{"title":"Computational insights into the rational design of organic electrode materials for metal ion batteries","authors":"Xinyue Zhu, Youchao Yang, Xipeng Shu, Tianze Xu, Yu Jing","doi":"10.1002/wcms.1660","DOIUrl":null,"url":null,"abstract":"<p>Metal ion batteries (MIBs), represented by lithium ion batteries are important energy storage devices for storing renewable energy. Advanced development of MIBs depends on the exploration of efficient and sustainable electrode materials. Organic electrode materials (OEMs) with redox-active moieties are low-cost and eco-friendly alternatives to conventional inorganic electrode materials for MIBs. Computational simulation plays an important role in understanding the energy storage mechanism of different active functional groups and boosting the discovery of new OEMs for high-efficient MIBs. Here, we will review recent progress of OEMs and comprehensively survey factors that determine their electrochemical properties. Dependable computational methods to guide the design of OEMs are comprehensively discussed and machine learning is highlighted as an emerging method to reveal the underlying structure–performance relationship and facilitate screening of OEMs with high-efficiency. Finally, we summarize the available molecular design strategies to effectively improve the redox activity and stability of OEMs, and discuss challenges and opportunities of theoretical calculations of OEMs for MIBs.</p><p>This article is categorized under:\n </p>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"13 5","pages":""},"PeriodicalIF":16.8000,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wiley Interdisciplinary Reviews: Computational Molecular Science","FirstCategoryId":"92","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/wcms.1660","RegionNum":2,"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: 4
Abstract
Metal ion batteries (MIBs), represented by lithium ion batteries are important energy storage devices for storing renewable energy. Advanced development of MIBs depends on the exploration of efficient and sustainable electrode materials. Organic electrode materials (OEMs) with redox-active moieties are low-cost and eco-friendly alternatives to conventional inorganic electrode materials for MIBs. Computational simulation plays an important role in understanding the energy storage mechanism of different active functional groups and boosting the discovery of new OEMs for high-efficient MIBs. Here, we will review recent progress of OEMs and comprehensively survey factors that determine their electrochemical properties. Dependable computational methods to guide the design of OEMs are comprehensively discussed and machine learning is highlighted as an emerging method to reveal the underlying structure–performance relationship and facilitate screening of OEMs with high-efficiency. Finally, we summarize the available molecular design strategies to effectively improve the redox activity and stability of OEMs, and discuss challenges and opportunities of theoretical calculations of OEMs for MIBs.
期刊介绍:
Computational molecular sciences harness the power of rigorous chemical and physical theories, employing computer-based modeling, specialized hardware, software development, algorithm design, and database management to explore and illuminate every facet of molecular sciences. These interdisciplinary approaches form a bridge between chemistry, biology, and materials sciences, establishing connections with adjacent application-driven fields in both chemistry and biology. WIREs Computational Molecular Science stands as a platform to comprehensively review and spotlight research from these dynamic and interconnected fields.