Computational insights into the rational design of organic electrode materials for metal ion batteries

IF 16.8 2区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Xinyue Zhu, Youchao Yang, Xipeng Shu, Tianze Xu, Yu Jing
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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.

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Abstract Image

金属离子电池有机电极材料合理设计的计算见解
以锂离子电池为代表的金属离子电池是储存可再生能源的重要储能装置。MIB的先进发展取决于对高效和可持续电极材料的探索。具有氧化还原活性部分的有机电极材料(OEM)是用于MIB的传统无机电极材料的低成本且环保的替代品。计算模拟在理解不同活性官能团的储能机制和促进发现高效MIB的新原始设备制造商方面发挥着重要作用。在这里,我们将回顾原始设备制造商的最新进展,并全面调查决定其电化学性能的因素。全面讨论了指导原始设备制造商设计的可靠计算方法,并强调机器学习是一种新兴的方法,可以揭示潜在的结构-性能关系,促进高效筛选原始设备制造商。最后,我们总结了有效提高原始设备制造商氧化还原活性和稳定性的可用分子设计策略,并讨论了原始设备制造商理论计算MIB的挑战和机遇。本文分为以下几类:
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Wiley Interdisciplinary Reviews: Computational Molecular Science
Wiley Interdisciplinary Reviews: Computational Molecular Science CHEMISTRY, MULTIDISCIPLINARY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
28.90
自引率
1.80%
发文量
52
审稿时长
6-12 weeks
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.
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