神经形态工程学
晶体管
材料科学
电导
人工神经网络
驻极体
计算机科学
光电子学
电子工程
纳米技术
人工智能
生物系统
电气工程
工程类
电压
物理
复合材料
凝聚态物理
生物
作者
Yi Zou,Enlong Li,Rengjian Yu,Changsong Gao,Xipeng Yu,Bangyan Zeng,Qian Yang,Tailiang Guo,Huipeng Chen
标识
DOI:10.1109/ted.2022.3211478
摘要
Organic synaptic transistors with excellent solution processability and biocompatibility have emerged as artificial electronic synapses. Regular organic synaptic transistors suffer from slight conductance variation and asymmetric conductance tuning, limiting the development of the model perception accuracy of the organic neuromorphic systems. Here, we first develop an electret-based vertical organic synaptic transistor (EVOST) with Mxene as the source electrode. The EVOST achieves linear conductance tuning by leveraging the nanoscale carrier transport channel length and high conductivity of MXene. Moreover, we develop an artificial neural recognition system composed of EVOSTs for recognizing the random images from the database, which achieves outstanding perception accuracy of 94.9%. The EVOST provides an alternative way for neuromorphic computing networks.
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