Ionic-electronic photodetector for vision assistance with in-sensor image processing

Zhipeng Zhong, Yezhao Zhuang, Xin Cheng, Jingtao Zheng, Qianyi Yang, Xiang Li, Yan Chen, Hong Shen, Tie Lin, Wu Shi, Xiangjian Meng, Junhao Chu, Hai Huang () and Jianlu Wang ()
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Zhipeng Zhong: Fudan University
Yezhao Zhuang: Fudan University
Xin Cheng: Fudan University
Jingtao Zheng: Fudan University
Qianyi Yang: Fudan University
Xiang Li: Fudan University
Yan Chen: Fudan University
Hong Shen: Chinese Academy of Sciences
Tie Lin: Chinese Academy of Sciences
Wu Shi: Fudan University
Xiangjian Meng: Chinese Academy of Sciences
Junhao Chu: Fudan University
Hai Huang: Fudan University
Jianlu Wang: Fudan University

Nature Communications, 2025, vol. 16, issue 1, 1-9

Abstract: Abstract The human eye is highly advanced but limited by color blindness and poor adaptation to changing light. Artificial photodetectors attempt to mimic vision but often require complex processing to overcome these limitations. Thus, developing photodetectors that complement human vision is crucial to overcoming these limitations. Here, we report a CuInP2S6-based photodetector array with tunable photoresponse for in-sensor image processing, directly complementing human vision. Through ionic and electronic tuning, the photodetector shows both positive and negative correlations with light intensity and wavelength. It enhances signal-to-background ratio by 880% and suppresses noise by 1,170 times, allowing effective detection of weak signals under strong illumination. Moreover, taking advantage of the distinct photoresponse to red and green light, the photodetector could improve the contrast between red and green patterns up to 43%, offering potential aid for red-green color blindness. This work presents a vision-enhancing photodetector capable of compensating for human visual deficiencies without external computation.

Date: 2025
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DOI: 10.1038/s41467-025-62563-7

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