A 1T1M Programmable Artificial Spiking Neuron via the Integration of FeFET and NbOₓ Mott Memristor

In this study, we present a one-transistor-one-memristor (1T1M) programmable artificial spiking neuron, achieved through the integration of a Hf0.5 Zr0.5 O2 ferroelectric transistor (FeFET) and a NbOx Mott memristor. The FeFET's threshold voltage, configurable by a gate write pulse ( {V}_{\text...

Full description

Saved in:
Bibliographic Details
Published in:IEEE electron device letters 2024-07, Vol.45 (7), p.1169-1172
Main Authors: Zhao, Shujing, Yu Han, Chuan, Tian, Fengbin, Yuan, Yubin, Chai, Junshuai, Xu, Hao, Fan, Shiquan, Li, Xin, Liu, Weihua, Li, Can, Man Tang, Wing, Lai, P. T., Huang, Xiaodong, Zhang, Guohe, Geng, Li, Wang, Xiaolei
Format: Article
Language:English
Subjects:
Artificial spiking neuron
Data storage
doped HfO
FeFET
FeFETs
Ferroelectricity
Logic gates
Memristors
Mott memristor
NbOₓ
Neural networks
Neurons
Oscillators
programmable neuron
Spiking
Switches
Threshold voltage
Transistors
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this study, we present a one-transistor-one-memristor (1T1M) programmable artificial spiking neuron, achieved through the integration of a Hf0.5 Zr0.5 O2 ferroelectric transistor (FeFET) and a NbOx Mott memristor. The FeFET's threshold voltage, configurable by a gate write pulse ( {V}_{\textit {pulse}} ), exhibits excellent retention properties, enabling the storage of data in multiple states. Simultaneously, the NbOx Mott memristor, characterized by threshold switching and high stability, is driven by the FeFET, allowing for the generation of diverse spike rates corresponding to the storage states of the FeFET. Consequently, a programmable artificial spiking neuron is realized, with its states precisely configured by {V}_{\textit {pulse}} to accurately transmit the encoded neuromorphic spikes. This achievement lays the groundwork for the development of spiking neural networks (SNNs).
ISSN:0741-3106
1558-0563
DOI:10.1109/LED.2024.3395024