Photoelectroactive artificial synapse and its application to biosignal pattern recognition
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Oh Seyong | - |
dc.contributor.author | Lee Je-Jun | - |
dc.contributor.author | Seo Seunghwan | - |
dc.contributor.author | Yoo Gwangwe | - |
dc.contributor.author | Park Jin-Hong | - |
dc.date.accessioned | 2023-08-07T07:30:01Z | - |
dc.date.available | 2023-08-07T07:30:01Z | - |
dc.date.issued | 2021-12 | - |
dc.identifier.issn | 2397-7132 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/113679 | - |
dc.description.abstract | In recent years, optoelectronic artificial synapses have garnered a great deal of research attention owing to their multifunctionality to process optical input signals or to update their weights optically. However, for most optoelectronic synapses, the use of optical stimuli is restricted to an excitatory spike pulse, which majorly limits their application to hardware neural networks. Here, we report a unique weight-update operation in a photoelectroactive synapse; the synaptic weight can be both potentiated and depressed using "optical spikes." This unique bidirectional operation originates from the ionization and neutralization of inherent defects in hexagonal-boron nitride by co-stimuli consisting of optical and electrical spikes. The proposed synapse device exhibits (i) outstanding analog memory characteristics, such as high accessibility (cycle-to-cycle variation of <1%) and long retention (>21 days), and (ii) excellent synaptic dynamics, such as a high dynamic range (>384) and modest asymmetricity (<3.9). Such remarkable characteristics enable a maximum accuracy of 96.1% to be achieved during the training and inference simulation for human electrocardiogram patterns. | - |
dc.format.extent | 8 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | NATURE PUBLISHING GROUP | - |
dc.title | Photoelectroactive artificial synapse and its application to biosignal pattern recognition | - |
dc.type | Article | - |
dc.publisher.location | 영국 | - |
dc.identifier.doi | 10.1038/s41699-021-00274-5 | - |
dc.identifier.scopusid | 2-s2.0-85121546552 | - |
dc.identifier.wosid | 000732544600002 | - |
dc.identifier.bibliographicCitation | npj 2D Materials and Applications, v.5, no.1, pp 1 - 8 | - |
dc.citation.title | npj 2D Materials and Applications | - |
dc.citation.volume | 5 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 8 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalResearchArea | Materials SciencePhysics | - |
dc.relation.journalWebOfScienceCategory | Nanoscience & Nanotechnology | - |
dc.relation.journalWebOfScienceCategory | Materials Science, Multidisciplinary | - |
dc.relation.journalWebOfScienceCategory | Physics, Applied | - |
dc.subject.keywordPlus | MEMORY | - |
dc.subject.keywordPlus | NETWORK | - |
dc.subject.keywordPlus | GRAPHENE | - |
dc.subject.keywordPlus | UPDATE | - |
dc.subject.keywordPlus | DEVICE | - |
dc.identifier.url | https://www.nature.com/articles/s41699-021-00274-5 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.