The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Magnetic skyrmion-based artificial neuron device
Abstract
Neuromorphic computing, inspired by the biological nervous system, has attracted considerable attention. Intensive research has been conducted in this field for developing artificial synapses and neurons, attempting to mimic the behaviors of biological synapses and neurons, which are two basic elements of a human brain. Recently, magnetic skyrmions have been investigated as promising candidates in neuromorphic computing design owing to their topologically protected particle-like behaviors, nanoscale size and low driving current density. In one of our previous studies, a skyrmion-based artificial synapse was proposed, with which both short-term plasticity and long-term potentiation functions have been demonstrated. In this work, we further report on a skyrmion-based artificial neuron by exploiting the tunable current-driven skyrmion motion dynamics, mimicking the leaky-integrate-fire function of a biological neuron. With a simple single-device implementation, this proposed artificial neuron may enable us to build a dense and energy-efficient spiking neuromorphic computing system.
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Cites
Nanoscale Memristor Device as Synapse in Neuromorphic Systems
Jo, S. H., Chang, T., Ebong, I., Bhadviya, B. B., Mazumder, P., & Lu, W. (2010) · Nano Letters · doi:10.1021/nl904092h · Cited by 4,174
Training and operation of an integrated neuromorphic network based on metal-oxide memristors
Prezioso, M., Merrikh-Bayat, F., Hoskins, B. D., Adam, G. C., Likharev, K. K., & Strukov, D. B. (2015) · Nature · doi:10.1038/nature14441 · Cited by 3,001
Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing
Kuzum, D., Jeyasingh, R. G. D., Lee, B., & Wong, H.-S. P. (2012) · Nano Letters · doi:10.1021/nl201040y · Cited by 1,267 · cited 1×
“advance has been made with the introduction of emerging nanoelectronic devices, such as phase change devices [4, 5], resistive memory devices [6–8], and spintronic devices [9, 10],”
BackgroundNeuromorphic Hardware System for Visual Pattern Recognition With Memristor Array and CMOS Neuron
Chu, M., Kim, B., Park, S., Hwang, H., Jeon, M., Lee, B. H., & Lee, B.-G. (2015) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2014.2356439 · Cited by 296
Cited by
A comprehensive review on emerging artificial neuromorphic devices
Zhu, J., Zhang, T., Yang, Y., & Huang, R. (2020) · Applied Physics Reviews · doi:10.1063/1.5118217 · Cited by 758
Perspective: Magnetic skyrmions—Overview of recent progress in an active research field
Everschor-Sitte, K., Masell, J., Reeve, R. M., & Kläui, M. (2018) · Journal of Applied Physics · doi:10.1063/1.5048972 · Cited by 601
Skyrmions in magnetic multilayers
Jiang, W., Chen, G., Liu, K., Zang, J., te Velthuis, S. G. E., & Hoffmann, A. (2017) · Physics Reports · doi:10.1016/j.physrep.2017.08.001 · Cited by 566
Metadata
- Authors
- Li, S., Kang, W., Huang, Y., Zhang, X., Zhou, Y., & Zhao, W.
- Venue
- Nanotechnology
- Publisher
- IOP Publishing
- Published
- 2017-07-14
- Volume
- 28
- Issue
- 31
- Pages
- 31LT01
- ISSN
- 0957-4484 (ISSN-L)
- 1361-6528
- OpenAlex
- W2698166745
- Cited by
- 244
- References
- 4
- FWCI
- 8.50
- Type
- journal article
- Language
- en
- Open access
- closed
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