Hybrid-Precision Synapse Based-on FDSOI FeFETs With Back-Gate Bias Modulation-Reference-Cited by-同舟云学术

Hybrid-Precision Synapse Based-on FDSOI FeFETs With Back-Gate Bias Modulation

Published:2024-06 Issue:6 Volume:71 Page:3994-3997
ISSN:0018-9383
Container-title:IEEE Transactions on Electron Devices
language:
Short-container-title:IEEE Trans. Electron Devices

Author:

Zhang Miaomiao¹,Chou Lulu¹,Zhang Hongrui¹,Qian Haoji¹,Jin Chengji¹^ORCID,Chen Bing¹^ORCID,Cheng Ran²^ORCID,Liu Yan¹^ORCID,Bernard Guillaume³,Loubriat Sebastien³,Nguyen Bich-Yen³^ORCID,Yu Xiao¹^ORCID,Chen Jiajia¹^ORCID,Han Genquan¹^ORCID

Affiliation:

1. Hangzhou Institute of Technology and the School of Microelectronics, Xidian University, Xi’an, China

2. School of Micro-Nano Electronics, Zhejiang University, Hangzhou, China

3. Soitec, Parc Technologique des Fontaines, Chemin des Franques, Bernin, France

Funder

National Natural Science Foundation of China

Scientific Research Project of Zhejiang Laboratory

Zhejiang Provincial Natural Science Foundation

Zhejiang Province Key Research and Development Programs

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/16/10538150/10502371.pdf?arnumber=10502371

Reference21 articles.

1. Ferroelectricity in hafnium oxide thin films

2. Ferroelectric HfZrO2 With Electrode Engineering and Stimulation Schemes as Symmetric Analog Synaptic Weight Element for Deep Neural Network Training

3. Ferroelectric Tunneling Junctions Based on Aluminum Oxide/ Zirconium-Doped Hafnium Oxide for Neuromorphic Computing

4. Ferroelectric Field Effect Transistors as a Synapse for Neuromorphic Application

5. HfZrO_x-based capacitive synapses with highly linear and symmetric multilevel characteristics for neuromorphic computing