IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-40574-6.html
   My bibliography  Save this article

Multiscale dynamics of charging and plating in graphite electrodes coupling operando microscopy and phase-field modelling

Author

Listed:
  • Xuekun Lu

    (Department of Chemical Engineering, UCL
    Harwell Science and Innovation Campus
    Queen Mary University of London)

  • Marco Lagnoni

    (University of Pisa)

  • Antonio Bertei

    (University of Pisa)

  • Supratim Das

    (MIT)

  • Rhodri E. Owen

    (Department of Chemical Engineering, UCL
    Harwell Science and Innovation Campus)

  • Qi Li

    (Beijing University of Technology)

  • Kieran O’Regan

    (Harwell Science and Innovation Campus
    University of Birmingham)

  • Aaron Wade

    (Department of Chemical Engineering, UCL
    Harwell Science and Innovation Campus)

  • Donal P. Finegan

    (National Renewable Energy Laboratory)

  • Emma Kendrick

    (Harwell Science and Innovation Campus
    University of Birmingham)

  • Martin Z. Bazant

    (MIT
    MIT)

  • Dan J. L. Brett

    (Department of Chemical Engineering, UCL
    Harwell Science and Innovation Campus)

  • Paul R. Shearing

    (Department of Chemical Engineering, UCL
    Harwell Science and Innovation Campus
    University of Oxford)

Abstract

The phase separation dynamics in graphitic anodes significantly affects lithium plating propensity, which is the major degradation mechanism that impairs the safety and fast charge capabilities of automotive lithium-ion batteries. In this study, we present comprehensive investigation employing operando high-resolution optical microscopy combined with non-equilibrium thermodynamics implemented in a multi-dimensional (1D+1D to 3D) phase-field modeling framework to reveal the rate-dependent spatial dynamics of phase separation and plating in graphite electrodes. Here we visualize and provide mechanistic understanding of the multistage phase separation, plating, inter/intra-particle lithium exchange and plated lithium back-intercalation phenomena. A strong dependence of intra-particle lithiation heterogeneity on the particle size, shape, orientation, surface condition and C-rate at the particle level is observed, which leads to early onset of plating spatially resolved by a 3D image-based phase-field model. Moreover, we highlight the distinct relaxation processes at different state-of-charges (SOCs), wherein thermodynamically unstable graphite particles undergo a drastic intra-particle lithium redistribution and inter-particle lithium exchange at intermediate SOCs, whereas the electrode equilibrates much slower at low and high SOCs. These physics-based insights into the distinct SOC-dependent relaxation efficiency provide new perspective towards developing advanced fast charge protocols to suppress plating and shorten the constant voltage regime.

Suggested Citation

  • Xuekun Lu & Marco Lagnoni & Antonio Bertei & Supratim Das & Rhodri E. Owen & Qi Li & Kieran O’Regan & Aaron Wade & Donal P. Finegan & Emma Kendrick & Martin Z. Bazant & Dan J. L. Brett & Paul R. Shear, 2023. "Multiscale dynamics of charging and plating in graphite electrodes coupling operando microscopy and phase-field modelling," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40574-6
    DOI: 10.1038/s41467-023-40574-6
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-40574-6
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-40574-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jianming Zheng & Mark H. Engelhard & Donghai Mei & Shuhong Jiao & Bryant J. Polzin & Ji-Guang Zhang & Wu Xu, 2017. "Electrolyte additive enabled fast charging and stable cycling lithium metal batteries," Nature Energy, Nature, vol. 2(3), pages 1-8, March.
    2. Peter M. Attia & Aditya Grover & Norman Jin & Kristen A. Severson & Todor M. Markov & Yang-Hung Liao & Michael H. Chen & Bryan Cheong & Nicholas Perkins & Zi Yang & Patrick K. Herring & Muratahan Ayko, 2020. "Closed-loop optimization of fast-charging protocols for batteries with machine learning," Nature, Nature, vol. 578(7795), pages 397-402, February.
    3. Yayuan Liu & Yangying Zhu & Yi Cui, 2019. "Challenges and opportunities towards fast-charging battery materials," Nature Energy, Nature, vol. 4(7), pages 540-550, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuqiang Zeng & Buyi Zhang & Yanbao Fu & Fengyu Shen & Qiye Zheng & Divya Chalise & Ruijiao Miao & Sumanjeet Kaur & Sean D. Lubner & Michael C. Tucker & Vincent Battaglia & Chris Dames & Ravi S. Prashe, 2023. "Extreme fast charging of commercial Li-ion batteries via combined thermal switching and self-heating approaches," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    2. Pietro Iurilli & Luigi Luppi & Claudio Brivio, 2022. "Non-Invasive Detection of Lithium-Metal Battery Degradation," Energies, MDPI, vol. 15(19), pages 1-14, September.
    3. Zhi Chang & Huijun Yang & Xingyu Zhu & Ping He & Haoshen Zhou, 2022. "A stable quasi-solid electrolyte improves the safe operation of highly efficient lithium-metal pouch cells in harsh environments," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Fan, Zhaohui & Fu, Yijie & Liang, Hong & Gao, Renjing & Liu, Shutian, 2023. "A module-level charging optimization method of lithium-ion battery considering temperature gradient effect of liquid cooling and charging time," Energy, Elsevier, vol. 265(C).
    5. Hsu, Chia-Wei & Xiong, Rui & Chen, Nan-Yow & Li, Ju & Tsou, Nien-Ti, 2022. "Deep neural network battery life and voltage prediction by using data of one cycle only," Applied Energy, Elsevier, vol. 306(PB).
    6. Penelope K. Jones & Ulrich Stimming & Alpha A. Lee, 2022. "Impedance-based forecasting of lithium-ion battery performance amid uneven usage," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    7. Bandara, T.G. Thusitha Asela & Viera, J.C. & González, M., 2022. "The next generation of fast charging methods for Lithium-ion batteries: The natural current-absorption methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    8. Zhang, Guangxu & Wei, Xuezhe & Tang, Xuan & Zhu, Jiangong & Chen, Siqi & Dai, Haifeng, 2021. "Internal short circuit mechanisms, experimental approaches and detection methods of lithium-ion batteries for electric vehicles: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    9. Kit McColl & Robert A. House & Gregory J. Rees & Alexander G. Squires & Samuel W. Coles & Peter G. Bruce & Benjamin J. Morgan & M. Saiful Islam, 2022. "Transition metal migration and O2 formation underpin voltage hysteresis in oxygen-redox disordered rocksalt cathodes," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    10. Zhi Chang & Huijun Yang & Anqiang Pan & Ping He & Haoshen Zhou, 2022. "An improved 9 micron thick separator for a 350 Wh/kg lithium metal rechargeable pouch cell," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    11. Hong, Joonki & Lee, Dongheon & Jeong, Eui-Rim & Yi, Yung, 2020. "Towards the swift prediction of the remaining useful life of lithium-ion batteries with end-to-end deep learning," Applied Energy, Elsevier, vol. 278(C).
    12. Yin, Yilin & Choe, Song-Yul, 2020. "Actively temperature controlled health-aware fast charging method for lithium-ion battery using nonlinear model predictive control," Applied Energy, Elsevier, vol. 271(C).
    13. Pepe, Simona & Ciucci, Francesco, 2023. "Long-range battery state-of-health and end-of-life prediction with neural networks and feature engineering," Applied Energy, Elsevier, vol. 350(C).
    14. Wassiliadis, Nikolaos & Ank, Manuel & Wildfeuer, Leo & Kick, Michael K. & Lienkamp, Markus, 2021. "Experimental investigation of the influence of electrical contact resistance on lithium-ion battery testing for fast-charge applications," Applied Energy, Elsevier, vol. 295(C).
    15. Minsung Baek & Jinyoung Kim & Jaegyu Jin & Jang Wook Choi, 2021. "Photochemically driven solid electrolyte interphase for extremely fast-charging lithium-ion batteries," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    16. Yan Zhao & Tianhong Zhou & Mounir Mensi & Jang Wook Choi & Ali Coskun, 2023. "Electrolyte engineering via ether solvent fluorination for developing stable non-aqueous lithium metal batteries," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    17. Ruixue Liu & Guannan He & Xizhe Wang & Dharik Mallapragada & Hongbo Zhao & Yang Shao-Horn & Benben Jiang, 2024. "A cross-scale framework for evaluating flexibility values of battery and fuel cell electric vehicles," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    18. In-Ho Cho & Pyeong-Yeon Lee & Jong-Hoon Kim, 2019. "Analysis of the Effect of the Variable Charging Current Control Method on Cycle Life of Li-ion Batteries," Energies, MDPI, vol. 12(15), pages 1-11, August.
    19. Yongyi Huang & Atsushi Yona & Hiroshi Takahashi & Ashraf Mohamed Hemeida & Paras Mandal & Alexey Mikhaylov & Tomonobu Senjyu & Mohammed Elsayed Lotfy, 2021. "Energy Management System Optimization of Drug Store Electric Vehicles Charging Station Operation," Sustainability, MDPI, vol. 13(11), pages 1-14, May.
    20. Jiangong Zhu & Yixiu Wang & Yuan Huang & R. Bhushan Gopaluni & Yankai Cao & Michael Heere & Martin J. Mühlbauer & Liuda Mereacre & Haifeng Dai & Xinhua Liu & Anatoliy Senyshyn & Xuezhe Wei & Michael K, 2022. "Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40574-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.