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Strain-controlled power devices as inspired by human reflex

Author

Listed:
  • Shuo Zhang

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

  • Bei Ma

    (Chiba University)

  • Xingyu Zhou

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

  • Qilin Hua

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

  • Jian Gong

    (Chinese Research Academy of Environmental Sciences)

  • Ting Liu

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

  • Xiao Cui

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

  • Jiyuan Zhu

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

  • Wenbin Guo

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

  • Liang Jing

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

  • Weiguo Hu

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

  • Zhong Lin Wang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences
    Guangxi University
    Georgia Institute of Technology)

Abstract

Bioinspired electronics are rapidly promoting advances in artificial intelligence. Emerging AI applications, e.g., autopilot and robotics, increasingly spur the development of power devices with new forms. Here, we present a strain-controlled power device that can directly modulate the output power responses to external strain at a rapid speed, as inspired by human reflex. By using the cantilever-structured AlGaN/AlN/GaN-based high electron mobility transistor, the device can control significant output power modulation (2.30–2.72 × 103 W cm−2) with weak mechanical stimuli (0–16 mN) at a gate bias of 1 V. We further demonstrate the acceleration-feedback-controlled power application, and prove that the output power can be effectively adjusted at real-time in response to acceleration changes, i.e., ▵P of 72.78–132.89 W cm−2 at an acceleration of 1–5 G at a supply voltage of 15 V. Looking forward, the device will have great significance in a wide range of AI applications, including autopilot, robotics, and human-machine interfaces.

Suggested Citation

  • Shuo Zhang & Bei Ma & Xingyu Zhou & Qilin Hua & Jian Gong & Ting Liu & Xiao Cui & Jiyuan Zhu & Wenbin Guo & Liang Jing & Weiguo Hu & Zhong Lin Wang, 2020. "Strain-controlled power devices as inspired by human reflex," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-019-14234-7
    DOI: 10.1038/s41467-019-14234-7
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    Cited by:

    1. Xin Liu & Danhao Wang & Wei Chen & Yang Kang & Shi Fang & Yuanmin Luo & Dongyang Luo & Huabin Yu & Haochen Zhang & Kun Liang & Lan Fu & Boon S. Ooi & Sheng Liu & Haiding Sun, 2024. "Optoelectronic synapses with chemical-electric behaviors in gallium nitride semiconductors for biorealistic neuromorphic functionality," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    2. Rui Ge & Qiuhong Yu & Feng Zhou & Shuhai Liu & Yong Qin, 2023. "Dual-modal piezotronic transistor for highly sensitive vertical force sensing and lateral strain sensing," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    3. Qiuhong Yu & Rui Ge & Juan Wen & Qi Xu & Zhouguang Lu & Shuhai Liu & Yong Qin, 2024. "Electric pulse-tuned piezotronic effect for interface engineering," Nature Communications, Nature, vol. 15(1), pages 1-11, December.

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