High-Endurance STO:YSZ Optoelectronic Memristors with Vertically Aligned Nanocomposite Structure for Edge Detection

Edge detection plays a critical role in cutting-edge domains such as real-time monitoring and automatic driving, with optoelectronic device-based real-time image processing garnering significant attention. However, the poor endurance and unstable optical responsivity of conventional optoelectronic memristors constrain their application in highly integrated edge detection systems. In this study, a silicon-based integrated optoelectronic memristor based on SrTiO₃:(Y₂O₃:ZrO₂) (STO:YSZ) vertically aligned nanocomposite (VAN) structure is introduced, where the conductive channels at the spatial vertical interface providing an effective transport pathway. The device achieves excellent endurance (10⁸ switching cycles) and stable multi-band (405-650 nm) optical switching. Additionally, it also exhibits the ability of simulating biological synaptic plasticity, implementing optical image extraction and ASCII code transmission. Importantly, edge detection of real-time road vehicle imagery is demonstrated via an optoelectronic memristor network. This work opens a promising paradigm for developing stable and high endurance machine vision systems based on optoelectronic memristor.