Monolayer MoS_(2)synaptic devices synergistically modulated by Na^(+)ions and sulfur vacancies for neuromorphic computing and pain perception stimulation  

作　　者：Y.B.Liu D.Cai T.C.Zhao M.Shen X.Zhou Z.H.Zhang X.W.Meng D.E.Gu 

机构地区：[1]State Key Laboratory of Electronic Thin Films and Integrated Devices,University of Electronic Science and Technology of China,Chengdu 610054,China [2]College of Chemistry and Materials Science,Sichuan Normal University,Chengdu 610066,China [3]Laboratory of Controllable Preparation and Application of Nanomaterials,Chinese Academy of Sciences,Beijing 100190,China

出　　处：《Journal of Materials Science & Technology》2023年第32期121-131,共11页材料科学技术（英文版）

基　　金：National Natural Science Foundation of China(NSFC)(No.62274021);thanks to eceshi(www.eceshi.com)for the DFT calculations.

摘　　要：Ion based synaptic devices(ISDs)are one of the excellent candidates for neuromorphic computing.However,most of ISDs utilized additional ion sources to supply ions for adjusting the conductance of the device channel,which might hinder the large-scale integration for fabricating hierarchical artificial neural network.Here a high-performance monolayer MoS_(2) ISD is demonstrated using Na^(+)ions doped in MoS_(2) lattice as ion sources.Benefited from the Na^(+)ions and S vacancy defects in the MoS_(2) lattice,the device not only exhibits various synaptic plasticity(long-and short-term plasticity)and typical biological features(pain-perceptual nociceptors and associative learning),but also has a low synaptic event response voltage(100 mV)and a low energy consumption(0.92 pJ)for a synaptic event.A dissociation-adsorptionmigration-binding model is proposed to elaborate the resistance switching mechanism,which is corroborated by density functional theory calculations and characterizations.In addition,an artificial neural network(ANN)based on MoS_(2) ISDs is simulated for the recognition of the MNIST handwritten digits.The deviation of the recognition accuracy is less than 8%compared to the ideal floating-point numeric precision.These results provide a new strategy for fabricating high-performance ISDs for neuromorphic computing.

关 键 词：2D materials MONOLAYER Molybdenum disulfide Synapses Neuromorphic computing 

分 类 号：TQ132.41[化学工程—无机化工]