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Three Musketeers: demonstration of multilevel memory, selector, and synaptic behaviors from an Ag-GeTe based chalcogenide material

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dc.contributor.authorYu, Min Ji-
dc.contributor.authorSon, Kyung Rock-
dc.contributor.authorKhot, Atul C.-
dc.contributor.authorKang, Dae Yun-
dc.contributor.authorSung, Ji Hoon-
dc.contributor.authorJang, Il Gyu-
dc.contributor.authorDange, Yogesh D.-
dc.contributor.authorDongale, Tukaram D.-
dc.contributor.authorKim, Tae Geun-
dc.date.accessioned2022-02-16T10:42:18Z-
dc.date.available2022-02-16T10:42:18Z-
dc.date.created2022-01-19-
dc.date.issued2021-11-
dc.identifier.issn2238-7854-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/135974-
dc.description.abstractFunctional neuronal computing systems that support information diversification require high-density memory with selector devices to reduce leakage current in cross-point architectures, which drives us to develop a functional switching layer that operates as three distinct devices, namely non-volatile memory, selector, and synaptic devices, using a GeTe-based single material system. In this study, amorphous Ag-GeTe switching layers are engineered by doping with Te species to achieve either resistive switching (RS) or threshold switching properties. The Ag/Ag-GeTe/Ag memory device exhibits multilevel characteris-tics via a tunable compliance current approach. By comparison, Ag/Ag-GeTex/Ag selector device provides excellent selectivity (>10(6)) with a very low OFF-current (similar to 10(-11) A). The RS mechanism for memory and selector devices is interrogated by using conductive atomic force microscopy. Moreover, the Ag/Ag-GeTe/Ag RS device mimics a cohort of basic and complex synaptic plasticity properties, including potentiation-depression and four-spike time-dependent plasticity rules that include asymmetric Hebbian, asymmetric anti-Hebbian, symmetric Hebbian, and symmetric anti-Hebbian learning rules. The capability of the synaptic devices to detect image edges is demonstrated by using a convolution neural network. The present work showcases the multi-functionality of Ag-GeTe materials, which will likely emerge as a prominent candidate for high-density cross-point architecture-based neuromorphic computing systems. (C) 2021 The Author(s). Published by Elsevier B.V.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER-
dc.subjectSTATES-
dc.subjectOXIDE-
dc.subjectMODEL-
dc.subjectRRAM-
dc.titleThree Musketeers: demonstration of multilevel memory, selector, and synaptic behaviors from an Ag-GeTe based chalcogenide material-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Tae Geun-
dc.identifier.doi10.1016/j.jmrt.2021.09.044-
dc.identifier.scopusid2-s2.0-85115090051-
dc.identifier.wosid000734459800005-
dc.identifier.bibliographicCitationJOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T, v.15, pp.1984 - 1995-
dc.relation.isPartOfJOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T-
dc.citation.titleJOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T-
dc.citation.volume15-
dc.citation.startPage1984-
dc.citation.endPage1995-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaMaterials Science-
dc.relation.journalResearchAreaMetallurgy & Metallurgical Engineering-
dc.relation.journalWebOfScienceCategoryMaterials Science, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryMetallurgy & Metallurgical Engineering-
dc.subject.keywordPlusMODEL-
dc.subject.keywordPlusOXIDE-
dc.subject.keywordPlusRRAM-
dc.subject.keywordPlusSTATES-
dc.subject.keywordAuthorAmorphous Ag-GeTe-
dc.subject.keywordAuthorConvolutional neural network edge detection-
dc.subject.keywordAuthorMultilevel resistive switching-
dc.subject.keywordAuthorNeuromorphic computing-
dc.subject.keywordAuthorSelector device-
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