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Contact-electrification-activated artificial afferents at femtojoule energy

Author

Listed:
  • Jinran Yu

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Guoyun Gao

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Jinrong Huang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Xixi Yang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Jing Han

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Huai Zhang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Youhui Chen

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Chunlin Zhao

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Qijun Sun

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences
    Guangxi University)

  • Zhong Lin Wang

    (Chinese Academy of Sciences
    Georgia Institute of Technology)

Abstract

Low power electronics endowed with artificial intelligence and biological afferent characters are beneficial to neuromorphic sensory network. Highly distributed synaptic sensory neurons are more readily driven by portable, distributed, and ubiquitous power sources. Here, we report a contact-electrification-activated artificial afferent at femtojoule energy. Upon the contact-electrification effect, the induced triboelectric signals activate the ion-gel-gated MoS2 postsynaptic transistor, endowing the artificial afferent with the adaptive capacity to carry out spatiotemporal recognition/sensation on external stimuli (e.g., displacements, pressures and touch patterns). The decay time of the synaptic device is in the range of sensory memory stage. The energy dissipation of the artificial afferents is significantly reduced to 11.9 fJ per spike. Furthermore, the artificial afferents are demonstrated to be capable of recognizing the spatiotemporal information of touch patterns. This work is of great significance for the construction of next-generation neuromorphic sensory network, self-powered biomimetic electronics and intelligent interactive equipment.

Suggested Citation

  • Jinran Yu & Guoyun Gao & Jinrong Huang & Xixi Yang & Jing Han & Huai Zhang & Youhui Chen & Chunlin Zhao & Qijun Sun & Zhong Lin Wang, 2021. "Contact-electrification-activated artificial afferents at femtojoule energy," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21890-1
    DOI: 10.1038/s41467-021-21890-1
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    Cited by:

    1. Xu, Pengcheng & Shen, Hui & Li, Jing & Zhang, Chun & Guan, Dong, 2023. "Power bonding diagram model and parameter analysis of contact-separation mode triboelectric nanogenerator," Energy, Elsevier, vol. 279(C).
    2. Vidal, João V. & Rolo, Pedro & Carneiro, Pedro M.R. & Peres, Inês & Kholkin, Andrei L. & Soares dos Santos, Marco P., 2022. "Automated electromagnetic generator with self-adaptive structure by coil switching," Applied Energy, Elsevier, vol. 325(C).

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