材料科学
晶体管
石墨烯
光电子学
神经形态工程学
帧(网络)
计算机科学
薄膜晶体管
人工神经网络
人工智能
纳米技术
图层(电子)
电气工程
工程类
电信
电压
作者
Chao Han,Xingwei Han,Jiayue Han,Meiyu He,Silu Peng,Chaoyi Zhang,Xianchao Liu,Jun Gou,Jun Wang
标识
DOI:10.1002/adfm.202113053
摘要
Abstract Optoelectronic synaptic devices, which combine the functions of photosensitivity and information processing, are essential for the development of artificial visual perception systems. Nevertheless, improving the paired pulse facilitation (PPF) index of optoelectronic synaptic devices, which is an urgent problem in the construction of high‐precision artificial visual perception systems, has received less attention so far. Herein, a light‐stimulated synaptic transistor (LSST) device with an ultra‐high PPF index ( ≈ 196%) is presented by introducing an ultra‐thin carrier regulator layer hexagonal boron nitride (h‐BN) into a classic graphene‐based hybrid transistor frame (graphene/CsPbBr 3 quantum dots). Crucially, analysis of the rate‐limiting effect of h‐BN on photogenerated carriers reveals the mechanism behind the LSST ultra‐high PPF index. Furthermore, a two‐layer artificial neural network connected by LSST devices demonstrate ≈ 91.5% recognition accuracy of handwritten digits. This work provides an effective method for constructing artificial visual perception systems using a hybrid transistor frame in the future.
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