神经形态工程学
材料科学
计算机科学
晶体管
接口(物质)
光电子学
突触重量
人工神经网络
电气工程
电压
人工智能
工程类
毛细管数
毛细管作用
复合材料
作者
Shengkai Wen,Jun Li,Zexin Wang,Zhenzhao Zhang,Jianhua Zhang
摘要
Featuring excellent computational rates and highly parallel computing, human brain-based neuromorphic devices have attracted the attention of more and more researchers. There have been numerous reports investigating the use of transistors to simulate synaptic functions; however, the majority of the dielectric and channel layers in these devices are layer-stacked structures, which are not conducive to the modulation of the active layers. Moreover, optimizing the paired pulse facilitation index is a critical factor in enhancing the short-term memory of synaptic devices and constructing high-precision synaptic systems, but it has received inadequate attention. In this study, we present a low-cost electrolyte-gated synaptic transistor with three-dimensional (3D) interfacial contacts, in which the channel layer is SnO2 nanofibers, and the 3D interface reduces the power consumption to 9.6 fJ. This study has simulated some important synaptic behaviors; importantly, the PPF value is as high as 223%, which is related to the slow kinetics of sodium ions. In addition, the Ebbinghaus forgetting curve and its application to image memory are also simulated. These findings provide valuable insight for the future development of complex neuromorphic systems.
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