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Programmable black phosphorus image sensor for broadband optoelectronic edge computing

Author

Listed:
  • Seokhyeong Lee

    (University of Washington)

  • Ruoming Peng

    (University of Washington)

  • Changming Wu

    (University of Washington)

  • Mo Li

    (University of Washington
    University of Washington)

Abstract

Image sensors with internal computing capability enable in-sensor computing that can significantly reduce the communication latency and power consumption for machine vision in distributed systems and robotics. Two-dimensional semiconductors have many advantages in realizing such intelligent vision sensors because of their tunable electrical and optical properties and amenability for heterogeneous integration. Here, we report a multifunctional infrared image sensor based on an array of black phosphorous programmable phototransistors (bP-PPT). By controlling the stored charges in the gate dielectric layers electrically and optically, the bP-PPT’s electrical conductance and photoresponsivity can be locally or remotely programmed with 5-bit precision to implement an in-sensor convolutional neural network (CNN). The sensor array can receive optical images transmitted over a broad spectral range in the infrared and perform inference computation to process and recognize the images with 92% accuracy. The demonstrated bP image sensor array can be scaled up to build a more complex vision-sensory neural network, which will find many promising applications for distributed and remote multispectral sensing.

Suggested Citation

  • Seokhyeong Lee & Ruoming Peng & Changming Wu & Mo Li, 2022. "Programmable black phosphorus image sensor for broadband optoelectronic edge computing," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29171-1
    DOI: 10.1038/s41467-022-29171-1
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    References listed on IDEAS

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    1. Guilherme Migliato Marega & Yanfei Zhao & Ahmet Avsar & Zhenyu Wang & Mukesh Tripathi & Aleksandra Radenovic & Andras Kis, 2020. "Logic-in-memory based on an atomically thin semiconductor," Nature, Nature, vol. 587(7832), pages 72-77, November.
    2. Fengnian Xia & Han Wang & Yichen Jia, 2014. "Rediscovering black phosphorus as an anisotropic layered material for optoelectronics and electronics," Nature Communications, Nature, vol. 5(1), pages 1-6, December.
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    Cited by:

    1. Gang Wu & Mohamed Abid & Mohamed Zerara & Jiung Cho & Miri Choi & Cormac Ó Coileáin & Kuan-Ming Hung & Ching-Ray Chang & Igor V. Shvets & Han-Chun Wu, 2024. "Miniaturized spectrometer with intrinsic long-term image memory," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Dohyun Kwak & Dmitry K. Polyushkin & Thomas Mueller, 2023. "In-sensor computing using a MoS2 photodetector with programmable spectral responsivity," Nature Communications, Nature, vol. 14(1), pages 1-8, December.

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