Small Data Machine Learning Approaches in Molecular and Materials Science

图书馆学 引用 计算机科学 化学 万维网
作者
Siddarth K. Achar,John A. Keith
出处
期刊:Chemical Reviews [American Chemical Society]
卷期号:124 (24): 13571-13573 被引量:12
标识
DOI:10.1021/acs.chemrev.4c00957
摘要

InfoMetrics Chemical ReviewsVol 124/Issue 24Article CiteCitationCitation and abstractCitation and referencesMore citation options ShareShare onFacebookX (Twitter)WeChatLinkedInRedditEmailJump toExpandCollapse HighlightDecember 25, 2024Small Data Machine Learning Approaches in Molecular and Materials ScienceClick to copy article linkArticle link copied!Siddarth K. AcharSiddarth K. AcharComputational Modeling & Simulation Program, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United StatesDepartment of Chemical & Petroleum Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United StatesMore by Siddarth K. AcharJohn A. Keith*John A. KeithDepartment of Chemical & Petroleum Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States*E-mail: [email protected]More by John A. Keithhttps://orcid.org/0000-0002-6583-6322Other Access OptionsChemical ReviewsCite this: Chem. Rev. 2024, 124, 24, 13571–13573Click to copy citationCitation copied!https://pubs.acs.org/doi/10.1021/acs.chemrev.4c00957https://doi.org/10.1021/acs.chemrev.4c00957Published December 25, 2024 Publication History Received 10 December 2024Published online 25 December 2024Published in issue 25 December 2024in-briefCopyright © Published 2024 by American Chemical SocietyRequest reuse permissionsACS PublicationsCopyright © Published 2024 by American Chemical Society Subjectswhat are subjectsArticle subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article.First-principles calculationsMaterialsMaterials scienceMolecular modelingQuality management Note: In lieu of an abstract, this is the article's first page. Read this article To access this article, please review the available access options below. Get instant access Purchase Access Read this article for 48 hours. Check out below using your ACS ID or as a guest. Purchase Access Restore my guest access Recommended Access through Your Institution You may have access to this article through your institution. Your institution does not have access to this content. Add or change your institution or let them know you'd like them to include access. Access Through Recommend Publication Institution Name Loading Institutional Login Options... Access Through Your Institution Add or Change Institution Explore subscriptions for institutions Recommended Log in to Access You may have access to this article with your ACS ID if you have previously purchased it or have ACS member benefits. Log in below. Login with ACS ID Purchase access Purchase this article for 48 hours $48.00 Add to cart Purchase this article for 48 hours Checkout Cited By Click to copy section linkSection link copied!This article has not yet been cited by other publications.Download PDF Get e-AlertsGet e-AlertsChemical ReviewsCite this: Chem. Rev. 2024, 124, 24, 13571–13573Click to copy citationCitation copied!https://doi.org/10.1021/acs.chemrev.4c00957Published December 25, 2024 Publication History Received 10 December 2024Published online 25 December 2024Published in issue 25 December 2024Copyright © Published 2024 by American Chemical SocietyRequest reuse permissionsArticle Views-Altmetric-Citations-Learn about these metrics closeArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated.Recommended Articles
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
张一完成签到 ,获得积分10
刚刚
刚刚
鲤角兽完成签到,获得积分10
2秒前
aaaa应助yry466采纳,获得30
2秒前
3秒前
JamesPei应助我爱娃哈哈采纳,获得10
3秒前
518发布了新的文献求助10
4秒前
gdou2030发布了新的文献求助10
4秒前
4秒前
4秒前
4秒前
yun完成签到,获得积分10
5秒前
5秒前
桔梗花完成签到,获得积分10
5秒前
丘比特应助飒saus采纳,获得10
5秒前
5秒前
一一应助石宇航采纳,获得10
5秒前
monica发布了新的文献求助10
5秒前
5秒前
5秒前
所所应助红豆子采纳,获得10
5秒前
6秒前
7秒前
橙子完成签到,获得积分10
7秒前
7秒前
霖槿发布了新的文献求助10
8秒前
8秒前
可爱的函函应助lchen采纳,获得10
8秒前
予秋发布了新的文献求助10
8秒前
姜院士发布了新的文献求助10
8秒前
caia完成签到,获得积分10
8秒前
小倩发布了新的文献求助10
8秒前
mss12138发布了新的文献求助200
8秒前
无极微光应助苹果采纳,获得20
9秒前
9秒前
108发布了新的文献求助10
9秒前
CSL完成签到 ,获得积分10
10秒前
11秒前
11秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
A Case Study on Hotels as Noncongregate Emergency Living Accommodations for Returning Citizens 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7764575
求助须知:如何正确求助?哪些是违规求助? 9308727
关于积分的说明 20307911
捐赠科研通 7349263
什么是DOI,文献DOI怎么找? 3314437
关于科研通互助平台的介绍 2463919
邀请新用户注册赠送积分活动 2328642