对偶(语法数字)
材料科学
光电子学
双重角色
纳米技术
化学
组合化学
艺术
文学类
作者
B.S. Pei,Xuchen Han,Yan Wang,Jing Liu
出处
期刊:PubMed
日期:2025-04-17
卷期号:: e2500184-e2500184
标识
DOI:10.1002/smll.202500184
摘要
Synaptic devices serve as the fundamental units of the brain-inspired neuromorphic computing architecture, which has been proposed to complement the drawback of von Neumann configuration in terms of computational efficiency. In this study, a dual-functional optoelectronic synaptic device is proposed based on the three-terminal MoTe2/h-BN transistor to seamlessly integrate both the synaptic and logic operation functions. The device can be switched between n- and p-type modes through ultraviolet (UV) light induced doping, allowing for versatile plasticity modulation strategies tailored to each operational mode. Comprehensive characterization of the synaptic behavior of the device reveals impressive stability and repeatability. The device is then explored to a virtual three-layered neural network array to classify the handwritten digit images from the Modified National Institute of Standards and Technology database, which achieves an accuracy of 95.4% and 94.2% for the n- and p-type modes, respectively, after 40 training cycles. The device also demonstrates its capability as optoelectronic logic gates, including "AND", "OR" and "XOR" under different gate bias. This multifaceted operation signifies a substantial advancement in the development of hybrid systems that leverage both synaptic and traditional logic functionalities, thereby enhancing the overall efficiency of data processing tasks.
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