神经形态工程学
单层
光电子学
电阻式触摸屏
材料科学
差速器(机械装置)
计算机科学
纳米技术
工程类
人工智能
航空航天工程
操作系统
人工神经网络
作者
Jian Zhen Yu,Mengyuan Duan,Guanghong Yang,Caihong Jia
标识
DOI:10.1021/acsaelm.5c00439
摘要
A monolayer MoS 2 memristor with bridge- and bisecting-domain boundaries (DBs) exhibits gate-tunable memristive behavior due to the influence of DBs on the migration kinetics of sulfur vacancy. With increasing the drain-to-source voltage bias, the rectification effect as well as the rectification ratio remain almost unchanged in bridge-DBs. However, for bisecting-DBs, an obvious bipolar resistive switching (RS) accompanying negative differential resistance (NDR) appears when the drain-to-source electric field strength is above 267 V/μm. Furthermore, a gating is effective in inducing bipolar RS and NDR in bisecting-DBs even at a lower drain-to-source electric field strength of 50 V/μm. The above behaviors can be fully understood by the generation and drift of sulfur vacancies coupled with electron trapping/detrapping. The RS and NDR in monolayer MoS 2 are analyzed in detail in a mechanism with a doubly ionized sulfur vacancy and further used for neuromorphic computing. Based on the highly linear conductance weight updates in the bisecting-DB memristor, an artificial neural network (ANN) was established with high recognition accuracies of 88.7% and 96% for the Fashion-MNIST and MNIST data sets, respectively. This lays a solid foundation for the application of two-dimensional (2D) materials in neuromorphic computing.
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