Optically tunable synaptic transistors based on AlGaN/GaN heterostructure for neuromorphic vision processing

作者：Xiaoqi Li, Huazhen Sun, Mei Ge, Leyang Qian, Xuyang Ge, Xuekun Hong, Weiying Qian, Xiangyang Zhang, Jun‐Ge Liang, Xinyi Shan, Jian Guo, Guofeng Yang · 发表于：Applied Physics Letters · 年份：2025 · DOI：10.1063/5.0307178 · 被引用次数：13 · 研究领域：Advanced Memory and Neural Computing、Neural Networks and Reservoir Computing、Ferroelectric and Negative Capacitance Devices

Optoelectronic synaptic devices are a promising technology for overcoming the von Neumann bottleneck, meeting the demand from rapidly advancing artificial intelligence for faster, more energy-efficient neuromorphic computing. This study fabricated an optically tunable synaptic transistor based on an AlGaN/GaN heterostructure, which enables the implementation of neuromorphic vision processing. The device exhibits a low dark current in the cutoff region and a high photo-to-dark current ratio of 1.47 × 108, highlighting its excellent photoresponsivity. Under UV illumination, the device demonstrates synaptic behaviors such as excitatory postsynaptic current and paired-pulse facilitation. By tuning the time, power, and number of optical pulses, dynamic transitions from short-term memory to long-term memory are achieved, effectively emulating visual persistent memory. Furthermore, an optically modulated convolutional neural network is implemented, achieving a classification accuracy of 93.86% on the Fashion-MNIST dataset. These results validate the potential of the proposed device for neuromorphic vision processing applications.