Brain-inspired neuromorphic computing has been intensively studied due to its potential to address the inherent energy and throughput limitations of conventional Von-Neumann based computing architecture. Memristors are ideal building blocks for artificial synapses, which are the fundamental components of neuromorphic computing. In recent years, the emerging ferroic (ferroelectric and ferromagnetic) tunnel junctions have been shown to be able to function as memristors, which are potential candidates to emulate artificial synapses for neuromorphic computing. Here, we provide a review on the ferroic tunnel junctions and their applications as artificial synapses in neuromorphic networks. We focus on the development history of ferroic tunnel junctions, their physical conduction mechanisms, and the intrinsic dynamics of memristors. Their current applications in neuromorphic networks will also be discussed. Finally, a conclusion and future outlooks on the development of ferroic tunnel junctions will be given. Our goal is to give a broad review of ferroic tunnel junction based artificial synapses that can be applied to neuromorphic computing and to help further ongoing research in this field.
Skip Nav Destination
Ferroic tunnel junctions and their application in neuromorphic networks
Article navigation
March 2020
Review Article|
January 06 2020
Ferroic tunnel junctions and their application in neuromorphic networks
Special Collection:
Brain Inspired Electronics
Rui Guo;
Rui Guo
a)
1
Department of Materials Science and Engineering, National University of Singapore
, Singapore 117575, Singapore
2
College of Electron and Information Engineering, Hebei University
, Baoding 071002, China
Search for other works by this author on:
Weinan Lin;
Weinan Lin
a)
1
Department of Materials Science and Engineering, National University of Singapore
, Singapore 117575, Singapore
Search for other works by this author on:
Xiaobing Yan;
Xiaobing Yan
a)
1
Department of Materials Science and Engineering, National University of Singapore
, Singapore 117575, Singapore
2
College of Electron and Information Engineering, Hebei University
, Baoding 071002, China
Search for other works by this author on:
T. Venkatesan;
T. Venkatesan
1
Department of Materials Science and Engineering, National University of Singapore
, Singapore 117575, Singapore
3
NUSNNI-Nanocore, National University of Singapore
, Singapore 117411, Singapore
4
Department of Electrical and Computer Science Engineering, National University of Singapore
, Singapore 117583, Singapore
5
Department of Physics, National University of Singapore
, Singapore 117542, Singapore
6
Integrative Science and Engineering, National University of Singapore
, Singapore 119077, Singapore
Search for other works by this author on:
Jingsheng Chen
Jingsheng Chen
b)
1
Department of Materials Science and Engineering, National University of Singapore
, Singapore 117575, Singapore
b)Author to whom correspondence should be addressed: msecj@nus.edu.sg
Search for other works by this author on:
a)
Contributions: R. Guo, W. Lin, and X. Yan equally contributed to this work.
b)Author to whom correspondence should be addressed: msecj@nus.edu.sg
Note: This paper is part of the special collection on Brain Inspired Electronics.
Appl. Phys. Rev. 7, 011304 (2020)
Article history
Received:
July 20 2019
Accepted:
October 01 2019
Citation
Rui Guo, Weinan Lin, Xiaobing Yan, T. Venkatesan, Jingsheng Chen; Ferroic tunnel junctions and their application in neuromorphic networks. Appl. Phys. Rev. 1 March 2020; 7 (1): 011304. https://doi.org/10.1063/1.5120565
Download citation file:
Sign in
Don't already have an account? Register
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Sign in via your Institution
Sign in via your InstitutionPay-Per-View Access
$40.00