神经形态工程学
计算机科学
突触重量
极化(电化学)
人工神经网络
材料科学
非线性系统
铁电性
半导体
突触
电子工程
光电子学
人工智能
神经科学
物理
工程类
化学
心理学
电介质
物理化学
量子力学
作者
Yitong Chen,Dingwei Li,Huihui Ren,Yingjie Tang,Kun Liang,Yan Wang,Fanfan Li,Chunyan Song,Jiaqi Guan,Zhong Chen,Xingyu Lu,Guangwei Xu,Wenbin Li,Shi Liu,Bowen Zhu
出处
期刊:Small
[Wiley]
日期:2022-09-26
卷期号:18 (45)
被引量:28
标识
DOI:10.1002/smll.202203611
摘要
Brain-inspired neuromorphic computing hardware based on artificial synapses offers efficient solutions to perform computational tasks. However, the nonlinearity and asymmetry of synaptic weight updates in reported artificial synapses have impeded achieving high accuracy in neural networks. Here, this work develops a synaptic memtransistor based on polarization switching in a two-dimensional (2D) ferroelectric semiconductor (FES) of α-In2 Se3 for neuromorphic computing. The α-In2 Se3 memtransistor exhibits outstanding synaptic characteristics, including near-ideal linearity and symmetry and a large number of programmable conductance states, by taking the advantages of both memtransistor configuration and electrically configurable polarization states in the FES channel. As a result, the α-In2 Se3 memtransistor-type synapse reaches high accuracy of 97.76% for digit patterns recognition task in simulated artificial neural networks. This work opens new opportunities for using multiterminal FES memtransistors in advanced neuromorphic electronics.
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