IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v597y2021i7874d10.1038_s41586-021-03772-0.html
   My bibliography  Save this article

Scalable production of high-performing woven lithium-ion fibre batteries

Author

Listed:
  • Jiqing He

    (Fudan University
    Fudan University
    Fudan University)

  • Chenhao Lu

    (Fudan University
    Fudan University
    Fudan University)

  • Haibo Jiang

    (Fudan University
    Fudan University
    Fudan University)

  • Fei Han

    (Fudan University)

  • Xiang Shi

    (Fudan University
    Fudan University
    Fudan University)

  • Jingxia Wu

    (Fudan University
    Fudan University
    Fudan University)

  • Liyuan Wang

    (Fudan University
    Fudan University
    Fudan University)

  • Taiqiang Chen

    (Fudan University
    Fudan University
    Fudan University)

  • Jiajia Wang

    (Fudan University
    Fudan University
    Fudan University)

  • Ye Zhang

    (Fudan University
    Fudan University
    Fudan University)

  • Han Yang

    (Fudan University
    Fudan University
    Fudan University)

  • Guoqi Zhang

    (Fudan University)

  • Xuemei Sun

    (Fudan University
    Fudan University
    Fudan University)

  • Bingjie Wang

    (Fudan University
    Fudan University
    Fudan University)

  • Peining Chen

    (Fudan University
    Fudan University
    Fudan University)

  • Yonggang Wang

    (Fudan University
    Fudan University
    Fudan University)

  • Yongyao Xia

    (Fudan University
    Fudan University
    Fudan University)

  • Huisheng Peng

    (Fudan University
    Fudan University
    Fudan University)

Abstract

Fibre lithium-ion batteries are attractive as flexible power solutions because they can be woven into textiles, offering a convenient way to power future wearable electronics1–4. However, they are difficult to produce in lengths of more than a few centimetres, and longer fibres were thought to have higher internal resistances3,5 that compromised electrochemical performance6,7. Here we show that the internal resistance of such fibres has a hyperbolic cotangent function relationship with fibre length, where it first decreases before levelling off as length increases. Systematic studies confirm that this unexpected result is true for different fibre batteries. We are able to produce metres of high-performing fibre lithium-ion batteries through an optimized scalable industrial process. Our mass-produced fibre batteries have an energy density of 85.69 watt hour per kilogram (typical values8 are less than 1 watt hour per kilogram), based on the total weight of a lithium cobalt oxide/graphite full battery, including packaging. Its capacity retention reaches 90.5% after 500 charge–discharge cycles and 93% at 1C rate (compared with 0.1C rate capacity), which is comparable to commercial batteries such as pouch cells. Over 80 per cent capacity can be maintained after bending the fibre for 100,000 cycles. We show that fibre lithium-ion batteries woven into safe and washable textiles by industrial rapier loom can wirelessly charge a cell phone or power a health management jacket integrated with fibre sensors and a textile display.

Suggested Citation

  • Jiqing He & Chenhao Lu & Haibo Jiang & Fei Han & Xiang Shi & Jingxia Wu & Liyuan Wang & Taiqiang Chen & Jiajia Wang & Ye Zhang & Han Yang & Guoqi Zhang & Xuemei Sun & Bingjie Wang & Peining Chen & Yon, 2021. "Scalable production of high-performing woven lithium-ion fibre batteries," Nature, Nature, vol. 597(7874), pages 57-63, September.
  • Handle: RePEc:nat:nature:v:597:y:2021:i:7874:d:10.1038_s41586-021-03772-0
    DOI: 10.1038/s41586-021-03772-0
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41586-021-03772-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/s41586-021-03772-0?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yi Xing & Mingjie Zhou & Yueguang Si & Chi-Yuan Yang & Liang-Wen Feng & Qilin Wu & Fei Wang & Xiaomin Wang & Wei Huang & Yuhua Cheng & Ruilin Zhang & Xiaozheng Duan & Jun Liu & Ping Song & Hengda Sun , 2023. "Integrated opposite charge grafting induced ionic-junction fiber," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Xiangdong Zhu & Litao Lin & Mingyue Pang & Chao Jia & Longlong Xia & Guosheng Shi & Shicheng Zhang & Yuanda Lu & Liming Sun & Fengbo Yu & Jie Gao & Zhelin He & Xuan Wu & Aodi Li & Liang Wang & Meiling, 2024. "Continuous and low-carbon production of biomass flash graphene," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    3. Pei He & Junyu Yue & Zhennan Qiu & Zijie Meng & Jiankang He & Dichen Li, 2024. "Consecutive multimaterial printing of biomimetic ionic hydrogel power sources with high flexibility and stretchability," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    4. Tianyu Wang & Jialin Meng & Xufeng Zhou & Yue Liu & Zhenyu He & Qi Han & Qingxuan Li & Jiajie Yu & Zhenhai Li & Yongkai Liu & Hao Zhu & Qingqing Sun & David Wei Zhang & Peining Chen & Huisheng Peng & , 2022. "Reconfigurable neuromorphic memristor network for ultralow-power smart textile electronics," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    5. Liu, Jin-Hua & Wang, Peng & Gao, Zhihan & Li, Xuehao & Cui, Wenbo & Li, Ru & Ramakrishna, Seeram & Zhang, Jun & Long, Yun-Ze, 2024. "Review on electrospinning anode and separators for lithium ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    6. Haojie Lu & Yong Zhang & Mengjia Zhu & Shuo Li & Huarun Liang & Peng Bi & Shuai Wang & Haomin Wang & Linli Gan & Xun-En Wu & Yingying Zhang, 2024. "Intelligent perceptual textiles based on ionic-conductive and strong silk fibers," Nature Communications, Nature, vol. 15(1), pages 1-9, 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:nature:v:597:y:2021:i:7874:d:10.1038_s41586-021-03772-0. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.