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RESEARCH PAPER · ACS Materials Letters · 2021

Screening Topological Quantum Materials for Na-Ion Battery Cathode

Wei Wu, Qiang Sun

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Screening Topological Quantum Materials for Na-Ion Battery CathodeOriginalRecent advances in topological quantum anode materials for metal-ion batteries31Topological quantum materials for energy conversion and storage198Corrugated Layered Titanates as High-Voltage Cathode Materials for Potassium-Ion Batteries18The CrBr3 monolayer: Two dimension sodium ion battery anode material to characterize state-of-charge by magnetism5Screening Topological Quantum Cathode Materials for K-Ion Batteries by Graph Neural Network and First-Principles Calculations10Data-driven-aided strategies in battery lifecycle management: Prediction, monitoring, and optimization87Quantum Materials2Machine learning promotes the development of all-solid-state batteries35Predicting the ET(30) parameter of organic solvents via machine learning16Multi-output ensemble deep learning: A framework for simultaneous prediction of multiple electrode material properties24Machine learning for beyond Li-ion batteries: Powering the research39V4C3 MXene: a Type‐II Nodal Line Semimetal with Potential as High‐Performing Anode Material for Mg‐Ion Battery13Hard carbon for sodium-ion batteries: progress, strategies and future perspective320Co-free and low strain cathode materials for sodium-ion batteries: Machine learning-based materials discovery28Machine learning in energy storage material discovery and performance prediction77Artificial intelligence driven design of cathode materials for sodium-ion batteries using graph deep learning method41Machine learning-assisted design and prediction of materials for batteries based on alkali metals8High-throughput screening of phosphide compounds for potassium-ion conductive cathode application8Benchmarking Selected Density Functionals and Dispersion Corrections for MOF-5 and Its Derivatives5Computational discovery of metastable Na Mn O 2 polymorphs as high-performance cathodes with ultralow Na + migration barriers1Artificial intelligence empowering innovation in key materials for sodium-ion batteries: Machine learning driven design and optimization of cathode and anode materials59Artificial intelligence-driven paradigms for layered cathode materials: A systematic framework for multi-scale engineering2Machine learning in sodium-ion battery development: Critical perspectives on design innovation and applications2From Small Data to High Capacity: Symbolic Learning of Sodium-Ion Cathode Materials0Accelerating Electrolyte Discovery for Sodium-Ion Battery Through Property-Based Frameworks and Artificial Intelligence0

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  1. Recent advances in topological quantum anode materials for metal-ion batteries

    Journal of Power Sources · 2022-05-26

    Mohammed M. Obeid, Qiang Sun

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  2. Topological quantum materials for energy conversion and storage

    Nature Reviews Physics · 2022-07-11

    Huixia Luo, Peifeng Yu, Guowei Li, Kai Yan

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  3. Corrugated Layered Titanates as High-Voltage Cathode Materials for Potassium-Ion Batteries

    ACS Materials Letters · 2022-07-29

    Jiaying Liao, Qiao Hu, Xinru Sheng, Zhuangzhuang Zhang, Yifan Xu, Xiangyin Mo, Xiaosi Zhou

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  4. The CrBr3 monolayer: Two dimension sodium ion battery anode material to characterize state-of-charge by magnetism

    Applied Surface Science · 2023-03-21

    Pengju Ma, Jiaohong Shu, Xinxin Zhao, Yunjiu Cao, Lili Wang, Guanglong Chen, Jianbao Wu, Yiming Mi

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  5. Screening Topological Quantum Cathode Materials for K-Ion Batteries by Graph Neural Network and First-Principles Calculations

    ACS Applied Energy Materials · 2023-04-20

    Yongyi Wang, Jiahui Liu, Peng‐Hu Du, Zhili Sun, Qiang Sun

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  6. Data-driven-aided strategies in battery lifecycle management: Prediction, monitoring, and optimization

    Energy storage materials · 2023-04-23

    Liqianyun Xu, Feng Wu, Renjie Chen, Li Li

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  7. Quantum Materials

    Ullmann's Encyclopedia of Industrial Chemistry · 2023-05-29

    Quoc Hue Pho, Yiran Jiao, Yan Jiao, Wei Sun, Nelson Tansu A, Marek Wojnicki, Hasan Shabbir, Katarzyna Rogóż, Nam Nghiep Tran, David Lewis, Volker Hessel

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  8. Machine learning promotes the development of all-solid-state batteries

    Chinese Journal of Structural Chemistry · 2023-06-07

    Yong Long Qiu, Xu Zhang, Yun Tian, Zhen Ping Zhou

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  9. Predicting the ET(30) parameter of organic solvents via machine learning

    Chemical Physics Letters · 2023-06-15

    Vaneet Saini, Harsh Singh

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  10. Multi-output ensemble deep learning: A framework for simultaneous prediction of multiple electrode material properties

    Chemical Engineering Journal · 2023-09-25

    Hanqing Yu, Kaiyi Yang, Lisheng Zhang, Wentao Wang, Mengzheng Ouyang, Bin Ma, Shichun Yang, Junfu Li, Xinhua Liu

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  11. Machine learning for beyond Li-ion batteries: Powering the research

    Journal of Energy Storage · 2023-09-27

    Aysegul Kilic, Burcu Oral, Damla Eroğlu, Ramazan Yıldırım

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  12. V4C3 MXene: a Type‐II Nodal Line Semimetal with Potential as High‐Performing Anode Material for Mg‐Ion Battery

    ChemSusChem · 2023-11-27

    Ali Sufyan, Ghulam Abbas, Muhammad Sajjad, J. Andreas Larsson

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  13. Hard carbon for sodium-ion batteries: progress, strategies and future perspective

    Chemical Science · 2024-01-01

    Chun Du Wu, Yunrui Yang, Yinghao Zhang, Hui Fang Xu, Xiangxi He, Xingqiao Wu, Shulei Chou

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  14. Co-free and low strain cathode materials for sodium-ion batteries: Machine learning-based materials discovery

    Energy storage materials · 2024-04-12

    Minseon Kim, Woon‐Hong Yeo, Kyoungmin Min

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  15. Machine learning in energy storage material discovery and performance prediction

    Chemical Engineering Journal · 2024-05-16

    Guochang Huang, Fuqiang Huang, Wujie Dong

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  16. Artificial intelligence driven design of cathode materials for sodium-ion batteries using graph deep learning method

    Journal of Energy Storage · 2024-10-08

    Kong Meng, Kun Bai, Shaorui Sun

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  17. Machine learning-assisted design and prediction of materials for batteries based on alkali metals

    Physical Chemistry Chemical Physics · 2025-01-01

    Kexin Si, Zhipeng Sun, Huaxin Song, Xiangfen Jiang, Xuebin Wang

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  18. High-throughput screening of phosphide compounds for potassium-ion conductive cathode application

    Journal of Materials Informatics · 2025-03-11

    Yawen Li, Natalia A. Kabanova, Vladislav A. Blatov, Junjie Wang

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  19. Benchmarking Selected Density Functionals and Dispersion Corrections for MOF-5 and Its Derivatives

    Journal of Chemical Theory and Computation · 2025-07-14

    Joshua Edzards, Julia Santana-Andreo, Holger‐Dietrich Saßnick, Caterina Cocchi

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  20. Computational discovery of metastable Na Mn O 2 polymorphs as high-performance cathodes with ultralow Na + migration barriers

    Physical Review Applied · 2025-12-24

    Fukuan Wang, Chen Zhou, Busheng Wang, Yong Liu

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  21. Artificial intelligence empowering innovation in key materials for sodium-ion batteries: Machine learning driven design and optimization of cathode and anode materials

    Journal of Energy Chemistry · 2026-01-18

    Jun Cong, Shaohua Luo

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  22. Artificial intelligence-driven paradigms for layered cathode materials: A systematic framework for multi-scale engineering

    Nano Energy · 2026-04-22

    Jingguo Gao, Tao Huang, Yuan Zhang, Yuan Zhang, Bin Chen, Xiangzhong Ren, Jiangtao Hu, Qianling Zhang, Heping Xie

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  23. Machine learning in sodium-ion battery development: Critical perspectives on design innovation and applications

    Nano Research Energy · 2026-06-25

    Tianxin Peng, Biao Ran, Yi Zhong, Da Shu, Chaopeng Fu, Chao Yang

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  24. From Small Data to High Capacity: Symbolic Learning of Sodium-Ion Cathode Materials

    The Journal of Physical Chemistry Letters · 2026-08-28

    Kong Meng, Andrey S. Vasenko, Evgueni V. Chulkov, Run Long

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  25. Accelerating Electrolyte Discovery for Sodium-Ion Battery Through Property-Based Frameworks and Artificial Intelligence

    Electrochemical Energy Reviews · 2026-09-21

    Li Ting Gao, Hossein Mashhadimoslem, yi He, Weinan Zhao, Qiran Lu, Sushanta Kumar Mitra, Zhansheng Guo, Aiping Yu

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