神经形态工程学
光电效应
光电子学
材料科学
晶体管
氧化物
金属浇口
金属
计算机科学
栅氧化层
纳米技术
电气工程
人工神经网络
工程类
人工智能
电压
冶金
作者
Guangtan Miao,L. Y. Shan,Dong Yao,Zezhong Yin,Ranran Ci,Guoxia Liu,Fukai Shan
摘要
Photoelectric synaptic transistors (PSTs) based on metal oxide semiconductors (MOSs) have shown promising applications in visual perception and photonic computing. However, the response range of the PST is limited in the ultra-violet region due to the wide bandgap of the MOS. Herein, a visible light-driven InGaZnO PST based on CeOx floating gate is presented. The optical response of the PST is improved due to the introduction of oxygen vacancies in the CeOx floating gate, and the tunable synaptic characteristics are endowed. Various synaptic behaviors under visible light stimulation have been simulated, including paired-pulse facilitation, high-pass filtering characteristics, the transition from short-term memory to long-term memory, and learning-experience behavior. The multilevel conductance modulation is realized through optical programming and electrical erasing operations. An artificial neural network was constructed based on the long-term plasticity of the PST, and 95.3% accuracy was achieved in image recognition. This work promotes the development of oxide-based PST and provides a candidate for artificial visual bionics inspired by visible light.
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