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Highly-packed self-assembled graphene oxide film-integrated resistive random-access memory on a silicon substrate for neuromorphic application

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dc.contributor.authorChoi, Hyun-Seok-
dc.contributor.authorLee, Jihye-
dc.contributor.authorKim, Boram-
dc.contributor.authorLee, Jaehong-
dc.contributor.authorPark, Byung-Gook-
dc.contributor.authorKim, Yoon-
dc.contributor.authorHong, Suck Won-
dc.date.accessioned2022-10-17T04:27:15Z-
dc.date.available2022-10-17T04:27:15Z-
dc.date.created2022-09-29-
dc.date.issued2022-10-
dc.identifier.citationNanotechnology, Vol.33 No.43, p. ac805d-
dc.identifier.issn0957-4484-
dc.identifier.urihttps://hdl.handle.net/10371/186256-
dc.description.abstract© 2022 IOP Publishing Ltd.Resistive random-access memories (RRAMs) based on metal-oxide thin films have been studied extensively for application as synaptic devices in neuromorphic systems. The use of graphene oxide (GO) as a switching layer offers an exciting alternative to other materials such as metal-oxides. We present a newly developed RRAM device fabricated by implementing highly-packed GO layers on a highly doped Si wafer to yield a gradual modulation of the memory as a function of the number of input pulses. By using flow-enabled self-assembly, highly uniform GO thin films can be formed on flat Si wafers in a rapid and simple process. The switching mechanism was explored through proposed scenarios reconstructing the density change of the sp2 cluster in the GO layer, resulting in a gradual conductance modulation. We analyzed that the current in a low resistance state could flow by tunneling or hopping via clusters because the distance between the sp2 clusters in closely-packed GO layers is short. Finally, through a pattern-recognition simulation with a Modified National Institute of Standards and Technology database, the feasibility of using close-packed GO layers as synapse devices was successfully demonstrated.-
dc.language영어-
dc.publisherInstitute of Physics Publishing-
dc.titleHighly-packed self-assembled graphene oxide film-integrated resistive random-access memory on a silicon substrate for neuromorphic application-
dc.typeArticle-
dc.identifier.doi10.1088/1361-6528/ac805d-
dc.citation.journaltitleNanotechnology-
dc.identifier.wosid000834589300001-
dc.identifier.scopusid2-s2.0-85135454175-
dc.citation.number43-
dc.citation.startpageac805d-
dc.citation.volume33-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorPark, Byung-Gook-
dc.type.docTypeArticle-
dc.description.journalClass1-
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