High-performance artificial neurons based on Ag/MXene/GST/Pt threshold switching memristors

作     者：连晓娟 付金科 高志瑄 顾世浦 王磊 Xiao-Juan Lian;Jin-Ke Fu;Zhi-Xuan Gao;Shi-Pu Gu;Lei Wang

作者机构：The College of Integrated Circuit Science and EngineeringNanjing University of Posts and TelecommunicationsNanjing 210023China The National and Local Joint Engineering Laboratory of RF Integration and Micro-Assembly TechnologyNanjing University of Posts and TelecommunicationsNanjing 210023China 

出 版 物：《Chinese Physics B》 (中国物理B（英文版）)

年 卷 期：2023年第32卷第1期

页      面：458-463页

核心收录：

学科分类：080903[工学-微电子学与固体电子学] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0809[工学-电子科学与技术（可授工学、理学学位）] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Project supported by the National Natural Science Foundation of China (Grant Nos.61804079 and 61964012) the open research fund of the National and Local Joint Engineering Laboratory of RF Integration and Micro-Assembly Technology (Grant No.KFJJ20200102) the Natural Science Foundation of Jiangsu Province of China (Grant Nos.BK20211273 and BZ2021031) the Nanjing University of Posts and Telecommunications (Grant No.NY220112) the Foundation of Jiangxi Science and Technology Department (Grant No.20202ACBL21200) 

主　　题：memristors artificial neurons 2D MXene Ge_(2)Sb_(2)Te_(5) 

摘      要：Threshold switching(TS) memristors can be used as artificial neurons in neuromorphic systems due to their continuous conductance modulation, scalable and energy-efficient properties. In this paper, we propose a low power artificial neuron based on the Ag/MXene/GST/Pt device with excellent TS characteristics, including a low set voltage(0.38 V)and current(200 nA), an extremely steep slope( 10^(3)). Besides, the characteristics of integrate and fire neurons that are indispensable for spiking neural networks have been experimentally demonstrated. Finally, its memristive mechanism is interpreted through the first-principles calculation depending on the electrochemical metallization effect.