All-Optically Modulated In-Sensor Computing Device Based on Ionic-Conducting CuInPSe.

Journal: Advanced materials (Deerfield Beach, Fla.)
Published Date: May 15, 2025

Abstract

Inspired by the human visual system, in-sensor computing has emerged as a promising approach to address growing demands for real-time image processing while overcoming constraints in computational resources. However, existing in-sensor computing optoelectronic devices still face challenges such as complex heterostructures or limited optical modulation for operational efficiency, restricting their practical use. Here, a simple two-terminal optoelectronic device has been fabricated using the 2D material CuInPSe, achieving neuromorphic functionalities through all-optical modulation. The device exhibits a tunable photoresponse across the visible spectrum (400 to 700 nm) and enables bidirectional conductance modulation in response to light stimuli, driven by the interaction between Cu⁺ ions and photogenerated electrons. It shows high linearity with 300 discrete conductance states under red, green, and blue light, enabling color-specific image feature extraction, processing, and recognition across three channels. This approach significantly enhances color image recognition accuracy by 4.6% when integrated with a three-channel convolutional neural network. Additionally, the bidirectional photoresponse allows for efficient noise suppression during color image preprocessing, leading to a 490% improvement in signal-to-noise ratio. These findings highlight the potential of CuInPSe-based architecture for robust performance, paving the way for in-sensor neuromorphic vision systems in artificial intelligence and biomimetic computing.

Authors

  • Qianyi Yang
    State Key Laboratory of Photovoltaic Science and Technology, Shanghai Frontiers Science Research Base of Intelligent Optoelectronic and Perception, Institute of Optoelectronic and Department of Materials Science, Fudan University, Shanghai, 200433, China.
  • Yezhao Zhuang
    State Key Laboratory of Photovoltaic Science and Technology, Shanghai Frontiers Science Research Base of Intelligent Optoelectronic and Perception, Institute of Optoelectronic and Department of Materials Science, Fudan University, Shanghai, 200433, China.
  • Zhipeng Zhong
    State Key Laboratory of Photovoltaic Science and Technology, Shanghai Frontiers Science Research Base of Intelligent Optoelectronic and Perception, Institute of Optoelectronic and Department of Materials Science, Fudan University, Shanghai, 200433, China.
  • Xin Cheng
    International Joint Laboratory for Embryonic Development & Prenatal Medicine Division of Histology and Embryology School of Medicine Jinan University Guangzhou China.
  • Xiang Li
    Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
  • Xiangjian Meng
    State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, 200083, China.
  • Wu Shi
    Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 201210, China.
  • Hai Huang
    Institute of Systems Genetics, Department of Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu 610000, China.
  • Jianlu Wang
    Frontier Institute of Chip and System, Fudan University, No. 2005 Songhu Road, Yangpu District, 200438, Shanghai, China.
  • Junhao Chu
    Shanghai Key Laboratory of Multidimensional Information Processing, Department of Electronic Engineering, East China Normal University, Shanghai 200241, China. jhchu@mail.sitp.ac.cn.

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