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Photo-induced non-volatile VO2 phase transition for neuromorphic ultraviolet sensors

Author

Listed:
  • Ge Li

    (Institute of Physics, Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Donggang Xie

    (Institute of Physics, Chinese Academy of Sciences
    China University of Petroleum (East China))

  • Hai Zhong

    (Institute of Physics, Chinese Academy of Sciences)

  • Ziye Zhang

    (Institute of Physics, Chinese Academy of Sciences
    Capital Normal University)

  • Xingke Fu

    (Institute of Physics, Chinese Academy of Sciences)

  • Qingli Zhou

    (Capital Normal University)

  • Qiang Li

    (University-Industry Joint Center for Ocean Observation and Broadband Communication, State Key Laboratory of Bio-Fibers and Eco-Textiles Qingdao University)

  • Hao Ni

    (China University of Petroleum (East China))

  • Jiaou Wang

    (Institute of High Energy Physics, Chinese Academy of Sciences)

  • Er-jia Guo

    (Institute of Physics, Chinese Academy of Sciences)

  • Meng He

    (Institute of Physics, Chinese Academy of Sciences)

  • Can Wang

    (Institute of Physics, Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Guozhen Yang

    (Institute of Physics, Chinese Academy of Sciences)

  • Kuijuan Jin

    (Institute of Physics, Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Chen Ge

    (Institute of Physics, Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

Abstract

In the quest for emerging in-sensor computing, materials that respond to optical stimuli in conjunction with non-volatile phase transition are highly desired for realizing bioinspired neuromorphic vision components. Here, we report a non-volatile multi-level control of VO2 films by oxygen stoichiometry engineering under ultraviolet irradiation. Based on the reversible regulation of VO2 films using ultraviolet irradiation and electrolyte gating, we demonstrate a proof-of-principle neuromorphic ultraviolet sensor with integrated sensing, memory, and processing functions at room temperature, and also prove its silicon compatible potential through the wafer-scale integration of a neuromorphic sensor array. The device displays linear weight update with optical writing because its metallic phase proportion increases almost linearly with the light dosage. Moreover, the artificial neural network consisting of this neuromorphic sensor can extract ultraviolet information from the surrounding environment, and significantly improve the recognition accuracy from 24% to 93%. This work provides a path to design neuromorphic sensors and will facilitate the potential applications in artificial vision systems.

Suggested Citation

  • Ge Li & Donggang Xie & Hai Zhong & Ziye Zhang & Xingke Fu & Qingli Zhou & Qiang Li & Hao Ni & Jiaou Wang & Er-jia Guo & Meng He & Can Wang & Guozhen Yang & Kuijuan Jin & Chen Ge, 2022. "Photo-induced non-volatile VO2 phase transition for neuromorphic ultraviolet sensors," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29456-5
    DOI: 10.1038/s41467-022-29456-5
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    References listed on IDEAS

    as
    1. Yang Chai, 2020. "In-sensor computing for machine vision," Nature, Nature, vol. 579(7797), pages 32-33, March.
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    Cited by:

    1. Jian Yao & Qinan Wang & Yong Zhang & Yu Teng & Jing Li & Pin Zhao & Chun Zhao & Ziyi Hu & Zongjie Shen & Liwei Liu & Dan Tian & Song Qiu & Zhongrui Wang & Lixing Kang & Qingwen Li, 2024. "Ultra-low power carbon nanotube/porphyrin synaptic arrays for persistent photoconductivity and neuromorphic computing," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Pengzhan Li & Mingzhen Zhang & Qingli Zhou & Qinghua Zhang & Donggang Xie & Ge Li & Zhuohui Liu & Zheng Wang & Erjia Guo & Meng He & Can Wang & Lin Gu & Guozhen Yang & Kuijuan Jin & Chen Ge, 2024. "Reconfigurable optoelectronic transistors for multimodal recognition," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    3. 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.
    4. Ting Jiang & Yiru Wang & Yingshuang Zheng & Le Wang & Xiang He & Liqiang Li & Yunfeng Deng & Huanli Dong & Hongkun Tian & Yanhou Geng & Linghai Xie & Yong Lei & Haifeng Ling & Deyang Ji & Wenping Hu, 2023. "Tetrachromatic vision-inspired neuromorphic sensors with ultraweak ultraviolet detection," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    5. Bujingda Zheng & Yunchao Xie & Shichen Xu & Andrew C. Meng & Shaoyun Wang & Yuchao Wu & Shuhong Yang & Caixia Wan & Guoliang Huang & James M. Tour & Jian Lin, 2024. "Programmed multimaterial assembly by synergized 3D printing and freeform laser induction," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    6. Zhuohui Liu & Qinghua Zhang & Donggang Xie & Mingzhen Zhang & Xinyan Li & Hai Zhong & Ge Li & Meng He & Dashan Shang & Can Wang & Lin Gu & Guozhen Yang & Kuijuan Jin & Chen Ge, 2023. "Interface-type tunable oxygen ion dynamics for physical reservoir computing," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    7. Zhiyuan Li & Zhongshao Li & Wei Tang & Jiaping Yao & Zhipeng Dou & Junjie Gong & Yongfei Li & Beining Zhang & Yunxiao Dong & Jian Xia & Lin Sun & Peng Jiang & Xun Cao & Rui Yang & Xiangshui Miao & Ron, 2024. "Crossmodal sensory neurons based on high-performance flexible memristors for human-machine in-sensor computing system," Nature Communications, Nature, vol. 15(1), pages 1-11, December.

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