Back to Search Start Over

Reconfigurable Ag/HfO2/NiO/Pt Memristors with Stable Synchronous Synaptic and Neuronal Functions for Renewable Homogeneous Neuromorphic Computing System

Authors :
Chen, Jiaqi
Liu, Xingqiang
Liu, Chang
Tang, Lin
Bu, Tong
Jiang, Bei
Qing, Yahui
Xie, Yulu
Wang, Yong
Shan, Yongtao
Li, Ruxin
Ye, Cong
Liao, Lei
Source :
Nano Letters; May 2024, Vol. 24 Issue: 17 p5371-5378, 8p
Publication Year :
2024

Abstract

Artificial synapses and bionic neurons offer great potential in highly efficient computing paradigms. However, complex requirements for specific electronic devices in neuromorphic computing have made memristors face the challenge of process simplification and universality. Herein, reconfigurable Ag/HfO2/NiO/Pt memristors are designed for feasible switching between volatile and nonvolatile modes by compliance current controlled Ag filaments, which enables stable and reconfigurable synaptic and neuronal functions. A neuromorphic computing system effectively replicates the biological synaptic weight alteration and continuously accomplishes excitation and reset of artificial neurons, which consist of bionic synapses and artificial neurons based on isotype Ag/HfO2/NiO/Pt memristors. This reconfigurable electrical performance of the Ag/HfO2/NiO/Pt memristors takes advantage of simplified hardware design and delivers integrated circuits with high density, which exhibits great potency for future neural networks.

Details

Language :
English
ISSN :
15306984 and 15306992
Volume :
24
Issue :
17
Database :
Supplemental Index
Journal :
Nano Letters
Publication Type :
Periodical
Accession number :
ejs67017150
Full Text :
https://doi.org/10.1021/acs.nanolett.4c01319