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Drawing inspiration from the human visual system’s exceptional capabilities in information processing and memory retention, optoelectronic neuromorphic devices have been considered a cutting-edge solution to mimic these key functions. These devices, particularly optoelectronic memristors, promise to revolutionize neuromorphic computing and visual biomimetic functions, holding significant potential to surpass the traditional von Neumann architecture. Herein, an optoelectronic memristor engineered from a MoS2/WO3 heterojunction is developed and integrated with optoelectronic synapses and optical perception capabilities. The device exhibits short/long-term synaptic plasticity under electrical and optical stimuli, effectively mimicking short/long-term memory and “learning–forgetting–relearning”. Leveraging its optical synaptic characteristics, the device successfully simulates complex synaptic behaviors, including Pavlovian conditioning, enabling visual associative learning similar to the biological brain. Through coordinated optoelectronic modulation of long-term potentiation/depression for synaptic weight, the system achieves 98.4% classification accuracy on the Modified National Institute of Standards and Technology (MNIST) handwritten digit recognition task. Moreover, a 4 × 4 optoelectronic memristor array demonstrates stable visual perception and memory functions under four distinct optical stimuli, facilitating adjustable image memory properties across different light wavelengths. This research advances the application of optoelectronic memristors in neuromorphic computing and bionic visual systems.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0, https://creativecommons.org/licenses/by/4.0/).
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