Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/168562
Title: Ferroic tunnel junctions and their application in neuromorphic networks
Authors: Guo, Rui 
Lin, Weinan 
Yan, Xiaobing 
Venkatesan, T. 
Chen, Jingsheng 
Issue Date: 6-Jan-2020
Publisher: American Institute of Physics Inc.
Citation: Guo, Rui, Lin, Weinan, Yan, Xiaobing, Venkatesan, T., Chen, Jingsheng (2020-01-06). Ferroic tunnel junctions and their application in neuromorphic networks. APPLIED PHYSICS REVIEWS 7 (1). ScholarBank@NUS Repository.
Abstract: 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. © 2020 Author(s).
Source Title: APPLIED PHYSICS REVIEWS
URI: https://scholarbank.nus.edu.sg/handle/10635/168562
ISSN: 19319401
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