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基于CdSe纳米带光敏化MoS晶体管的人工光电突触,具有用于神经形态应用的长保留时间。

Artificial optoelectronic synapse based on CdSe nanobelt photosensitized MoS transistor with long retention time for neuromorphic application.

作者信息

Song Xiaohui, Lv Xiaojing, He Mengjie, Mao Fei, Bai Jie, Qin Xuan, Hu Yanjie, Ma Zinan, Liu Zhen, Li Xueping, Shen Chenhai, Jiang Yurong, Zhao Xu, Xia Congxin

机构信息

Henan Key Laboratory of Photovoltaic Materials, Department of Physics, Henan Normal University, Xinxiang 453007, China.

Department of Electronic and Electrical Engineering, Henan Normal University, Xinxiang 453007, China.

出版信息

Nanophotonics. 2024 Aug 29;13(22):4211-4224. doi: 10.1515/nanoph-2024-0368. eCollection 2024 Sep.

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 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.

摘要

光电突触器件被视为构建神经形态计算系统的关键组件。然而,基于传统二维晶体管的光电突触仍存在光敏性低和保留行为易挥发的问题,这会影响识别精度和长期记忆。在此,展示了一种基于富含表面态的CdSe纳米带光敏化二维MoS晶体管的新型光电突触器件。受益于CdSe优异的光吸收和异质界面处有效的电荷俘获,该器件不仅表现出高光敏性,而且具有长保留时间(>1500秒)。此外,通过光刺激成功模拟和调制了典型的突触功能,包括兴奋性突触后电流、双脉冲易化、从短期可塑性到长期可塑性的转变、尖峰幅度依赖性可塑性以及学习 - 遗忘 - 再学习过程。最重要的是,基于突触器件的光学增强和电习惯化特性模拟了人工神经网络,对于文件类型数据集、小数字和大数字,识别准确率分别达到了89.2%、93.8%和91.9%。本研究展示了一种通过结合特定材料和器件架构的优点来制造用于人工神经网络的高光敏性光电突触的简单有效方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a95/11501069/1a2200611523/j_nanoph-2024-0368_fig_001.jpg

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