Perpendicular-spin-transfer-torque magnetic-tunnel-junction neuron for spiking neural networks depending on the nanoscale grain size of the MgO tunnelling barrier
DC Field | Value | Language |
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dc.contributor.author | Baek, Jong-Ung | - |
dc.contributor.author | Choi, Jin-Young | - |
dc.contributor.author | Kim, Dong-Won | - |
dc.contributor.author | Kim, Ji-Chan | - |
dc.contributor.author | Jun, Han-Sol | - |
dc.contributor.author | Woo, Dae-Seong | - |
dc.contributor.author | Yi, Woo-Seok | - |
dc.contributor.author | Choi, Yo-Han | - |
dc.contributor.author | Seo, Hyung-Tak | - |
dc.contributor.author | Kim, Jae-Joon | - |
dc.contributor.author | Park, Jea-Gun | - |
dc.date.accessioned | 2022-07-06T10:21:53Z | - |
dc.date.available | 2022-07-06T10:21:53Z | - |
dc.date.created | 2022-01-26 | - |
dc.date.issued | 2022-02 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/139621 | - |
dc.description.abstract | Unlike conventional neuromorphic chips fabricated with C-MOSFETs and capacitors, those utilizing p-STT MTJ neuron devices can achieve fast switching (on the order of several tens of nanoseconds) and extremely low power consumption (<0.2 pJ per spike). A p-STT MTJ neuron with a sensing circuit, which is composed of one p-STT MTJ neuron device, seven n-MOSFETs, three p-MOSFETs, and one reference resistor, was constructed in this study and presented integrate-and-fire characteristics for use in spiking neural networks. In particular, the difference in resistance between the no-spiking input and after the implementation of integration-and-fire was found to be principally determined by the average nanoscale grain size (i.e., 0.418 to 1.141 nm) and face-centered-cubic crystallinity of the MgO tunnelling barrier of the p-STT MTJ neuron devices. Therefore, a larger grain size and better crystallinity led to a larger resistance difference in these devices. MNIST pattern recognition tests (achieving a testing accuracy of 90.34%) using the p-STT MTJ neurons were conducted for demonstrating a spiking neural network. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | ROYAL SOC CHEMISTRY | - |
dc.title | Perpendicular-spin-transfer-torque magnetic-tunnel-junction neuron for spiking neural networks depending on the nanoscale grain size of the MgO tunnelling barrier | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Park, Jea-Gun | - |
dc.identifier.doi | 10.1039/d1ma00862e | - |
dc.identifier.scopusid | 2-s2.0-85124624676 | - |
dc.identifier.wosid | 000739503800001 | - |
dc.identifier.bibliographicCitation | MATERIALS ADVANCES, v.3, no.3, pp.1587 - 1593 | - |
dc.relation.isPartOf | MATERIALS ADVANCES | - |
dc.citation.title | MATERIALS ADVANCES | - |
dc.citation.volume | 3 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 1587 | - |
dc.citation.endPage | 1593 | - |
dc.type.rims | ART | - |
dc.type.docType | Article; Early Access | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Materials Science | - |
dc.relation.journalWebOfScienceCategory | Materials Science, Multidisciplinary | - |
dc.subject.keywordPlus | POWER | - |
dc.identifier.url | https://pubs.rsc.org/en/content/articlelanding/2022/MA/D1MA00862E | - |
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