{"title":"Cover Image, Volume 4, Issue 3, May 2025","authors":"","doi":"10.1002/bte2.12191","DOIUrl":null,"url":null,"abstract":"<p><b>Front Cover:</b> Transition metal molybdates have emerged as promising electrode materials for energy storage applications. In the article number BTE.20240073, D. S. Sawant, S. B. Kulkarni, D. P. Dubal, and G. M. Lohar present an innovative approach combining machine learning (ML) techniques to predict and analyze how structural, compositional, and synthesis parameters influence the electrochemical performance of molybdates. By identifying the critical factors that govern their energy storage behavior, the study offers valuable insights into the rational design of molybdate-based composites. The authors also review morphology-dependent supercapacitor performance, highlighting how the integration of experimental data with ML-driven optimization can accelerate the development of next-generation energy storage systems.\n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure></p>","PeriodicalId":8807,"journal":{"name":"Battery Energy","volume":"4 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bte2.12191","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Battery Energy","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/bte2.12191","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Front Cover: Transition metal molybdates have emerged as promising electrode materials for energy storage applications. In the article number BTE.20240073, D. S. Sawant, S. B. Kulkarni, D. P. Dubal, and G. M. Lohar present an innovative approach combining machine learning (ML) techniques to predict and analyze how structural, compositional, and synthesis parameters influence the electrochemical performance of molybdates. By identifying the critical factors that govern their energy storage behavior, the study offers valuable insights into the rational design of molybdate-based composites. The authors also review morphology-dependent supercapacitor performance, highlighting how the integration of experimental data with ML-driven optimization can accelerate the development of next-generation energy storage systems.
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