C. D. Chavare, D. S. Sawant, S. V. Gaikwad, A. V. Fulari, H. R. Kulkarni, D. P. Dubal and G. M. Lohar
{"title":"镍钴磷酸盐/磷酸盐作为外置式超级电容器的理想电极材料:机器学习分析","authors":"C. D. Chavare, D. S. Sawant, S. V. Gaikwad, A. V. Fulari, H. R. Kulkarni, D. P. Dubal and G. M. Lohar","doi":"10.1039/D4TA07613C","DOIUrl":null,"url":null,"abstract":"<p >Recently, transition metal compounds containing phosphorous, such as metal phosphates and phosphides, have attracted great attention for fabrication of energy storage devices such as supercapacitors. Benefiting from their high ion conductivity, good chemical stability, and metalloid properties, metal phosphates and phosphides show promise to deliver excellent charge storage capacity. The present review provides a comprehensive summary of recent advancements in nickel cobalt phosphates and phosphides, including their charge storage mechanisms, structural information using different analytical tools and morphology (1D, 2D, and 3D)-dependent electrochemical performance. The electronic structures of nickel cobalt phosphate/phosphide are intentionally reviewed using density functional theory results. Furthermore, for the first time, we introduce machine learning analysis as a tool to explore different parameters and predict supercapacitor behaviour with respect to different experimental and electrochemical parameters. Machine learning technology enhances accuracy, saves time, and efficiently analyzes energy storage materials. Finally, the challenges and future perspectives to enhance the supercapacitor performance of nickel cobalt phosphates and phosphides are discussed.</p>","PeriodicalId":82,"journal":{"name":"Journal of Materials Chemistry A","volume":" 10","pages":" 6993-7054"},"PeriodicalIF":9.5000,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nickel cobalt phosphate/phosphide as a promising electrode material for extrinsic supercapacitors: machine learning analysis†\",\"authors\":\"C. D. Chavare, D. S. Sawant, S. V. Gaikwad, A. V. Fulari, H. R. Kulkarni, D. P. Dubal and G. M. Lohar\",\"doi\":\"10.1039/D4TA07613C\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >Recently, transition metal compounds containing phosphorous, such as metal phosphates and phosphides, have attracted great attention for fabrication of energy storage devices such as supercapacitors. Benefiting from their high ion conductivity, good chemical stability, and metalloid properties, metal phosphates and phosphides show promise to deliver excellent charge storage capacity. The present review provides a comprehensive summary of recent advancements in nickel cobalt phosphates and phosphides, including their charge storage mechanisms, structural information using different analytical tools and morphology (1D, 2D, and 3D)-dependent electrochemical performance. The electronic structures of nickel cobalt phosphate/phosphide are intentionally reviewed using density functional theory results. Furthermore, for the first time, we introduce machine learning analysis as a tool to explore different parameters and predict supercapacitor behaviour with respect to different experimental and electrochemical parameters. Machine learning technology enhances accuracy, saves time, and efficiently analyzes energy storage materials. Finally, the challenges and future perspectives to enhance the supercapacitor performance of nickel cobalt phosphates and phosphides are discussed.</p>\",\"PeriodicalId\":82,\"journal\":{\"name\":\"Journal of Materials Chemistry A\",\"volume\":\" 10\",\"pages\":\" 6993-7054\"},\"PeriodicalIF\":9.5000,\"publicationDate\":\"2025-01-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Materials Chemistry A\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://pubs.rsc.org/en/content/articlelanding/2025/ta/d4ta07613c\",\"RegionNum\":2,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Materials Chemistry A","FirstCategoryId":"88","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2025/ta/d4ta07613c","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
Nickel cobalt phosphate/phosphide as a promising electrode material for extrinsic supercapacitors: machine learning analysis†
Recently, transition metal compounds containing phosphorous, such as metal phosphates and phosphides, have attracted great attention for fabrication of energy storage devices such as supercapacitors. Benefiting from their high ion conductivity, good chemical stability, and metalloid properties, metal phosphates and phosphides show promise to deliver excellent charge storage capacity. The present review provides a comprehensive summary of recent advancements in nickel cobalt phosphates and phosphides, including their charge storage mechanisms, structural information using different analytical tools and morphology (1D, 2D, and 3D)-dependent electrochemical performance. The electronic structures of nickel cobalt phosphate/phosphide are intentionally reviewed using density functional theory results. Furthermore, for the first time, we introduce machine learning analysis as a tool to explore different parameters and predict supercapacitor behaviour with respect to different experimental and electrochemical parameters. Machine learning technology enhances accuracy, saves time, and efficiently analyzes energy storage materials. Finally, the challenges and future perspectives to enhance the supercapacitor performance of nickel cobalt phosphates and phosphides are discussed.
期刊介绍:
The Journal of Materials Chemistry A, B & C covers a wide range of high-quality studies in the field of materials chemistry, with each section focusing on specific applications of the materials studied. Journal of Materials Chemistry A emphasizes applications in energy and sustainability, including topics such as artificial photosynthesis, batteries, and fuel cells. Journal of Materials Chemistry B focuses on applications in biology and medicine, while Journal of Materials Chemistry C covers applications in optical, magnetic, and electronic devices. Example topic areas within the scope of Journal of Materials Chemistry A include catalysis, green/sustainable materials, sensors, and water treatment, among others.