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Broadband nonlinear modulation of incoherent light using a transparent optoelectronic neuron array

Author

Listed:
  • Dehui Zhang

    (University of California)

  • Dong Xu

    (University of California)

  • Yuhang Li

    (University of California)

  • Yi Luo

    (University of California)

  • Jingtian Hu

    (University of California)

  • Jingxuan Zhou

    (University of California)

  • Yucheng Zhang

    (University of California)

  • Boxuan Zhou

    (University of California)

  • Peiqi Wang

    (University of California)

  • Xurong Li

    (University of California)

  • Bijie Bai

    (University of California)

  • Huaying Ren

    (University of California)

  • Laiyuan Wang

    (University of California)

  • Ao Zhang

    (University of California)

  • Mona Jarrahi

    (University of California
    University of California)

  • Yu Huang

    (University of California
    University of California)

  • Aydogan Ozcan

    (University of California
    University of California)

  • Xiangfeng Duan

    (University of California
    University of California)

Abstract

Nonlinear optical processing of ambient natural light is highly desired for computational imaging and sensing. Strong optical nonlinear response under weak broadband incoherent light is essential for this purpose. By merging 2D transparent phototransistors (TPTs) with liquid crystal (LC) modulators, we create an optoelectronic neuron array that allows self-amplitude modulation of spatially incoherent light, achieving a large nonlinear contrast over a broad spectrum at orders-of-magnitude lower intensity than achievable in most optical nonlinear materials. We fabricated a 10,000-pixel array of optoelectronic neurons, and experimentally demonstrated an intelligent imaging system that instantly attenuates intense glares while retaining the weaker-intensity objects captured by a cellphone camera. This intelligent glare-reduction is important for various imaging applications, including autonomous driving, machine vision, and security cameras. The rapid nonlinear processing of incoherent broadband light might also find applications in optical computing, where nonlinear activation functions for ambient light conditions are highly sought.

Suggested Citation

  • Dehui Zhang & Dong Xu & Yuhang Li & Yi Luo & Jingtian Hu & Jingxuan Zhou & Yucheng Zhang & Boxuan Zhou & Peiqi Wang & Xurong Li & Bijie Bai & Huaying Ren & Laiyuan Wang & Ao Zhang & Mona Jarrahi & Yu , 2024. "Broadband nonlinear modulation of incoherent light using a transparent optoelectronic neuron array," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-46387-5
    DOI: 10.1038/s41467-024-46387-5
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    References listed on IDEAS

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    2. Lukas Mennel & Joanna Symonowicz & Stefan Wachter & Dmitry K. Polyushkin & Aday J. Molina-Mendoza & Thomas Mueller, 2020. "Ultrafast machine vision with 2D material neural network image sensors," Nature, Nature, vol. 579(7797), pages 62-66, March.
    3. Zhuochao Wang & Guangwei Hu & Xinwei Wang & Xumin Ding & Kuang Zhang & Haoyu Li & Shah Nawaz Burokur & Qun Wu & Jian Liu & Jiubin Tan & Cheng-Wei Qiu, 2022. "Single-layer spatial analog meta-processor for imaging processing," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    4. Dehui Zhang & Zhen Xu & Zhengyu Huang & Audrey Rose Gutierrez & Cameron J. Blocker & Che-Hung Liu & Miao-Bin Lien & Gong Cheng & Zhe Liu & Il Yong Chun & Jeffrey A. Fessler & Zhaohui Zhong & Theodore , 2021. "Neural network based 3D tracking with a graphene transparent focal stack imaging system," Nature Communications, Nature, vol. 12(1), pages 1-7, December.
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