CMOS-integrated organic neuromorphic imagers for high-resolution dual-modal imaging

Salihuojia Talanti, Kerui Fu, Xiaolong Zheng, Youzhi Shi, Yimei Tan, Chenxi Liu, Yanfei Liu, Ge Mu, Qun Hao, Kangkang Weng () and Xin Tang ()
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Salihuojia Talanti: Beijing Institute of Technology
Kerui Fu: Beijing Institute of Technology
Xiaolong Zheng: Beijing Institute of Technology
Youzhi Shi: Beijing Institute of Technology
Yimei Tan: Beijing Institute of Technology
Chenxi Liu: Beijing Institute of Technology
Yanfei Liu: LTD
Ge Mu: Beijing Institute of Technology
Qun Hao: Beijing Institute of Technology
Kangkang Weng: Beijing Institute of Technology
Xin Tang: Beijing Institute of Technology

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

Abstract: Abstract Simultaneously capturing static images and processing dynamic visual information within a single sensor enables a more comprehensive and efficient acquisition of scene information, thereby enhancing the understanding and processing of complex scenes. However, current artificial visual systems present significant challenges in device integration and multimodal operation. Here, we developed a 640×512-pixel CMOS-integrated organic neuromorphic imager featuring dual modes: standard (frame-based imaging) and synaptic (neuromorphic imaging). In synaptic mode, the system extracts high-resolution spatiotemporal maps (light distribution and motion trajectories) from final frames, decoding temporal sequences of light events through contrast analysis. The neuromorphic device demonstrates adjustable memory behavior through modulation of charge recombination-trapping dynamics, enabling multi-level memory functionality. We further developed a CMOS-compatible photolithography method, which supports high-resolution and non-destructive patterning of organic neuromorphic devices. The fabricated imager allows in-sensor memorization (>18 min) and real-world spatiotemporal imaging with reduced computation resource, demonstrating its potential for industrial monitoring and motion detection.

Date: 2025
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DOI: 10.1038/s41467-025-59446-2

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