IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-47986-y.html
   My bibliography  Save this article

Cellulose nanofiber-mediated manifold dynamic synergy enabling adhesive and photo-detachable hydrogel for self-powered E-skin

Author

Listed:
  • Lei Zhang

    (Chinese Academy of Forestry)

  • Lu Chen

    (Wuhan University)

  • Siheng Wang

    (Chinese Academy of Forestry
    Wuhan University)

  • Shanshan Wang

    (Nanjing Forestry University)

  • Dan Wang

    (Chinese Academy of Forestry)

  • Le Yu

    (Wuhan University)

  • Xu Xu

    (Nanjing Forestry University)

  • He Liu

    (Chinese Academy of Forestry)

  • Chaoji Chen

    (Wuhan University)

Abstract

Self-powered skin attachable and detachable electronics are under intense development to enable the internet of everything and everyone in new and useful ways. Existing on-demand separation strategies rely on complicated pretreatments and physical properties of the adherends, achieving detachable-on-demand in a facile, rapid, and universal way remains challenging. To overcome this challenge, an ingenious cellulose nanofiber-mediated manifold dynamic synergy strategy is developed to construct a supramolecular hydrogel with both reversible tough adhesion and easy photodetachment. The cellulose nanofiber-reinforced network and the coordination between Fe ions and polymer chains endow the dynamic reconfiguration of supramolecular networks and the adhesion behavior of the hydrogel. This strategy enables the simple and rapid fabrication of strong yet reversible hydrogels with tunable toughness ((Valuemax-Valuemin)/Valuemax of up to 86%), on-demand adhesion energy ((Valuemax-Valuemin)/Valuemax of up to 93%), and stable conductivity up to 12 mS cm−1. We further extend this strategy to fabricate different cellulose nanofiber/Fe3+-based hydrogels from various biomacromolecules and petroleum polymers, and shed light on exploration of fundamental dynamic supramolecular network reconfiguration. Simultaneously, we prepare an adhesive-detachable triboelectric nanogenerator as a human-machine interface for a self-powered wireless monitoring system based on this strategy, which can acquire the real-time, self-powered monitoring, and wireless whole-body movement signal, opening up possibilities for diversifying potential applications in electronic skins and intelligent devices.

Suggested Citation

  • Lei Zhang & Lu Chen & Siheng Wang & Shanshan Wang & Dan Wang & Le Yu & Xu Xu & He Liu & Chaoji Chen, 2024. "Cellulose nanofiber-mediated manifold dynamic synergy enabling adhesive and photo-detachable hydrogel for self-powered E-skin," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47986-y
    DOI: 10.1038/s41467-024-47986-y
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-47986-y
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-024-47986-y?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. Yang Zou & Puchuan Tan & Bojing Shi & Han Ouyang & Dongjie Jiang & Zhuo Liu & Hu Li & Min Yu & Chan Wang & Xuecheng Qu & Luming Zhao & Yubo Fan & Zhong Lin Wang & Zhou Li, 2019. "A bionic stretchable nanogenerator for underwater sensing and energy harvesting," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    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. Hongfa Zhao & Minyi Xu & Mingrui Shu & Jie An & Wenbo Ding & Xiangyu Liu & Siyuan Wang & Cong Zhao & Hongyong Yu & Hao Wang & Chuan Wang & Xianping Fu & Xinxiang Pan & Guangming Xie & Zhong Lin Wang, 2022. "Underwater wireless communication via TENG-generated Maxwell’s displacement current," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Wenxi Huang & Qiongling Ding & Hao Wang & Zixuan Wu & Yibing Luo & Wenxiong Shi & Le Yang & Yujie Liang & Chuan Liu & Jin Wu, 2023. "Design of stretchable and self-powered sensing device for portable and remote trace biomarkers detection," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Ali Matin Nazar & King-James Idala Egbe & Azam Abdollahi & Mohammad Amin Hariri-Ardebili, 2021. "Triboelectric Nanogenerators for Energy Harvesting in Ocean: A Review on Application and Hybridization," Energies, MDPI, vol. 14(18), pages 1-33, September.
    4. Yijia Lu & Han Tian & Jia Cheng & Fei Zhu & Bin Liu & Shanshan Wei & Linhong Ji & Zhong Lin Wang, 2022. "Decoding lip language using triboelectric sensors with deep learning," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    5. Sixing Xiong & Kenjiro Fukuda & Kyohei Nakano & Shinyoung Lee & Yutaro Sumi & Masahito Takakuwa & Daishi Inoue & Daisuke Hashizume & Baocai Du & Tomoyuki Yokota & Yinhua Zhou & Keisuke Tajima & Takao , 2024. "Waterproof and ultraflexible organic photovoltaics with improved interface adhesion," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    6. Zhengyang Kong & Elvis K. Boahen & Dong Jun Kim & Fenglong Li & Joo Sung Kim & Hyukmin Kweon & So Young Kim & Hanbin Choi & Jin Zhu & Wu Ying & Do Hwan Kim, 2024. "Ultrafast underwater self-healing piezo-ionic elastomer via dynamic hydrophobic-hydrolytic domains," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    7. Ying Liu & Chan Wang & Zhuo Liu & Xuecheng Qu & Yansong Gai & Jiangtao Xue & Shengyu Chao & Jing Huang & Yuxiang Wu & Yusheng Li & Dan Luo & Zhou Li, 2024. "Self-encapsulated ionic fibers based on stress-induced adaptive phase transition for non-contact depth-of-field camouflage sensing," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    8. Wenbo Liu & Youning Duo & Jiaqi Liu & Feiyang Yuan & Lei Li & Luchen Li & Gang Wang & Bohan Chen & Siqi Wang & Hui Yang & Yuchen Liu & Yanru Mo & Yun Wang & Bin Fang & Fuchun Sun & Xilun Ding & Chi Zh, 2022. "Touchless interactive teaching of soft robots through flexible bimodal sensory interfaces," Nature Communications, Nature, vol. 13(1), pages 1-14, 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:15:y:2024:i:1:d:10.1038_s41467-024-47986-y. 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.