Large-scale high uniform optoelectronic synapses array for artificial visual neural network

人工神经网络 计算机科学 比例(比率) 光电子学 人工智能 材料科学 纳米技术 物理 量子力学
作者
Fanqing Zhang,Chunyang Li,Zhicheng Chen,Haiqiu Tan,Zhongyi Li,Chengzhai Lv,Shuai Xiao,Lining Wu,Jing Zhao
出处
期刊:Microsystems & Nanoengineering [Springer Nature]
卷期号:11 (1): 5-5 被引量:26
标识
DOI:10.1038/s41378-024-00859-2
摘要

Abstract Recently, the biologically inspired intelligent artificial visual neural system has aroused enormous interest. However, there are still significant obstacles in pursuing large-scale parallel and efficient visual memory and recognition. In this study, we demonstrate a 28 × 28 synaptic devices array for the artificial visual neuromorphic system, within the size of 0.7 × 0.7 cm 2 , which integrates sensing, memory, and processing functions. The highly uniform floating-gate synaptic transistors array were constructed by the wafer-scale grown monolayer molybdenum disulfide with Au nanoparticles (NPs) acting as the electrons capture layers. Various synaptic plasticity behaviors have been achieved owing to the switchable electronic storage performance. The excellent optical/electrical coordination capabilities were implemented by paralleled processing both the optical and electrical signals the synaptic array of 784 devices, enabling to realize the badges and letters writing and erasing process. Finally, the established artificial visual convolutional neural network (CNN) through optical/electrical signal modulation can reach the high digit recognition accuracy of 96.5%. Therefore, our results provide a feasible route for future large-scale integrated artificial visual neuromorphic system.
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