一种数据驱动方法快速筛选高性能水系锌离子电池中金属掺杂二氧化锰正极

引用本文: 单昱呈, 许立明, 孙鹏, 朱之婧, 王成龙, 黎晋良, 杨光, 潘丽坤. 一种数据驱动方法快速筛选高性能水系锌离子电池中金属掺杂二氧化锰正极[J]. 物理化学学报, 2026, 42(7): 100232. doi: 10.1016/j.actphy.2025.100232 shu

Citation: Yucheng Shan, Liming Xu, Peng Sun, Zhijing Zhu, Chenglong Wang, Jinliang Li, Guang Yang, Likun Pan. A data-driven approach for rapid revealing of metal doping in MnO₂ cathodes for high-performance aqueous zinc-ion batteries[J]. Acta Physico-Chimica Sinica, 2026, 42(7): 100232. doi: 10.1016/j.actphy.2025.100232 shu

一种数据驱动方法快速筛选高性能水系锌离子电池中金属掺杂二氧化锰正极

单昱呈 ^1, ,
许立明 ^3, ,
孙鹏 ^2, ,
朱之婧 ^4, ,
王成龙 ^{1,
,} ,
黎晋良 ^{2,
,} ,
杨光 ^1, ,
潘丽坤 ^{1,
,}

1.
华东师范大学物理学院, 上海磁共振重点实验室, 医学磁共振与分子影像技术研究院, 上海 200241;
2.
暨南大学物理与光电工程学院物理系, 广东省真空镀膜技术与新能源材料工程技术研究中心, 思源实验室, 广东广州 510632;
3.
江西科技师范大学, 柔性电子江西省重点实验室, 江西南昌 330013;
4.
上海理工大学材料与化学学院, 上海 200093

通讯作者: 王成龙,E-mail:clwang@phy.ecnu.edu.cn; 黎晋良,E-mail:lijinliang@email.jnu.edu.cn; 潘丽坤,E-mail:lkpan@phy.ecnu.edu.cn

基金项目:
上海市自然科学基金(25ZR1401102)，广州市科技计划项目(SL2024A03J00326)资助。本研究工作得到华东师范大学公共创新服务平台高性能计算中心的算力支持。

摘要: 金属掺杂是水系锌离子电池二氧化锰(MnO₂)正极的重要改性策略，其中参数的选择直接影响电化学性能。然而，掺杂元素类型、浓度以及合成条件与电化学性能之间的复杂相互关系，使得优化MnO₂正极以获得优异电化学性能仍然具有挑战性。为了高效研究金属掺杂MnO₂的性能，我们提出了一种基于文献数据的机器学习模型。在特征工程和模型选择后，我们发现极限梯度提升模型(XGB)在测试集上R²达到了0.921的高预测精度。在此之后，特征重要性分析进一步指导了一系列实验的设计，这些实验与密度泛函理论计算一致地验证了模型的准确性和可靠性。在从多个角度验证可行性后，我们进一步构建了基于该模型的在线性能预测平台，为后续研究人员提供了一个便捷的工具，帮助他们获得指导和启发。我们相信，这项工作为金属掺杂MnO₂在能源存储领域的研究提供了新的视角和框架。

关键词:

English

A data-driven approach for rapid revealing of metal doping in MnO₂ cathodes for high-performance aqueous zinc-ion batteries

Yucheng Shan ^1, ,
Liming Xu ^3, ,
Peng Sun ^2, ,
Zhijing Zhu ^4, ,
Chenglong Wang ^{1,
,} ,
Jinliang Li ^{2,
,} ,
Guang Yang ^1, ,
Likun Pan ^{1,
,}

1.
Shanghai Key Laboratory of Magnetic Resonance, School of Physics, Institute of Magnetic Resonance and Molecular Imaging in Medicine, East China Normal University, Shanghai 200241, China;
2.
Siyuan Laboratory, Guangdong Provincial Engineering Technology Research Center of Vacuum Coating Technologies and New Energy Materials, Department of Physics, College of Physics & Optoelectronic Engineering, Jinan University, Guangzhou 510632, Guangdong Province, China;
3.
Jiangxi Provincial Key Laboratory of Flexible Electronics, Jiangxi Science and Technology Normal University, Nanchang 330013, Jiangxi Province, China;
4.
School of Materials and Chemistry, University of Shanghai for Science and Technology, Shanghai 200093, China

Corresponding author: Chenglong Wang, ; Jinliang Li, ; Likun Pan,

Received Date: 01 October 2025
Accepted Date: 17 December 2025
Revised Date: 02 December 2025

Abstract: Metal doping is a key modification strategy for MnO₂ cathodes in aqueous zinc-ion batteries, with parameter selection directly governing the resulting electrochemical performance. However, the intricate interplay among dopant type and concentration, synthesis conditions, and electrochemical performance renders the optimization of MnO₂ cathodes for high electrochemical properties still elusive. Traditional trial-and-error experimental screening is time-consuming and expensive, and developing a unified guideline on the design of metal-doped MnO₂ remains a long-standing challenge. To efficiently study the performance of metal-doped MnO₂, we proposed a machine learning (ML) model driven by data from the literature. A dataset was constructed from 36 articles covering 21 dopant elements, integrating elemental descriptors, synthesis parameters, and electrochemical testing conditions. After feature filtering and model evaluation, the extreme gradient boosting (XGB) model achieves a high predictive accuracy with an R² of 0.921 on the test set. Beyond prediction, model interpretability using Shapley additive explanations (SHAP) analysis identifies the dominant factors affecting capacity, revealing the influence of current density, dopant ratio, and molecular weight. Feature importance analysis further guided the design of a series of experiments that validated the accuracy and reliability of the model. Experiments on Fe- and Ni-doped MnO₂ cathodes confirmed the ability of metal doping to enhance specific capacity, and the model achieved a mean absolute error (MAE) below 12 mAh g^-1 for all cases. Density functional theory (DFT) calculations further verified the molecular-level mechanism of metal doping by demonstrating that dopant incorporation modulates the electronic structure of MnO₂ and narrows the bandgap, improving conductivity. The consistency between the ML results, experimental validation, and theoretical calculations highlights the robustness of the proposed framework. Having established the feasibility from multiple perspectives, we further deployed a performance prediction platform based on this model, providing a convenient tool for researchers to rapidly estimate the specific capacity of metal-doped MnO₂ under user-defined conditions. This work demonstrates a comprehensive data-driven paradigm that integrates ML, experimental validation, and theoretical calculations. We believe that this approach provides a new strategy and framework for the rational design of high-performance MnO₂ cathodes, and is broadly applicable for accelerating the discovery of other metal-doped energy storage materials.

Key words:

1. [1]
  Y. Li, H. Xu, X.D. Li, X. Lin, H.Y. Zhao, Y.J. Zhang, K.N. Hui, J.L. Li, L.K. Pan, Adv. Sci. 12 (2025) e07071, https://doi.org/10.1002/advs.202507071Y. Li, H. Xu, X.D. Li, X. Lin, H.Y. Zhao, Y.J. Zhang, K.N. Hui, J.L. Li, L.K. Pan, Adv. Sci. 12 (2025) e07071, https://doi.org/10.1002/advs.202507071
2. [2]
  H.T. Xu, W.Y. Yang, M. Li, H.B. Liu, S.Q. Gong, F. Zhao, C.L. Li, J.J. Qi, H.H. Wang, W.C. Peng, et al., Small 20 (2024) 2310972, https://doi.org/10.1002/smll.202310972H.T. Xu, W.Y. Yang, M. Li, H.B. Liu, S.Q. Gong, F. Zhao, C.L. Li, J.J. Qi, H.H. Wang, W.C. Peng, et al., Small 20 (2024) 2310972, https://doi.org/10.1002/smll.202310972
3. [3]
  Y. Li, H. Xu, X.Y. Xuan, Y. J. Zhang, H.Y. Zhao, J.L. Li, M. Xu, L.K. Pan, Chem. Eng. J. 505 (2025) 158934, https://doi.org/10.1016/j.cej.2024.158934Y. Li, H. Xu, X.Y. Xuan, Y. J. Zhang, H.Y. Zhao, J.L. Li, M. Xu, L.K. Pan, Chem. Eng. J. 505 (2025) 158934, https://doi.org/10.1016/j.cej.2024.158934
4. [4]
  Z. Liu, M. Qin, B. Fu, M. Li, S. Liang, G. Fang, Angew. Chem. Int. Ed. 64 (2025) e202417049, https://doi.org/10.1002/anie.202417049Z. Liu, M. Qin, B. Fu, M. Li, S. Liang, G. Fang, Angew. Chem. Int. Ed. 64 (2025) e202417049, https://doi.org/10.1002/anie.202417049
5. [5]
  P.C. Ruan, S.Q. Liang, B.G. Lu, H.J. Fan, J. Zhou, Angew. Chem. Int. Ed. 61 (2022) e202200598, https://doi.org/10.1002/anie.202200598P.C. Ruan, S.Q. Liang, B.G. Lu, H.J. Fan, J. Zhou, Angew. Chem. Int. Ed. 61 (2022) e202200598, https://doi.org/10.1002/anie.202200598
6. [6]
  N. Wang, X.L. Dong, B.L. Wang, Z.W. Guo, Z. Wang, R.H. Wang, X. Qiu, Y.G. Wang, Angew. Chem. Int. Ed. 59 (2020) 14577, https://doi.org/10.1002/anie.202005603N. Wang, X.L. Dong, B.L. Wang, Z.W. Guo, Z. Wang, R.H. Wang, X. Qiu, Y.G. Wang, Angew. Chem. Int. Ed. 59 (2020) 14577, https://doi.org/10.1002/anie.202005603
7. [7]
  V. Mathew, B. Sambandam, S. Kim, S. Kim, S. Park, S. Lee, M.H. Alfaruqi, V. Soundharrajan, S. Islam, D.Y. Putro, et al., ACS Energy Lett. 5 (2020) 2376, https://doi.org/10.1021/acsenergylett.0c00740V. Mathew, B. Sambandam, S. Kim, S. Kim, S. Park, S. Lee, M.H. Alfaruqi, V. Soundharrajan, S. Islam, D.Y. Putro, et al., ACS Energy Lett. 5 (2020) 2376, https://doi.org/10.1021/acsenergylett.0c00740
8. [8]
  Q.L. Ma, T.B. Song, T.L. He, X.R. Zhang, H.M. Xiong, Acta Phys. Chim. Sin. 41 (2025) 100106, https://doi.org/10.1016/j.actphy.2025.100106Q.L. Ma, T.B. Song, T.L. He, X.R. Zhang, H.M. Xiong, Acta Phys. Chim. Sin. 41 (2025) 100106, https://doi.org/10.1016/j.actphy.2025.100106
9. [9]
  Z.H. Wang, M.W. Chang, H.S. Geng, P. Cui, P.C. Song, F. Hu, J.H. You, K. Zhu, J. Electroanal. Chem. 989 (2025) 119210, https://doi.org/10.1016/j.jelechem.2025.119210Z.H. Wang, M.W. Chang, H.S. Geng, P. Cui, P.C. Song, F. Hu, J.H. You, K. Zhu, J. Electroanal. Chem. 989 (2025) 119210, https://doi.org/10.1016/j.jelechem.2025.119210
10. [10]
  W.L. Zhang, S.Y. Niu, Y. Wang, Z.Y. Wang, Y.M. Wang, N. Ju, X.Y. Liu, Y.G. Jia, H.B. Sun, Chem. Commun. 60 (2024) 9586, https://doi.org/10.1039/d4cc02769hW.L. Zhang, S.Y. Niu, Y. Wang, Z.Y. Wang, Y.M. Wang, N. Ju, X.Y. Liu, Y.G. Jia, H.B. Sun, Chem. Commun. 60 (2024) 9586, https://doi.org/10.1039/d4cc02769h
11. [11]
  Y. K. Li, Z.M. Huang, P.K. Kalambate, Y. Zhong, Z.M. Huang, M.L. Xie, Y. Shen, Y.H. Huang, Nano Energy 60 (2019) 752, https://doi.org/10.1016/j.nanoen.2019.04.009Y. K. Li, Z.M. Huang, P.K. Kalambate, Y. Zhong, Z.M. Huang, M.L. Xie, Y. Shen, Y.H. Huang, Nano Energy 60 (2019) 752, https://doi.org/10.1016/j.nanoen.2019.04.009
12. [12]
  S.L. Tang, C.L. Wang, X.J. Pu, X.K. Gu, Z.X. Chen, Acta Phys. Chim. Sin. 39 (2023) 2212037, https://doi.org/10.3866/PKU.WHXB202212037S.L. Tang, C.L. Wang, X.J. Pu, X.K. Gu, Z.X. Chen, Acta Phys. Chim. Sin. 39 (2023) 2212037, https://doi.org/10.3866/PKU.WHXB202212037
13. [13]
  D.D. Qin, J.Y. Ding, C. Liang, Q. Liu, L.G. Feng, Y. Luo, G.Z. Hu, J. Luo, X.J. Liu, Acta Phys. Chim. Sin. 40 (2024) 2310034, https://doi.org/10.3866/pku.Whxb202310034D.D. Qin, J.Y. Ding, C. Liang, Q. Liu, L.G. Feng, Y. Luo, G.Z. Hu, J. Luo, X.J. Liu, Acta Phys. Chim. Sin. 40 (2024) 2310034, https://doi.org/10.3866/pku.Whxb202310034
14. [14]
  J.J. Wang, J.G. Wang, H.Y. Liu, C.G. Wei, F.Y. Kang, J. Mater. Chem. A 7 (2019) 13727, https://doi.org/10.1039/c9ta03541aJ.J. Wang, J.G. Wang, H.Y. Liu, C.G. Wei, F.Y. Kang, J. Mater. Chem. A 7 (2019) 13727, https://doi.org/10.1039/c9ta03541a
15. [15]
  Y. Zheng, D. Chen, Y. Zhao, H. Bao, Y. Sun, J. Power Sources 625 (2025) 235658, https://doi.org/10.1016/j.jpowsour.2024.235658Y. Zheng, D. Chen, Y. Zhao, H. Bao, Y. Sun, J. Power Sources 625 (2025) 235658, https://doi.org/10.1016/j.jpowsour.2024.235658
16. [16]
  S.Q. Liu, B.Y. Wang, X. Zhang, S. Zhao, Z.H. Zhang, H.J. Yu, Matter 4 (2021) 1511, https://doi.org/10.1016/j.matt.2021.02.023S.Q. Liu, B.Y. Wang, X. Zhang, S. Zhao, Z.H. Zhang, H.J. Yu, Matter 4 (2021) 1511, https://doi.org/10.1016/j.matt.2021.02.023
17. [17]
  D. Guo, J. Sun, C. Wang, H. Quan, H. Lu, Y. Wei, C. Sun, S. Wang, Angew. Chem. Int. Ed. 64 (2025) e202505102, https://doi.org/10.1002/anie.202505102D. Guo, J. Sun, C. Wang, H. Quan, H. Lu, Y. Wei, C. Sun, S. Wang, Angew. Chem. Int. Ed. 64 (2025) e202505102, https://doi.org/10.1002/anie.202505102
18. [18]
  Y. Hu, Z. Liu, L. Li, S. Guo, X. Xie, Z. Luo, G. Fang, S. Liang, Natl. Sci. Rev. 10 (2023) nwad220, https://doi.org/10.1093/nsr/nwad220Y. Hu, Z. Liu, L. Li, S. Guo, X. Xie, Z. Luo, G. Fang, S. Liang, Natl. Sci. Rev. 10 (2023) nwad220, https://doi.org/10.1093/nsr/nwad220
19. [19]
  Y.Q. Jiang, D.L. Ba, Y.Y. Li, J.P. Liu, Adv. Sci. 7 (2020) 1902795, https://doi.org/10.1002/advs.201902795Y.Q. Jiang, D.L. Ba, Y.Y. Li, J.P. Liu, Adv. Sci. 7 (2020) 1902795, https://doi.org/10.1002/advs.201902795
20. [20]
  J.J. Wang, J.G. Wang, H.Y. Liu, Z.Y. You, Z. Li, F.Y. Kang, B.Q. Wei, Adv. Funct. Mater. 31 (2021) 2007397, https://doi.org/10.1002/adfm.202007397J.J. Wang, J.G. Wang, H.Y. Liu, Z.Y. You, Z. Li, F.Y. Kang, B.Q. Wei, Adv. Funct. Mater. 31 (2021) 2007397, https://doi.org/10.1002/adfm.202007397
21. [21]
  M. Karbak, M. Baazizi, S. Sayah, C. Autret-Lambert, Y. Tison, H. Martinez, T. Chafik, F. Ghamouss, J. Mater. Chem. A 11 (2023) 2634, https://doi.org/10.1039/d2ta07838dM. Karbak, M. Baazizi, S. Sayah, C. Autret-Lambert, Y. Tison, H. Martinez, T. Chafik, F. Ghamouss, J. Mater. Chem. A 11 (2023) 2634, https://doi.org/10.1039/d2ta07838d
22. [22]
  X.H. Chen, P.C. Ruan, X.W. Wu, S.Q. Liang, J. Zhou, Acta Phys. Chim. Sin. 38 (2022), 2111003 https://doi.org/10.3866/pku.Whxb202111003X.H. Chen, P.C. Ruan, X.W. Wu, S.Q. Liang, J. Zhou, Acta Phys. Chim. Sin. 38 (2022), 2111003 https://doi.org/10.3866/pku.Whxb202111003
23. [23]
  J. Hua, X.W. Wu, F.X. Xie, M.M. Wu, Surf. Interfaces 62 (2025) 106312, https://doi.org/10.1016/j.surfin.2025.106312J. Hua, X.W. Wu, F.X. Xie, M.M. Wu, Surf. Interfaces 62 (2025) 106312, https://doi.org/10.1016/j.surfin.2025.106312
24. [24]
  Q.G. Li, C. Wang, Y. Zhu, W.Z. Du, W.X. Liu, M. Yao, Y.Q. Wang, Y.M. Qian, S.J. Feng, Chem. Eng. J. 485 (2024) 150077, https://doi.org/10.1016/j.cej.2024.150077Q.G. Li, C. Wang, Y. Zhu, W.Z. Du, W.X. Liu, M. Yao, Y.Q. Wang, Y.M. Qian, S.J. Feng, Chem. Eng. J. 485 (2024) 150077, https://doi.org/10.1016/j.cej.2024.150077
25. [25]
  X. Li, J. Qu, J. Xu, S. Zhang, X. Wang, X. Wang, S. Dai, J. Electroanal. Chem. 895 (2021) 115529, https://doi.org/10.1016/j.jelechem.2021.115529X. Li, J. Qu, J. Xu, S. Zhang, X. Wang, X. Wang, S. Dai, J. Electroanal. Chem. 895 (2021) 115529, https://doi.org/10.1016/j.jelechem.2021.115529
26. [26]
  Q. Xie, G. Cheng, T. Xue, L. Huang, S. Chen, Y. Sun, M. Sun, H. Wang, L. Yu, Mater. Today Energy 24 (2022) 100934, https://doi.org/10.1016/j.mtener.2021.100934Q. Xie, G. Cheng, T. Xue, L. Huang, S. Chen, Y. Sun, M. Sun, H. Wang, L. Yu, Mater. Today Energy 24 (2022) 100934, https://doi.org/10.1016/j.mtener.2021.100934
27. [27]
  J. Tan, T. Feng, S. Hu, Y. Liang, S. Zhang, Z. Xu, H. Zhou, M. Wu, Appl. Surf. Sci. 604 (2022) 154578, https://doi.org/10.1016/j.apsusc.2022.154578J. Tan, T. Feng, S. Hu, Y. Liang, S. Zhang, Z. Xu, H. Zhou, M. Wu, Appl. Surf. Sci. 604 (2022) 154578, https://doi.org/10.1016/j.apsusc.2022.154578
28. [28]
  Q. Zhang, H. Fan, Q. Liu, Y. Wu, E. Wang, J. Mater. Chem. A 12 (2024) 8167, https://doi.org/10.1039/d3ta07587gQ. Zhang, H. Fan, Q. Liu, Y. Wu, E. Wang, J. Mater. Chem. A 12 (2024) 8167, https://doi.org/10.1039/d3ta07587g
29. [29]
  R. Han, Y. Pan, C. Du, Y. Xiang, Y. Wang, H. Zhu, C. Yin, J. Energy Storage 80 (2024) 110250, https://doi.org/10.1016/j.est.2023.110250R. Han, Y. Pan, C. Du, Y. Xiang, Y. Wang, H. Zhu, C. Yin, J. Energy Storage 80 (2024) 110250, https://doi.org/10.1016/j.est.2023.110250
30. [30]
  F.W. Fenta, B.W. Olbasa, M.-C. Tsai, N.T. Temesgen, W.-H. Huang, T.M. Tekaligne, Y. Nikodimos, S.-H. Wu, W.-N. Su, H. Dai, et al., J. Power Sources 548 (2022) 232010, https://doi.org/10.1016/j.jpowsour.2022.232010F.W. Fenta, B.W. Olbasa, M.-C. Tsai, N.T. Temesgen, W.-H. Huang, T.M. Tekaligne, Y. Nikodimos, S.-H. Wu, W.-N. Su, H. Dai, et al., J. Power Sources 548 (2022) 232010, https://doi.org/10.1016/j.jpowsour.2022.232010
31. [31]
  Y. Ma, M. Xu, R. Liu, H. Xiao, Y. Liu, X. Wang, Y. Huang, G. Yuan, Energy Storage Mater. 48 (2022) 212, https://doi.org/10.1016/j.ensm.2022.03.024Y. Ma, M. Xu, R. Liu, H. Xiao, Y. Liu, X. Wang, Y. Huang, G. Yuan, Energy Storage Mater. 48 (2022) 212, https://doi.org/10.1016/j.ensm.2022.03.024
32. [32]
  G. Liu, Q.G. Chi, Y.Q. Zhang, Q.G. Chen, C.H. Zhang, K. Zhu, D.X. Cao, Chem. Commun. 54 (2018) 9474, https://doi.org/10.1039/c8cc05366aG. Liu, Q.G. Chi, Y.Q. Zhang, Q.G. Chen, C.H. Zhang, K. Zhu, D.X. Cao, Chem. Commun. 54 (2018) 9474, https://doi.org/10.1039/c8cc05366a
33. [33]
  G.D. Miao, Z. Wang, F. Sun, Y. Liu, F.X. Lin, Y.X. Fang, X. Yang, P. Li, X.H. Qu, J. Colloid Interface Sci. 693 (2025) 137636, https://doi.org/10.1016/j.jcis.2025.137636G.D. Miao, Z. Wang, F. Sun, Y. Liu, F.X. Lin, Y.X. Fang, X. Yang, P. Li, X.H. Qu, J. Colloid Interface Sci. 693 (2025) 137636, https://doi.org/10.1016/j.jcis.2025.137636
34. [34]
  T. Le, E.S. Takeuchi, K.J. Takeuchi, A.C. Marschilok, P. Liu, Energy Storage 6 (2024) e663, https://doi.org/10.1002/est2.633T. Le, E.S. Takeuchi, K.J. Takeuchi, A.C. Marschilok, P. Liu, Energy Storage 6 (2024) e663, https://doi.org/10.1002/est2.633
35. [35]
  H. Wang, Y. Zhu, J.L. Li, X.J. Liu, Y.C. Ma, Y.F. Yao, J. Zhang, L.K. Pan, J. Mater. Chem. A 13 (2025) 17197, https://doi.org/10.1039/d5ta00922gH. Wang, Y. Zhu, J.L. Li, X.J. Liu, Y.C. Ma, Y.F. Yao, J. Zhang, L.K. Pan, J. Mater. Chem. A 13 (2025) 17197, https://doi.org/10.1039/d5ta00922g
36. [36]
  T.P. Hu, H.C. Huang, G.B. Zhou, X.Y. Wang, J.X. Zhu, Z. Cheng, F. J. Fu, X. X. Wang, F. Z. Dai, K. Yu, et al., Nat. Commun. 16 (2025) 7379, https://doi.org/10.1038/s41467-025-62824-5T.P. Hu, H.C. Huang, G.B. Zhou, X.Y. Wang, J.X. Zhu, Z. Cheng, F. J. Fu, X. X. Wang, F. Z. Dai, K. Yu, et al., Nat. Commun. 16 (2025) 7379, https://doi.org/10.1038/s41467-025-62824-5
37. [37]
  R.R. Sharma, V. Venkatkrishna, V. Balakrishna, S. Ganguly, Adv. Eng. Mater. 27 (2025) 2402584, https://doi.org/10.1002/adem.202402584R.R. Sharma, V. Venkatkrishna, V. Balakrishna, S. Ganguly, Adv. Eng. Mater. 27 (2025) 2402584, https://doi.org/10.1002/adem.202402584
38. [38]
  G.S. Xu, M.X. Jiang, J.L. Li, X.Y. Xuan, J.B. Li, T. Lu, L.K. Pan, Energy Storage Mater. 72 (2024) 103710, https://doi.org/10.1016/j.ensm.2024.103710G.S. Xu, M.X. Jiang, J.L. Li, X.Y. Xuan, J.B. Li, T. Lu, L.K. Pan, Energy Storage Mater. 72 (2024) 103710, https://doi.org/10.1016/j.ensm.2024.103710
39. [39]
  G.S. Xu, Y. Li, J.F. Li, J.L. Li, X.J. Liu, C.L. Wang, W.J. Mai, G. Yang, L.K. Pan, Angew. Chem. Int. Ed. 64 (2025) e202511389, https://doi.org/10.1002/anie.202511389G.S. Xu, Y. Li, J.F. Li, J.L. Li, X.J. Liu, C.L. Wang, W.J. Mai, G. Yang, L.K. Pan, Angew. Chem. Int. Ed. 64 (2025) e202511389, https://doi.org/10.1002/anie.202511389
40. [40]
  H. Wang, Y.Q. Li, X.Y. Xuan, K. Wang, Y.F. Yao, L.K. Pan, Environ. Sci. Technol. 59 (2025) 6361, https://doi.org/10.1021/acs.est.5c00390H. Wang, Y.Q. Li, X.Y. Xuan, K. Wang, Y.F. Yao, L.K. Pan, Environ. Sci. Technol. 59 (2025) 6361, https://doi.org/10.1021/acs.est.5c00390
41. [41]
  G. Xu, Y. Zhang, M. Jiang, J. Li, H. Sun, J. Li, T. Lu, C. Wang, G. Yang, L. Pan, Chem. Eng. J. 476 (2023) 146676, https://doi.org/10.1016/j.cej.2023.146676G. Xu, Y. Zhang, M. Jiang, J. Li, H. Sun, J. Li, T. Lu, C. Wang, G. Yang, L. Pan, Chem. Eng. J. 476 (2023) 146676, https://doi.org/10.1016/j.cej.2023.146676
42. [42]
  H.R. Luo, Q.Z. Gou, Y.J. Zheng, K.X. Wang, R.D. Yuan, S.D. Zhang, W. Fang, Z. Luogu, Y.Z. Hu, H.P. Mei, et al., ACS Nano 19 (2025) 2427, https://doi.org/10.1021/acsnano.4c13312H.R. Luo, Q.Z. Gou, Y.J. Zheng, K.X. Wang, R.D. Yuan, S.D. Zhang, W. Fang, Z. Luogu, Y.Z. Hu, H.P. Mei, et al., ACS Nano 19 (2025) 2427, https://doi.org/10.1021/acsnano.4c13312
43. [43]
  Y. Shang, V. Kundi, I. Pal, H.N. Kim, H.Y. Zhong, P. Kumar, D. Kundu, Adv. Mater. 36 (2024) 2309212, https://doi.org/10.1002/adma.202309212Y. Shang, V. Kundi, I. Pal, H.N. Kim, H.Y. Zhong, P. Kumar, D. Kundu, Adv. Mater. 36 (2024) 2309212, https://doi.org/10.1002/adma.202309212
44. [44]
  M. Kim, M. Lee, I. Choi, J. Oh, S. Paik, A. Han, S. Lee, H. Hwang, J. Na, K.W. Nam, Small 21 (2025) 2411632, https://doi.org/10.1002/smll.202411632M. Kim, M. Lee, I. Choi, J. Oh, S. Paik, A. Han, S. Lee, H. Hwang, J. Na, K.W. Nam, Small 21 (2025) 2411632, https://doi.org/10.1002/smll.202411632
45. [45]
  J.F. Cai, Z.L. Wang, S.C. Wu, Y.Q. Han, J.J. Li, Energy Storage Mater. 42 (2021) 277, https://doi.org/10.1016/j.ensm.2021.07.042J.F. Cai, Z.L. Wang, S.C. Wu, Y.Q. Han, J.J. Li, Energy Storage Mater. 42 (2021) 277, https://doi.org/10.1016/j.ensm.2021.07.042
46. [46]
  Y.S. Wudil, M.A. Gondal, M.A. Al-Osta, ACS Appl. Mater. Interfaces 17 (2025) 10603, https://doi.org/10.1021/acsami.4c18556Y.S. Wudil, M.A. Gondal, M.A. Al-Osta, ACS Appl. Mater. Interfaces 17 (2025) 10603, https://doi.org/10.1021/acsami.4c18556
47. [47]
  N.A. Chowdhury, L.N.A. Henderson, S. Yaser, O.P. Oyeku, M.M. Tresa, C. Kundu, J. Thomas, Phys. Chem. Chem. Phys. 27 (2025) 16636, https://doi.org/10.1039/D5CP01218JN.A. Chowdhury, L.N.A. Henderson, S. Yaser, O.P. Oyeku, M.M. Tresa, C. Kundu, J. Thomas, Phys. Chem. Chem. Phys. 27 (2025) 16636, https://doi.org/10.1039/D5CP01218J
48. [48]
  L. Zhou, A. M. Yao, Y. Wu, Z. Hu, Y. Huang, Z. Hong, Adv. Theor. Simul. 4 (2021) 2100196, https://doi.org/10.1002/adts.202100196L. Zhou, A. M. Yao, Y. Wu, Z. Hu, Y. Huang, Z. Hong, Adv. Theor. Simul. 4 (2021) 2100196, https://doi.org/10.1002/adts.202100196
49. [49]
  H. Wang, C.L. Wang, J.F. Li, Y.Q. Li, Y. Liu, Z.Q. Chen, X.J. Liu, G. Yang, L.K. Pan, Sep. Purif. Technol. 376 (2025) 134181, https://doi.org/10.1016/j.seppur.2025.134181H. Wang, C.L. Wang, J.F. Li, Y.Q. Li, Y. Liu, Z.Q. Chen, X.J. Liu, G. Yang, L.K. Pan, Sep. Purif. Technol. 376 (2025) 134181, https://doi.org/10.1016/j.seppur.2025.134181
50. [50]
  H. Wang, M.X. Jiang, G.S. Xu, C.L. Wang, X.T. Xu, Y. Liu, Y.Q. Li, T. Lu, G. Yang, L.K. Pan, Small 20 (2024) 2401214, https://doi.org/10.1002/smll.202401214H. Wang, M.X. Jiang, G.S. Xu, C.L. Wang, X.T. Xu, Y. Liu, Y.Q. Li, T. Lu, G. Yang, L.K. Pan, Small 20 (2024) 2401214, https://doi.org/10.1002/smll.202401214
51. [51]
  X. Guo, J. Zhou, C. Bai, X. Li, G. Fang, S. Liang, Mater. Today Energy 16 (2020) 100396, https://doi.org/10.1016/j.mtener.2020.100396X. Guo, J. Zhou, C. Bai, X. Li, G. Fang, S. Liang, Mater. Today Energy 16 (2020) 100396, https://doi.org/10.1016/j.mtener.2020.100396
52. [52]
  W. Zhao, Q. Kong, X. Wu, X. An, J. Zhang, X. Liu, W. Yao, Appl. Surf. Sci. 605 (2022) 154685, https://doi.org/10.1016/j.apsusc.2022.154685W. Zhao, Q. Kong, X. Wu, X. An, J. Zhang, X. Liu, W. Yao, Appl. Surf. Sci. 605 (2022) 154685, https://doi.org/10.1016/j.apsusc.2022.154685
53. [53]
  L. Breiman, Mach. Learn. 45 (2001) 5, https://doi.org/10.1023/A:1010933404324L. Breiman, Mach. Learn. 45 (2001) 5, https://doi.org/10.1023/A:1010933404324
54. [54]
  C. Cortes, V. Vapnik, Mach. Learn. 20 (1995) 273, https://doi.org/10.1007/BF00994018C. Cortes, V. Vapnik, Mach. Learn. 20 (1995) 273, https://doi.org/10.1007/BF00994018
55. [55]
  T. Chen, C. Guestrin, XGBoost: a scalable tree boosting system, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD, San Francisco, CA, USA, 2016, pp. 785–794 August 13–17, 2016. New York: ACM, 2016.T. Chen, C. Guestrin, XGBoost: a scalable tree boosting system, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD, San Francisco, CA, USA, 2016, pp. 785–794 August 13–17, 2016. New York: ACM, 2016.
56. [56]
  R. Tian, S.-H. Park, P.J. King, G. Cunningham, J. Coelho, V. Nicolosi, J.N. Coleman, Nat. Commun. 10 (2019) 1933, https://doi.org/10.1038/s41467-019-09792-9R. Tian, S.-H. Park, P.J. King, G. Cunningham, J. Coelho, V. Nicolosi, J.N. Coleman, Nat. Commun. 10 (2019) 1933, https://doi.org/10.1038/s41467-019-09792-9
57. [57]
  X. Zhao, Y. Li, Y. Wang, E. Song, R. Ma, J. Liu, Nat. Commun. 16 (2025) 5718, https://doi.org/10.1038/s41467-025-60823-0X. Zhao, Y. Li, Y. Wang, E. Song, R. Ma, J. Liu, Nat. Commun. 16 (2025) 5718, https://doi.org/10.1038/s41467-025-60823-0
58. [58]
  G.J. Li, L. Sun, S.L. Zhang, C.F. Zhang, H.Y. Jin, K. Davey, G.M. Liang, S.L. Liu, J.F. Mao, Z.P. Guo, Adv. Funct. Mater. 34 (2024) 2301291, https://doi.org/10.1002/adfm.202301291G.J. Li, L. Sun, S.L. Zhang, C.F. Zhang, H.Y. Jin, K. Davey, G.M. Liang, S.L. Liu, J.F. Mao, Z.P. Guo, Adv. Funct. Mater. 34 (2024) 2301291, https://doi.org/10.1002/adfm.202301291
59. [59]
  D. Wang, S. Zhang, C. Li, X. Chen, W. Wang, Y. Han, H. Lin, Z. Shi, S. Feng, Chem. Eng. J. 435 (2022) 134754, https://doi.org/10.1016/j.cej.2022.134754D. Wang, S. Zhang, C. Li, X. Chen, W. Wang, Y. Han, H. Lin, Z. Shi, S. Feng, Chem. Eng. J. 435 (2022) 134754, https://doi.org/10.1016/j.cej.2022.134754
60. [60]
  N. Zhang, F. Cheng, J. Liu, L. Wang, X. Long, X. Liu, F. Li, J. Chen, Nat. Commun. 8 (2017) 405, https://doi.org/10.1038/s41467-017-00467-xN. Zhang, F. Cheng, J. Liu, L. Wang, X. Long, X. Liu, F. Li, J. Chen, Nat. Commun. 8 (2017) 405, https://doi.org/10.1038/s41467-017-00467-x
61. [61]
  N. Gao, Y. Song, C. Li, C. Q. Hu, ACS Appl. Mater. Interfaces 15 (2023) 28044, https://doi.org/10.1021/acsami.3c03437N. Gao, Y. Song, C. Li, C. Q. Hu, ACS Appl. Mater. Interfaces 15 (2023) 28044, https://doi.org/10.1021/acsami.3c03437
62. [62]
  H. Li, Z. Huang, B. Chen, Y. Jiang, C. Li, W. Xiao, X. Yan, J. Power Sources 527 (2022) 231198, https://doi.org/10.1016/j.jpowsour.2022.231198H. Li, Z. Huang, B. Chen, Y. Jiang, C. Li, W. Xiao, X. Yan, J. Power Sources 527 (2022) 231198, https://doi.org/10.1016/j.jpowsour.2022.231198
63. [63]
  F. Long, Y. Xiang, S. Yang, Y. Li, H. Du, Y. Liu, X. Wu, X. Wu, J. Colloid Interface Sci. 616 (2022) 101, https://doi.org/10.1016/j.jcis.2022.02.059F. Long, Y. Xiang, S. Yang, Y. Li, H. Du, Y. Liu, X. Wu, X. Wu, J. Colloid Interface Sci. 616 (2022) 101, https://doi.org/10.1016/j.jcis.2022.02.059
64. [64]
  Z. Wang, K. Han, Q. Wan, Y. Fang, X. Qu, P. Li, ACS Appl. Mater. Interfaces 15 (2022) 859, https://doi.org/10.1021/acsami.2c15924Z. Wang, K. Han, Q. Wan, Y. Fang, X. Qu, P. Li, ACS Appl. Mater. Interfaces 15 (2022) 859, https://doi.org/10.1021/acsami.2c15924
65. [65]
  M. Chamoun, W.R. Brant, C.-W. Tai, G. Karlsson, D. Noréus, Energy Storage Mater. 15 (2018) 351, https://doi.org/10.1016/j.ensm.2018.06.019M. Chamoun, W.R. Brant, C.-W. Tai, G. Karlsson, D. Noréus, Energy Storage Mater. 15 (2018) 351, https://doi.org/10.1016/j.ensm.2018.06.019
66. [66]
  J. Yang, J.Y. Cao, Y.D. Peng, W.J. Yang, S. Barg, Z. Liu, I.A. Kinloch, M.A. Bissett, R.A.W. Dryfe, ChemSusChem 13 (2020) 4103, https://doi.org/10.1002/cssc.202001216J. Yang, J.Y. Cao, Y.D. Peng, W.J. Yang, S. Barg, Z. Liu, I.A. Kinloch, M.A. Bissett, R.A.W. Dryfe, ChemSusChem 13 (2020) 4103, https://doi.org/10.1002/cssc.202001216
67. [67]
  F. Gao, W. Shi, B. Jiang, Z. Xia, L. Zhang, Q. An, Batteries 9 (2023) 9010050, https://doi.org/10.3390/batteries9010050F. Gao, W. Shi, B. Jiang, Z. Xia, L. Zhang, Q. An, Batteries 9 (2023) 9010050, https://doi.org/10.3390/batteries9010050
68. [68]
  D.A. Kitchaev, H.W. Peng, Y. Liu, J.W. Sun, J.P. Perdew, G. Ceder, Phys. Rev. B 93 (2016) 045132, https://doi.org/10.1103/PhysRevB.93.045132D.A. Kitchaev, H.W. Peng, Y. Liu, J.W. Sun, J.P. Perdew, G. Ceder, Phys. Rev. B 93 (2016) 045132, https://doi.org/10.1103/PhysRevB.93.045132
69. [69]
  T. Le, N. Sadique, L.M. Housel, A.S. Poyraz, E.S. Takeuchi, K.J. Takeuchi, A.C. Marschilok, P. Liu, ACS Appl. Mater. Interfaces 13 (2021) 59937, https://doi.org/10.1021/acsami.1c18849T. Le, N. Sadique, L.M. Housel, A.S. Poyraz, E.S. Takeuchi, K.J. Takeuchi, A.C. Marschilok, P. Liu, ACS Appl. Mater. Interfaces 13 (2021) 59937, https://doi.org/10.1021/acsami.1c18849
70. [70]
  T. Le, E. S. Takeuchi, K. J. Takeuchi, A. C. Marschilok, P. Liu, J. Phys. Chem. C 127 (2023) 907, https://doi.org/10.1021/acs.jpcc.2c06851T. Le, E. S. Takeuchi, K. J. Takeuchi, A. C. Marschilok, P. Liu, J. Phys. Chem. C 127 (2023) 907, https://doi.org/10.1021/acs.jpcc.2c06851

扫一扫看文章

计量

PDF下载量: 0
文章访问数: 7
HTML全文浏览量: 0

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

一种数据驱动方法快速筛选高性能水系锌离子电池中金属掺杂二氧化锰正极

通讯作者: 王成龙,E-mail:clwang@phy.ecnu.edu.cn; 黎晋良,E-mail:lijinliang@email.jnu.edu.cn; 潘丽坤,E-mail:lkpan@phy.ecnu.edu.cn

English

A data-driven approach for rapid revealing of metal doping in MnO₂ cathodes for high-performance aqueous zinc-ion batteries

Corresponding author: Chenglong Wang, ; Jinliang Li, ; Likun Pan,

CCS Chemistry：嵌段共聚物自组装成 “三明治”二维有机材料，实现纳米级压力传感功能

CCS Chemistry：颜徐州、鲍哲南：你的皮肤可能是一片SPMs

CCS Chemistry：工作高效不疲劳，只须让催化剂动起来

CCS Chemistry：静电组装导向聚合- 聚电解质纳米凝胶量化制备新策略

CCS Chemistry：金黄色葡萄球菌醛基脱氢酶是如何识别特异性底物的？

计量

通讯作者: 陈斌, bchen63@163.com

中国化学会秘书处

一种数据驱动方法快速筛选高性能水系锌离子电池中金属掺杂二氧化锰正极

通讯作者: 王成龙,E-mail:clwang@phy.ecnu.edu.cn; 黎晋良,E-mail:lijinliang@email.jnu.edu.cn; 潘丽坤,E-mail:lkpan@phy.ecnu.edu.cn

English

A data-driven approach for rapid revealing of metal doping in MnO2 cathodes for high-performance aqueous zinc-ion batteries

Corresponding author: Chenglong Wang, ; Jinliang Li, ; Likun Pan,

CCS Chemistry：嵌段共聚物自组装成 “三明治”二维有机材料，实现纳米级压力传感功能

CCS Chemistry：颜徐州、鲍哲南： 你的皮肤可能是一片SPMs

CCS Chemistry：工作高效不疲劳，只须让催化剂动起来

CCS Chemistry：静电组装导向聚合- 聚电解质纳米凝胶量化制备新策略

CCS Chemistry：金黄色葡萄球菌醛基脱氢酶是如何识别特异性底物的？

计量

文章相关

通讯作者: 陈斌, bchen63@163.com

中国化学会秘书处

A data-driven approach for rapid revealing of metal doping in MnO₂ cathodes for high-performance aqueous zinc-ion batteries

CCS Chemistry：颜徐州、鲍哲南：你的皮肤可能是一片SPMs