神经形态工程学
材料科学
光电子学
突触
晶体管
神经促进
计算机科学
光敏性
长时程增强
兴奋性突触后电位
人工神经网络
神经科学
化学
人工智能
电气工程
抑制性突触后电位
电压
生物
工程类
生物化学
受体
作者
Xiaohui Song,Xiaojing Lv,Mengjie He,Fei Mao,Jie Bai,Xuan Qin,Yanjie Hu,Zinan Ma,Zhen Liu,Xueping Li,Chenhai Shen,Yurong Jiang,Xu Zhao,Congxin Xia
出处
期刊:Nanophotonics
[De Gruyter]
日期:2024-08-28
卷期号:13 (22): 4211-4224
被引量:5
标识
DOI:10.1515/nanoph-2024-0368
摘要
Abstract Optoelectronic synaptic devices have been regarded as the key component in constructing neuromorphic computing systems. However, the optoelectronic synapses based on conventional 2D transistor are still suffering low photosensitivity and volatile retention behavior, which can affect the recognition accuracy and long-term memory. Here, a novel optoelectronic synaptic device based on surface-state-rich CdSe nanobelt photosensitized 2D MoS 2 transistor is demonstrated. Benefiting from the excellent light absorption of CdSe and effective charge trapping at the hetero-interface, the device exhibits not only high photosensitivity but also long retention time (>1,500 s). In addition, typical synaptic functions including the excitatory postsynaptic current, paired-pulse facilitation, the transformation from short-term to long-term plasticity, the transformation from short-term to long-term plasticity, spike-amplitude-dependent plasticity, and learning-forgetting-relearning process are successfully simulated and modulated by light stimulation. Most importantly, an artificial neural network is simulated based on the optical potentiation and electrical habituation characteristics of the synaptic devices, with recognition accuracy rates of 89.2, 93.8, and 91.9 % for file type datasets, small digits, and large digits are achieved. This study demonstrates a simple and efficient way to fabricate highly photosensitive optoelectronic synapse for artificial neural networks by combining the merits of specific materials and device architecture.
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