Artificial Synapses and Logic Gates Based on Tellurium Oxide Memristors for Artificial Vision Applications

Abstract The separation of “storage and computation” in the traditional von Neumann architecture creates an insurmountable “memory wall” bottleneck, resulting in high energy consumption and low data transfer efficiency. The integration of brain‐like functions that combine sensing, storage, and computation into a unified hardware system has emerged as a promising strategy for overcoming the von Neumann limitations. This study presents a comprehensive investigation into the development of an integrated optoelectronic neuromorphic system based on tellurium oxide (TeO _x ) memristor for artificial vision applications. The TeO _x memristor exhibits excellent resistive switching (RS) properties and achieves synaptic plasticity and OR, AND logic gates under light and electrical stimulation. Modulated by light pulses with different wavelengths, it mimics associative learning and the brain's “melatonin secretion and inhibition” process. Furthermore, the short‐term plasticity and long‐term plasticity demonstrated by the device can mimic the function of visual neural networks in recognizing and memorizing images from noise. By further integrating the synaptic plasticity functionality with a convolutional neural network (CNN), the device is capable of achieving precise image recognition and classification, with an accuracy of 94.84%. This indicates the significant potential of optoelectronic devices based on TeO _x in the field of artificial vision applications.