements. Using sodium metal in synthesis and our proprietary ion diffusion control technologies, we discovered new cage-like compounds by extracting monovalent cations from materials with nano-framework structures, as well as new intercalation compounds. The Element Reactivity Maps were also used to select barrier metals for device electrodes, and an autonomous contact resistance measurement system is under development.
期刊介绍:
Science and Technology of Advanced Materials (STAM) is a leading open access, international journal for outstanding research articles across all aspects of materials science. Our audience is the international community across the disciplines of materials science, physics, chemistry, biology as well as engineering.
The journal covers a broad spectrum of topics including functional and structural materials, synthesis and processing, theoretical analyses, characterization and properties of materials. Emphasis is placed on the interdisciplinary nature of materials science and issues at the forefront of the field, such as energy and environmental issues, as well as medical and bioengineering applications.
Of particular interest are research papers on the following topics:
Materials informatics and materials genomics
Materials for 3D printing and additive manufacturing
Nanostructured/nanoscale materials and nanodevices
Bio-inspired, biomedical, and biological materials; nanomedicine, and novel technologies for clinical and medical applications
Materials for energy and environment, next-generation photovoltaics, and green technologies
Advanced structural materials, materials for extreme conditions.