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Cited 2 time in webofscience Cited 2 time in scopus
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Binary Electronic Synapses for Integrating Digital and Neuromorphic Computation in a Single Physical Platform

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dc.contributor.authorWu, Chaoxing-
dc.contributor.authorZhang, Yongai-
dc.contributor.authorZhou, Xiongtu-
dc.contributor.authorLi, Dianlun-
dc.contributor.authorPark, Jae Hyeon-
dc.contributor.authorAn, Haoqun-
dc.contributor.authorSung, Sihyun-
dc.contributor.authorLin, Jintang-
dc.contributor.authorGuo, Tailiang-
dc.contributor.authorLi, Fushan-
dc.contributor.authorKim, Tae Whan-
dc.date.accessioned2021-08-02T09:28:56Z-
dc.date.available2021-08-02T09:28:56Z-
dc.date.created2021-05-12-
dc.date.issued2020-04-
dc.identifier.issn1944-8244-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/9932-
dc.description.abstractAs a promising advanced computation technology, the integration of digital computation with neuromorphic computation into a single physical platform holds the advantage of a precise, deterministic, fast data process as well as the advantage of a flexible, paralleled, fault-tolerant data process. Even though two-terminal memristive devices have been respectively proved as leading electronic elements for digital computation and neuromorphic computation, it is difficult to steadily maintain both sudden-state-change and gradual-state-change in a single device due to the entirely different operating mechanisms. In this work, we developed a digital-analog compatible memristive device, namely, binary electronic synapse, through realizing controllable cation drift in a memristive layer. The devices feature nonvolatile binary memory as well as artificial neuromorphic plasticity with high operation endurance. With strong nonlinearity in switching dynamics, binary switching, neuromorphic plasticity, two-dimension information store, and trainable memory can be implemented by a single device.-
dc.language영어-
dc.language.isoen-
dc.publisherAMER CHEMICAL SOC-
dc.titleBinary Electronic Synapses for Integrating Digital and Neuromorphic Computation in a Single Physical Platform-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Tae Whan-
dc.identifier.doi10.1021/acsami.0c02145-
dc.identifier.scopusid2-s2.0-85083079865-
dc.identifier.wosid000526583500122-
dc.identifier.bibliographicCitationACS APPLIED MATERIALS & INTERFACES, v.12, no.14, pp.17130 - 17138-
dc.relation.isPartOfACS APPLIED MATERIALS & INTERFACES-
dc.citation.titleACS APPLIED MATERIALS & INTERFACES-
dc.citation.volume12-
dc.citation.number14-
dc.citation.startPage17130-
dc.citation.endPage17138-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaScience & Technology - Other Topics-
dc.relation.journalResearchAreaMaterials Science-
dc.relation.journalWebOfScienceCategoryNanoscience & Nanotechnology-
dc.relation.journalWebOfScienceCategoryMaterials Science, Multidisciplinary-
dc.subject.keywordPlusSWITCHES-
dc.subject.keywordAuthorbinary electronic synapse-
dc.subject.keywordAuthormemristive device-
dc.subject.keywordAuthordigital computation-
dc.subject.keywordAuthorneuromorphic computation-
dc.subject.keywordAuthorcation drift-
dc.identifier.urlhttps://pubs.acs.org/doi/10.1021/acsami.0c02145-
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