This work reports a low-cost optoelectronic synaptic device based on an electrochemically deposited CuI thin film. The electrochemical deposition technique enables large-area and uniform thin-film fabrication under low-temperature and ambient-pressure conditions, offering significant advantages of simple processing, cost-effectiveness, and compatibility with flexible substrates. Under 445 nm light stimulation, the device successfully emulates the biological synaptic functions, including paired-pulse facilitation, spike-width-dependent plasticity, spike-frequency-dependent plasticity, and spike-number-dependent plasticity. Furthermore, by implementing a convolutional neural network (CNN) for backend processing of the device-generated optoelectronic pulse signals, a high training set recognition accuracy of 95.2% is achieved under 50% noise perturbation in clothing image classification tasks, validating its potential for low-power, highly parallel neuromorphic computing applications.
Yu et al. (2026) studied this question.