Article(id=1319222540204097919, tenantId=1146029695717560320, journalId=1263187385517883426, issueId=1319222524555153701, articleNumber=null, orderNo=null, doi=10.14062/j.issn.0454-5648.20220813, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1664467200000, receivedDateStr=2022-09-30, revisedDate=1669219200000, revisedDateStr=2022-11-24, acceptedDate=null, acceptedDateStr=null, onlineDate=1792456763553, onlineDateStr=2026-10-20, pubDate=1676822400000, pubDateStr=2023-02-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792456763553, onlineIssueDateStr=2026-10-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792456763553, creator=13701087609, updateTime=1792456763553, updator=13701087609, issue=Issue{id=1319222524555153701, tenantId=1146029695717560320, journalId=1263187385517883426, year='2023', volume='51', issue='2', pageStart='283', pageEnd='560', issueExtLink='null', onlineDate='null', pubDate='1676822400000', pubDateStr='2023-02-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1792456759823, creator='13701087609', updateTime=1792456885477, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1319223051636560419, tenantId=1146029695717560320, journalId=1263187385517883426, issueId=1319222524555153701, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1319223051636560420, tenantId=1146029695717560320, journalId=1263187385517883426, issueId=1319222524555153701, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=367, endPage=372, ext={EN=ArticleExt(id=1319222540447367552, articleId=1319222540204097919, tenantId=1146029695717560320, journalId=1263187385517883426, language=EN, title=Discovering ABO3-Type Perovskite with High Dielectric Constant via Unsupervised Learning, columnId=1321891532131652078, journalTitle=Journal of the Chinese Ceramic Society, columnName=Application of Machine Learning in Material Research & Development—Research Articles, runingTitle=null, highlight=null, articleAbstract=

Machine learning has become an important transformative method to explore novel materials, but the small sample size and high noise of material data bring a great challenge to data-driven research and development. To address the challenge, unsupervised learning was applied to discover perovskite materials with a high dielectric constant. Twenty perovskite materials with a high dielectric constant (i.e., BaHfO3 and BiFeO3) were screened out via iterative clustering. We performed dimensionality reduction analysis and descriptors analysis including elements, crystal structure and tolerance factors to find the underlying trend and the relationship between ABO3 structure and dielectric constant. This method can provide an idea for solving the lack of material data labels, which can be also applied to screen other novel functional materials.

, authors=Runlin LIU1, Changjiao LI2, Jian WANG2, Hanxing LIU1, Zhonghui SHEN1, authorsList=Runlin LIU, Changjiao LI, Jian WANG, Hanxing LIU, Zhonghui SHEN, authorCompany=null, correspAuthors=Zhonghui SHEN, authorNote=

LIU Runlin (2001-), male, Master candidate. E-mail:

, correspAuthorsNote=
SHEN Zhonghui (1991-), male, Ph.D, Associate Professor. E-mail:
, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1319222540678054273, articleId=1319222540204097919, tenantId=1146029695717560320, journalId=1263187385517883426, language=CN, title=无监督学习探索高介电常数的ABO3型钙钛矿材料, columnId=1321891532337172975, journalTitle=硅酸盐学报, columnName=机器学习在材料研发中的应用专题—研究论文, runingTitle=null, highlight=null, articleAbstract=

机器学习已成为新材料研发的重要变革性手段,但材料数据样本量少、噪音高等特点为数据驱动的研发模式带来巨大挑战。本工作将无监督学习应用于挖掘高介电常数的钙钛矿材料。针对标签数据少的问题,通过聚类学习的方法不断优化迭代来缩小搜索空间,最终筛选出了BaHfO3和BiFeO3等20种具有高介电常数潜力的钙钛矿材料,并通过降维分析等手段从元素种类、晶体结构和容忍因子等方面展开规律分析,挖掘钙钛矿材料结构与介电常数之间的关联。该方法为解决材料性能数据标签的缺失提供了一种思路,可应用于筛选和挖掘其他新型功能材料。

, authors=刘润林1, 李长姣2, 王建2, 刘韩星1, 沈忠慧1, authorsList=刘润林, 李长姣, 王建, 刘韩星, 沈忠慧, authorCompany=null, correspAuthors=沈忠慧, authorNote=

刘润林(2001—),男,硕士研究生。

, correspAuthorsNote=
沈忠慧(1991—),男,博士,副教授。
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无监督学习探索高介电常数的ABO3型钙钛矿材料
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刘润林 1 , 李长姣 2 , 王建 2 , 刘韩星 1 , 沈忠慧 1
硅酸盐学报 | 机器学习在材料研发中的应用专题—研究论文 2023,51(2): 367-372
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硅酸盐学报 |机器学习在材料研发中的应用专题—研究论文 2023 , 51 (2) : 367 -372
无监督学习探索高介电常数的ABO3型钙钛矿材料
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刘润林1 , 李长姣2, 王建2, 刘韩星1, 沈忠慧1
作者信息
  • 1.武汉理工大学材料科学与工程国际化示范学院,武汉 430070
  • 2.武汉理工大学材料科学与工程学院,武汉 430070
通讯作者:
沈忠慧(1991—),男,博士,副教授。
作者简介:

刘润林(2001—),男,硕士研究生。

Discovering ABO3-Type Perovskite with High Dielectric Constant via Unsupervised Learning
Runlin LIU1 , Changjiao LI2, Jian WANG2, Hanxing LIU1, Zhonghui SHEN1
Affiliations
  • 1.International School of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China
  • 2.School of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China
  • Corresponding Author:
    SHEN Zhonghui (1991-), male, Ph.D, Associate Professor. E-mail:

    LIU Runlin (2001-), male, Master candidate. E-mail:

出版时间: 2023-02-20 doi: 10.14062/j.issn.0454-5648.20220813
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机器学习已成为新材料研发的重要变革性手段,但材料数据样本量少、噪音高等特点为数据驱动的研发模式带来巨大挑战。本工作将无监督学习应用于挖掘高介电常数的钙钛矿材料。针对标签数据少的问题,通过聚类学习的方法不断优化迭代来缩小搜索空间,最终筛选出了BaHfO3和BiFeO3等20种具有高介电常数潜力的钙钛矿材料,并通过降维分析等手段从元素种类、晶体结构和容忍因子等方面展开规律分析,挖掘钙钛矿材料结构与介电常数之间的关联。该方法为解决材料性能数据标签的缺失提供了一种思路,可应用于筛选和挖掘其他新型功能材料。

介电常数  /  机器学习  /  钙钛矿材料  /  电介质材料

Machine learning has become an important transformative method to explore novel materials, but the small sample size and high noise of material data bring a great challenge to data-driven research and development. To address the challenge, unsupervised learning was applied to discover perovskite materials with a high dielectric constant. Twenty perovskite materials with a high dielectric constant (i.e., BaHfO3 and BiFeO3) were screened out via iterative clustering. We performed dimensionality reduction analysis and descriptors analysis including elements, crystal structure and tolerance factors to find the underlying trend and the relationship between ABO3 structure and dielectric constant. This method can provide an idea for solving the lack of material data labels, which can be also applied to screen other novel functional materials.

dielectric constant  /  machine learning  /  perovskite materials  /  dielectrics
刘润林, 李长姣, 王建, 刘韩星, 沈忠慧. 无监督学习探索高介电常数的ABO3型钙钛矿材料. 硅酸盐学报, 2023 , 51 (2) : 367 -372 . DOI: 10.14062/j.issn.0454-5648.20220813
Runlin LIU, Changjiao LI, Jian WANG, Hanxing LIU, Zhonghui SHEN. Discovering ABO3-Type Perovskite with High Dielectric Constant via Unsupervised Learning[J]. Journal of the Chinese Ceramic Society, 2023 , 51 (2) : 367 -372 . DOI: 10.14062/j.issn.0454-5648.20220813
  • 国家自然科学基金青年科学基金项目(52002300)
  • 国家自然科学基金重大研究计划培育项目(92066103)
  • 中国科协青年人才托举工程(2019QNRC001)
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2023年第51卷第2期
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doi: 10.14062/j.issn.0454-5648.20220813
  • 接收时间:2022-09-30
  • 首发时间:2026-10-20
  • 出版时间:2023-02-20
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  • 收稿日期:2022-09-30
  • 修回日期:2022-11-24
基金
国家自然科学基金青年科学基金项目(52002300)
国家自然科学基金重大研究计划培育项目(92066103)
中国科协青年人才托举工程(2019QNRC001)
作者信息
    1.武汉理工大学材料科学与工程国际化示范学院,武汉 430070
    2.武汉理工大学材料科学与工程学院,武汉 430070

通讯作者:

沈忠慧(1991—),男,博士,副教授。
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https://castjournals.cast.org.cn/joweb/gsyxb/CN/10.14062/j.issn.0454-5648.20220813
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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