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论文类型：期刊论文

发表刊物：NPJ 2D Materials & Applications

收录刊物：SCI

学科门类：工学

一级学科：电子科学与技术

文献类型：J

卷号：3

页面范围：31

关键字：graphene, organic ferroelectric, transistor, complementary synapse, ReSuMe

DOI码：10.1038/s41699-019-0114-6

发表时间：2019-07-08

影响因子：11.0

摘要：The hardware design of supervised learning (SL) in spiking neural network (SNN) prefers 3-terminal memristive synapses, where the third terminal is used to impose supervise signals. In this work we address this demand by fabricating graphene transistor gated through organic ferroelectrics of polyvinylidenefluoride. Through gate tuning not only is the nonvolatile and continuous change of graphene channel conductance demonstrated, but also the transition between electron-dominated and hole-dominated transport. By exploiting the adjustable bipolar characteristic, the graphene–ferroelectric transistor can be electrically reconfigured as potentiative or depressive synapse and in this way complementary synapses are realized. The complementary synapse and neuron circuit is then constructed to execute remote supervise method (ReSuMe) of SNN, and quick convergence to successful learning is found through network-level simulation when applying to a SL task of classifying 3 × 3-pixel images. The presented design of graphene–ferroelectric transistor-based complementary synapses and quantitative simulation may indicate a potential approach to hardware implementation of SL in SNN.