过渡时期的算法观察镜

IF 38.1 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Alexander Rosu-Finsen
{"title":"过渡时期的算法观察镜","authors":"Alexander Rosu-Finsen","doi":"10.1038/s41570-024-00667-2","DOIUrl":null,"url":null,"abstract":"Glass transition temperatures are determined through, for instance, calorimetry, but maybe machine learning models can predict them. Here, researchers test this idea with published data as input for the model, to find a close correlation between predicted and experimental values. ","PeriodicalId":18849,"journal":{"name":"Nature reviews. Chemistry","volume":"8 11","pages":"797-797"},"PeriodicalIF":38.1000,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An algorithmic looking glass for transitions\",\"authors\":\"Alexander Rosu-Finsen\",\"doi\":\"10.1038/s41570-024-00667-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Glass transition temperatures are determined through, for instance, calorimetry, but maybe machine learning models can predict them. Here, researchers test this idea with published data as input for the model, to find a close correlation between predicted and experimental values. \",\"PeriodicalId\":18849,\"journal\":{\"name\":\"Nature reviews. Chemistry\",\"volume\":\"8 11\",\"pages\":\"797-797\"},\"PeriodicalIF\":38.1000,\"publicationDate\":\"2024-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature reviews. Chemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://www.nature.com/articles/s41570-024-00667-2\",\"RegionNum\":1,\"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":"Nature reviews. Chemistry","FirstCategoryId":"92","ListUrlMain":"https://www.nature.com/articles/s41570-024-00667-2","RegionNum":1,"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

玻璃转化温度可以通过量热法等方法确定,但机器学习模型或许可以预测玻璃转化温度。在这里,研究人员利用已公布的数据作为模型的输入,对这一想法进行了测试,发现预测值与实验值之间存在密切的相关性;
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An algorithmic looking glass for transitions

An algorithmic looking glass for transitions
Glass transition temperatures are determined through, for instance, calorimetry, but maybe machine learning models can predict them. Here, researchers test this idea with published data as input for the model, to find a close correlation between predicted and experimental values. 
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
Nature reviews. Chemistry
Nature reviews. Chemistry Chemical Engineering-General Chemical Engineering
CiteScore
52.80
自引率
0.80%
发文量
88
期刊介绍: Nature Reviews Chemistry is an online-only journal that publishes Reviews, Perspectives, and Comments on various disciplines within chemistry. The Reviews aim to offer balanced and objective analyses of selected topics, providing clear descriptions of relevant scientific literature. The content is designed to be accessible to recent graduates in any chemistry-related discipline while also offering insights for principal investigators and industry-based research scientists. Additionally, Reviews should provide the authors' perspectives on future directions and opinions regarding the major challenges faced by researchers in the field.
×
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