Alcohol-sensitive MoS2 optoelectronic synapses for mimicking human-like visual adaptation

Xiao Liu , Ming Huang , Xiongfeng Zou , Wajid Ali , Sajid Ur Rehman , Juan Li , Ziwei Li , Li Xiang , Anlian Pan

InfoMat ›› 2025, Vol. 7 ›› Issue (8) : e70019

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InfoMat ›› 2025, Vol. 7 ›› Issue (8) : e70019 DOI: 10.1002/inf2.70019
RESEARCH ARTICLE

Alcohol-sensitive MoS2 optoelectronic synapses for mimicking human-like visual adaptation

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Abstract

The rapid advancements in humanoid robotics and autonomous driving demand smart artificial optoelectronic vision systems that can emulate human-like perception. Although many studies have reported multi-functional visual chips based on artificial optoelectronic synaptic devices, few can simulate complex behavioral characteristics of humans, like specific living habits and physiological adaptations. In this study, we demonstrated MoS2 optoelectronic synapses capable of exhibiting tunable human-like visual adaptation abilities under various alcohol concentrations, featuring remarkable photo-induced conductance plasticity for emulating alcohol-sensitive human visual recognition. Two working mechanisms involving hydrogen-atom and oxygen-atom doping were unveiled during the concentration-dependent doping process. The visual adaptation abilities were systematically explored by controlling the doping concentration of alcohol molecules, and were further enhanced by electric and optoelectronic stimuli to emulate human-like behaviors, such as slight drunkenness, heavy drunkenness, and sobering up. Under the influence of alcohol molecules and the modulation of device operating voltage, the accuracy of handwritten digit recognition for this device has greatly increased from 78.9% to 94.7%.

Keywords

MoS2 / optoelectronic synapse / photodetector / phototransistor / visual adaptation

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Xiao Liu, Ming Huang, Xiongfeng Zou, Wajid Ali, Sajid Ur Rehman, Juan Li, Ziwei Li, Li Xiang, Anlian Pan. Alcohol-sensitive MoS2 optoelectronic synapses for mimicking human-like visual adaptation. InfoMat, 2025, 7(8): e70019 DOI:10.1002/inf2.70019

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2025 The Author(s). InfoMat published by UESTC and John Wiley & Sons Australia, Ltd.

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