混合钙钛矿的材料数据:方法和潜在的用途

IF 14 2区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Trends in Chemistry Pub Date : 2023-10-01 DOI:10.1016/j.trechm.2023.08.005
Rayan Chakraborty, Volker Blum
{"title":"混合钙钛矿的材料数据:方法和潜在的用途","authors":"Rayan Chakraborty, Volker Blum","doi":"10.1016/j.trechm.2023.08.005","DOIUrl":null,"url":null,"abstract":"Over the past decade, hybrid perovskite research has evolved to a point where the literature contains an enormous volume of chemical and physical information. However, many essential material design challenges remain open for researchers to address. The dispersed nature of the large, rapidly growing body of hybrid perovskite materials data poses a barrier to systematic discovery efforts, which can be solved by materials property databases, either by high-throughput or by systematic, accurate human-curated efforts. This opinioned review article discusses the necessity, challenges, and requirements of building such data libraries. In light of using machine learning (ML) and related tools to solve specific problems, the importance of information related to different material attributes and properties is also highlighted.","PeriodicalId":48544,"journal":{"name":"Trends in Chemistry","volume":"16 1","pages":"0"},"PeriodicalIF":14.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Curated materials data of hybrid perovskites: approaches and potential usage\",\"authors\":\"Rayan Chakraborty, Volker Blum\",\"doi\":\"10.1016/j.trechm.2023.08.005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Over the past decade, hybrid perovskite research has evolved to a point where the literature contains an enormous volume of chemical and physical information. However, many essential material design challenges remain open for researchers to address. The dispersed nature of the large, rapidly growing body of hybrid perovskite materials data poses a barrier to systematic discovery efforts, which can be solved by materials property databases, either by high-throughput or by systematic, accurate human-curated efforts. This opinioned review article discusses the necessity, challenges, and requirements of building such data libraries. In light of using machine learning (ML) and related tools to solve specific problems, the importance of information related to different material attributes and properties is also highlighted.\",\"PeriodicalId\":48544,\"journal\":{\"name\":\"Trends in Chemistry\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":14.0000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Trends in Chemistry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.trechm.2023.08.005\",\"RegionNum\":2,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.trechm.2023.08.005","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

在过去的十年里,杂化钙钛矿的研究已经发展到一个地步,文献中包含了大量的化学和物理信息。然而,许多重要的材料设计挑战仍有待研究人员解决。大量快速增长的混合钙钛矿材料数据的分散性对系统的发现工作构成了障碍,这可以通过材料属性数据库来解决,无论是通过高通量还是通过系统的、准确的人为策划的努力。这篇评论文章讨论了构建此类数据库的必要性、挑战和需求。鉴于使用机器学习(ML)和相关工具来解决具体问题,还强调了与不同材料属性和性能相关的信息的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Curated materials data of hybrid perovskites: approaches and potential usage
Over the past decade, hybrid perovskite research has evolved to a point where the literature contains an enormous volume of chemical and physical information. However, many essential material design challenges remain open for researchers to address. The dispersed nature of the large, rapidly growing body of hybrid perovskite materials data poses a barrier to systematic discovery efforts, which can be solved by materials property databases, either by high-throughput or by systematic, accurate human-curated efforts. This opinioned review article discusses the necessity, challenges, and requirements of building such data libraries. In light of using machine learning (ML) and related tools to solve specific problems, the importance of information related to different material attributes and properties is also highlighted.
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
Trends in Chemistry
Trends in Chemistry CHEMISTRY, MULTIDISCIPLINARY-
CiteScore
28.00
自引率
0.60%
发文量
138
期刊介绍: Trends in Chemistry serves as a new global platform for discussing significant and transformative concepts across all areas of chemistry. It recognizes that breakthroughs in chemistry hold the key to addressing major global challenges. The journal offers readable, multidisciplinary articles, including reviews, opinions, and short pieces, designed to keep both students and leading scientists updated on pressing issues in the field. Covering analytical, inorganic, organic, physical, and theoretical chemistry, the journal highlights major themes such as biochemistry, catalysis, environmental chemistry, materials, medicine, polymers, and supramolecular chemistry. It also welcomes articles on chemical education, health and safety, policy and public relations, and ethics and law.
期刊最新文献
Enantiospecific 1,3-hydrogen transfer of alkenes and alkynes Subscription and Copyright Information Advisory Board and Contents Cholesterol-mediated functionalization of liposomes for artificial cell design ChemCarnival: inspiring future STEM pioneers
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1