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Cited 9 time in webofscience Cited 10 time in scopus
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Implementation of 8-bit reservoir computing through volatile ZrOx-based memristor as a physical reservoir

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dc.contributor.authorJu, Dongyeol-
dc.contributor.authorKoo, Minsuk-
dc.contributor.authorKim, Sungjun-
dc.date.accessioned2024-08-13T06:30:18Z-
dc.date.available2024-08-13T06:30:18Z-
dc.date.issued2024-09-
dc.identifier.issn2211-2855-
dc.identifier.issn2211-3282-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/22860-
dc.description.abstractIn this study, we employed a sputtering process to construct a memristive device within the ITO/ZrOx/TaN structure for implementing neuromorphic computing. Initially, we scanned the basic electrical properties of the ITO/ZrOx/TaN device using a DC voltage sweep on the top ITO electrode. A highly uniform gradual resistive switching phenomenon was observed over 100 cycles. The current decay in the low-resistance state was effectively controlled by the volatile memory properties. Gradual conductance changes for potentiation and depression were achieved by applying electrical pulses, enabling the establishment of multi-level conductance states. In addition, the emulation of various synaptic functions was achieved by following the learning rules of SRDP, EPSC, STDP, ADSP, Pavlovian associative learning, and PPF. Finally, 8-bit reservoir computing was demonstrated in cost-effective pattern generation and recognition, highlighting the ITO/ZrOx/TaN device's advantageous memory storage properties for synaptic characteristics. © 2024 Elsevier Ltd-
dc.format.extent13-
dc.language영어-
dc.language.isoENG-
dc.publisherElsevier BV-
dc.titleImplementation of 8-bit reservoir computing through volatile ZrOx-based memristor as a physical reservoir-
dc.typeArticle-
dc.publisher.location네델란드-
dc.identifier.doi10.1016/j.nanoen.2024.109958-
dc.identifier.scopusid2-s2.0-85198002511-
dc.identifier.wosid001362110900001-
dc.identifier.bibliographicCitationNano Energy, v.128, pp 1 - 13-
dc.citation.titleNano Energy-
dc.citation.volume128-
dc.citation.startPage1-
dc.citation.endPage13-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaScience & Technology - Other Topics-
dc.relation.journalResearchAreaMaterials Science-
dc.relation.journalResearchAreaPhysics-
dc.relation.journalWebOfScienceCategoryChemistry, Physical-
dc.relation.journalWebOfScienceCategoryNanoscience & Nanotechnology-
dc.relation.journalWebOfScienceCategoryMaterials Science, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryPhysics, Applied-
dc.subject.keywordPlusRESISTIVE SWITCHING CHARACTERISTICS-
dc.subject.keywordPlusFILMS-
dc.subject.keywordPlusOXIDE-
dc.subject.keywordAuthorArtificial synapse-
dc.subject.keywordAuthorHigh bit reservoir computing-
dc.subject.keywordAuthorNeuromorphic system-
dc.subject.keywordAuthorResistive switching device-
dc.subject.keywordAuthorZrO<sub>x</sub>-
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