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Ferroelectric-controlled graphene plasmonic surfaces for all-optical neuromorphic vision

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Abstract

Artificial visual systems can recognize desired objects and information from complex environments, and are therefore highly desired for pattern recognition, object detection, and imaging applications. However, state-of-the-art artificial visual systems with high recognition performances that typically consist of electronic devices face the challenges of requiring huge storage space and high power consumption owing to redundant data. Here, we report a terahertz (THz) frequency-selective surface using a graphene split-ring resonator driven by ferroelectric polarization for efficient visual system applications. The downward polarization of the ferroelectric material offers an ultrahigh electrostatic field for doping p-type graphene with an anticipated Fermi level. By optimizing the geometric parameters of the devices and modulating the carrier behaviors of graphene, our plasmonic devices exhibit a tunable spectral response in a range of 1.7–6.0 THz with continuous transmission values. The all-optical neural network using graphene plasmonic surfaces designed in this study exhibited excellent performance in visual preprocessing and convolutional filtering and achieved an ultrahigh recognition accuracy of up to 99.3% in training the Modified National Institute of Standards and Technology (MNIST) handwritten digit dataset. These features demonstrate the great potential of graphene plasmonic devices for future smart artificial vision systems.

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Author information

Authors and Affiliations

  1. School of Electronic Information and Electrical Engineering, Institute for Advanced Study, Chengdu University, Chengdu, 610106, China

    JianBo Chen, ShangDong Li & JunXiong Guo

  2. School of Integrated Circuits, Tsinghua University, Beijing, 100084, China

    Yu Liu

  3. School of Integrated Circuits (National Exemplary School of Microelectronics), University of Electronic Science and Technology of China, Chengdu, 610054, China

    ShangDong Li, Lin Lin & Wen Huang

  4. Jincheng Research Institute of Opto-mechatronics Industry, Jincheng, 048000, China

    YaDong Li

  5. Shanxi Key Laboratory of Advanced Semiconductor Optoelectronic Devices and Integrated Systems, Jincheng, 048000, China

    YaDong Li & JunXiong Guo

  6. Engineering Research Center of Digital Imaging and Display, Ministry of Education, Soochow University, Suzhou, 215006, China

    JunXiong Guo

Authors
  1. JianBo Chen
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  2. Yu Liu
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  7. JunXiong Guo
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Corresponding authors

Correspondence to Yu Liu or JunXiong Guo.

Additional information

This work was supported by the National Natural Science Foundation of China (Grant No. 62201096), the Engineering Research Center of Digital Imaging and Display, Ministry of Education, Soochow University (Grant No. SDGC2246), and the Open Project Program of Shanxi Key Laboratory of Advanced Semiconductor Optoelectronic Devices and Integrated Systems (Grant No. 2023SZKF12).

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The supporting information is available online at tech.scichina.com and link.springer.com. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.

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Chen, J., Liu, Y., Li, S. et al. Ferroelectric-controlled graphene plasmonic surfaces for all-optical neuromorphic vision. Sci. China Technol. Sci. 67, 765–773 (2024). https://doi.org/10.1007/s11431-023-2456-1

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  • DOI: https://doi.org/10.1007/s11431-023-2456-1

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