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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 |
Appears in Collections: | Staff Publications Elements |
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Ferroic tunnel junctions and their application in neuromorphic networks.pdf | 7.52 MB | Adobe PDF | OPEN | None | View/Download |
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