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A flexible ultrasensitive optoelectronic sensor array for neuromorphic vision systems

Author

Listed:
  • Qian-Bing Zhu

    (Chinese Academy of Sciences
    University of Science and Technology of China)

  • Bo Li

    (Chinese Academy of Sciences
    University of Science and Technology of China)

  • Dan-Dan Yang

    (Nanjing University of Science and Technology)

  • Chi Liu

    (Chinese Academy of Sciences)

  • Shun Feng

    (Chinese Academy of Sciences
    ShanghaiTech University)

  • Mao-Lin Chen

    (Chinese Academy of Sciences)

  • Yun Sun

    (Chinese Academy of Sciences)

  • Ya-Nan Tian

    (Northeastern University)

  • Xin Su

    (Nanjing University)

  • Xiao-Mu Wang

    (Nanjing University)

  • Song Qiu

    (Chinese Academy of Sciences)

  • Qing-Wen Li

    (Chinese Academy of Sciences)

  • Xiao-Ming Li

    (Nanjing University of Science and Technology)

  • Hai-Bo Zeng

    (Nanjing University of Science and Technology)

  • Hui-Ming Cheng

    (Chinese Academy of Sciences
    University of Science and Technology of China
    Tsinghua University)

  • Dong-Ming Sun

    (Chinese Academy of Sciences
    University of Science and Technology of China)

Abstract

The challenges of developing neuromorphic vision systems inspired by the human eye come not only from how to recreate the flexibility, sophistication, and adaptability of animal systems, but also how to do so with computational efficiency and elegance. Similar to biological systems, these neuromorphic circuits integrate functions of image sensing, memory and processing into the device, and process continuous analog brightness signal in real-time. High-integration, flexibility and ultra-sensitivity are essential for practical artificial vision systems that attempt to emulate biological processing. Here, we present a flexible optoelectronic sensor array of 1024 pixels using a combination of carbon nanotubes and perovskite quantum dots as active materials for an efficient neuromorphic vision system. The device has an extraordinary sensitivity to light with a responsivity of 5.1 × 107 A/W and a specific detectivity of 2 × 1016 Jones, and demonstrates neuromorphic reinforcement learning by training the sensor array with a weak light pulse of 1 μW/cm2.

Suggested Citation

  • Qian-Bing Zhu & Bo Li & Dan-Dan Yang & Chi Liu & Shun Feng & Mao-Lin Chen & Yun Sun & Ya-Nan Tian & Xin Su & Xiao-Mu Wang & Song Qiu & Qing-Wen Li & Xiao-Ming Li & Hai-Bo Zeng & Hui-Ming Cheng & Dong-, 2021. "A flexible ultrasensitive optoelectronic sensor array for neuromorphic vision systems," Nature Communications, Nature, vol. 12(1), pages 1-7, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-22047-w
    DOI: 10.1038/s41467-021-22047-w
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    Cited by:

    1. He-Shan Zhang & Xue-Mei Dong & Zi-Cheng Zhang & Ze-Pu Zhang & Chao-Yi Ban & Zhe Zhou & Cheng Song & Shi-Qi Yan & Qian Xin & Ju-Qing Liu & Yin-Xiang Li & Wei Huang, 2022. "Co-assembled perylene/graphene oxide photosensitive heterobilayer for efficient neuromorphics," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    2. Tian Zhang & Xin Guo & Pan Wang & Xinyi Fan & Zichen Wang & Yan Tong & Decheng Wang & Limin Tong & Linjun Li, 2024. "High performance artificial visual perception and recognition with a plasmon-enhanced 2D material neural network," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    3. Chengyu Wang & Yangshuang Bian & Kai Liu & Mingcong Qin & Fan Zhang & Mingliang Zhu & Wenkang Shi & Mingchao Shao & Shengcong Shang & Jiaxin Hong & Zhiheng Zhu & Zhiyuan Zhao & Yunqi Liu & Yunlong Guo, 2024. "Strain-insensitive viscoelastic perovskite film for intrinsically stretchable neuromorphic vision-adaptive transistors," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    4. Doeon Lee & Minseong Park & Yongmin Baek & Byungjoon Bae & Junseok Heo & Kyusang Lee, 2022. "In-sensor image memorization and encoding via optical neurons for bio-stimulus domain reduction toward visual cognitive processing," Nature Communications, Nature, vol. 13(1), pages 1-9, December.

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