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Research Article | Open Access

All-Optically Controlled Synapse-Based Neuromorphic Vision System for Bioinformation Recognition

Xinmiao Li1Ying Li1( )Huifang Jiang2Yancheng Chen1Zhuangzhuang Ma2Zhifeng Shi2Di Chen1Guozhen Shen1 ( )
School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China
Key Laboratory of Materials Physics of Ministry of Education, School of Physics and Microelectronics, Zhengzhou University, Zhengzhou 450052, China
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Abstract

All-optically controlled artificial synapses for neuromorphic vision offer unique advantages in simplifying circuit design and minimizing power consumption, meeting the application demands of the current artificial intelligence era. However, developing all-optically controlled devices that combine high performance and high reproducibility remains a significant challenge. In this work, we demonstrate an all-optically controlled artificial synapse based on ZnO and Cs2CoCl4 single crystal connected structure, which integrates light information sensing and processing capabilities. Relying on the simple series-connected structure, as well as the positive photoconductance of ZnO and the negative photoconductance of Cs2CoCl4, the optically controlled bidirectional synaptic plasticity is realized under ultraviolet and visible light stimulation without additional voltage modulation in the all-optically controlled synapse. In addition, leveraging its ultraviolet-enhanced feature extraction and visible-suppression capabilities, the all-optically controlled synapse can act as denoising units in bioinformation preprocessing and weight-updating units in feature recognition. The proposed all-optically controlled synapses exhibit excellent information perception, low-level noise reduction, and high-level cognition functions for bioinformation recognition under complex light conditions. We believe that this work can provide structural-level insights and inspirations in the design and fabrication of all-optically controlled synapses to promote the application for efficient neuromorphic vision in the future.

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Cite this article:
Li X, Li Y, Jiang H, et al. All-Optically Controlled Synapse-Based Neuromorphic Vision System for Bioinformation Recognition. Energy & Environmental Materials, 2026, 9(1). https://doi.org/10.1002/eem2.70131

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Received: 04 July 2025
Revised: 02 August 2025
Published: 09 August 2025
© 2025 The Author(s).

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.