材料信息学辅助下对新型无机材料的系统检索。

IF 7.4 3区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Science and Technology of Advanced Materials Pub Date : 2024-11-11 eCollection Date: 2025-01-01 DOI:10.1080/14686996.2024.2428154
Yukari Katsura, Masakazu Akiyama, Haruhiko Morito, Masaya Fujioka, Tohru Sugahara
{"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}
引用次数: 0

摘要

我们引进我们专有的材料信息学(MI)技术和我们的化学导向的方法来探索新的无机功能材料。利用晶体结构数据库的机器学习,我们开发了“元素反应性图”,显示了80 × 80 × 80元素组合的化合物的存在或预测的形成概率。用德劳内四面体分解法分析原子配位,建立了德劳内化学的概念。这使我们能够通过组合已知化合物的Delaunay四面体来设计晶体结构,并开发“晶体簇模拟器”网络系统。我们还开发了Starrydata2 web系统,从学术论文的情节图像中收集大规模的材料特性实验数据。该数据集支持我们通过各种数据分析来选择新型热电材料的候选材料。在涉及7000多个样品的大规模合成实验中,我们发现了许多新相,包括以新元素组合的已知结构的固溶体。我们利用金属钠合成和我们专有的离子扩散控制技术,通过从具有纳米框架结构的材料中提取一价阳离子,发现了新的笼状化合物,以及新的插层化合物。元件反应性图也用于选择器件电极的屏障金属,并且自主接触电阻测量系统正在开发中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Science and Technology of Advanced Materials
Science and Technology of Advanced Materials 工程技术-材料科学:综合
CiteScore
10.60
自引率
3.60%
发文量
52
审稿时长
4.8 months
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信