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Cited 6 time in webofscience Cited 6 time in scopus
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Noise-assisted transport mechanism analysis and synaptic characteristics in ZrOX/HfAlOX-based memristor for neuromorphic systems

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dc.contributor.authorHeo, Jungang-
dc.contributor.authorCho, Youngboo-
dc.contributor.authorJi, Hyeonseung-
dc.contributor.authorKim, Min-Hwi-
dc.contributor.authorLee, Jong-Ho-
dc.contributor.authorLee, Jung-Kyu-
dc.contributor.authorKim, Sungjun-
dc.date.accessioned2024-08-08T08:31:06Z-
dc.date.available2024-08-08T08:31:06Z-
dc.date.issued2023-11-
dc.identifier.issn2166-532X-
dc.identifier.issn2166-532X-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/20505-
dc.description.abstractIn this work, we compare the resistive switching characteristics between Ti/ZrOX/TiN and Ti/ZrOX/HfAlOX/TiN. The bilayer structure of the ZrOX-based device enables power consumption reduction owing to a lower forming voltage and compliance current. Moreover, the on/off ratio of the Ti/ZrOX/HfAlOX/TiN device (>102) is higher than that of the Ti/ZrOX/TiN device (>10). We use the 1/f noise measurement technique to clarify the transport mechanism of the Ti/ZrOX/HfAlOX/TiN device; consequently, ohmic conduction and Schottky emission are confirmed in the low- and high-resistance states, respectively. In addition, the multilevel cell, potentiation, and depression characteristics of the Ti/ZrOX/HfOX/TiN device are considered to assess its suitability as a neuromorphic device. Accordingly, a modified National Institute of Standards and Technology database simulation is conducted using Python to test the pattern recognition accuracy. © 2023 Author(s).-
dc.format.extent12-
dc.language영어-
dc.language.isoENG-
dc.publisherAIP Publishing-
dc.titleNoise-assisted transport mechanism analysis and synaptic characteristics in ZrOX/HfAlOX-based memristor for neuromorphic systems-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1063/5.0175587-
dc.identifier.scopusid2-s2.0-85175733475-
dc.identifier.wosid001096677500002-
dc.identifier.bibliographicCitationAPL Materials, v.11, no.11, pp 1 - 12-
dc.citation.titleAPL Materials-
dc.citation.volume11-
dc.citation.number11-
dc.citation.startPage1-
dc.citation.endPage12-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaScience & Technology - Other Topics-
dc.relation.journalResearchAreaMaterials Science-
dc.relation.journalResearchAreaPhysics-
dc.relation.journalWebOfScienceCategoryNanoscience & Nanotechnology-
dc.relation.journalWebOfScienceCategoryMaterials Science, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryPhysics, Applied-
dc.subject.keywordPlusLOW-FREQUENCY NOISE-
dc.subject.keywordPlusRRAM-
dc.subject.keywordPlusCONDUCTION-
dc.subject.keywordPlusBEHAVIOR-
dc.subject.keywordPlusDEVICES-
dc.subject.keywordAuthorPattern Recognition-
dc.subject.keywordAuthorBi-layer Structure-
dc.subject.keywordAuthorForming Voltages-
dc.subject.keywordAuthorMechanism Analysis-
dc.subject.keywordAuthorMemristor-
dc.subject.keywordAuthorNeuromorphic Systems-
dc.subject.keywordAuthorPower Consumption Reduction-
dc.subject.keywordAuthorResistive Switching-
dc.subject.keywordAuthorSwitching Characteristics-
dc.subject.keywordAuthorTin And Ti-
dc.subject.keywordAuthorTransport Mechanism-
dc.subject.keywordAuthorComputer Software-
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