Three Musketeers: demonstration of multilevel memory, selector, and synaptic behaviors from an Ag-GeTe based chalcogenide material
DC Field | Value | Language |
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dc.contributor.author | Yu, Min Ji | - |
dc.contributor.author | Son, Kyung Rock | - |
dc.contributor.author | Khot, Atul C. | - |
dc.contributor.author | Kang, Dae Yun | - |
dc.contributor.author | Sung, Ji Hoon | - |
dc.contributor.author | Jang, Il Gyu | - |
dc.contributor.author | Dange, Yogesh D. | - |
dc.contributor.author | Dongale, Tukaram D. | - |
dc.contributor.author | Kim, Tae Geun | - |
dc.date.accessioned | 2022-02-16T10:42:18Z | - |
dc.date.available | 2022-02-16T10:42:18Z | - |
dc.date.created | 2022-01-19 | - |
dc.date.issued | 2021-11 | - |
dc.identifier.issn | 2238-7854 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/135974 | - |
dc.description.abstract | Functional 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.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER | - |
dc.subject | STATES | - |
dc.subject | OXIDE | - |
dc.subject | MODEL | - |
dc.subject | RRAM | - |
dc.title | Three Musketeers: demonstration of multilevel memory, selector, and synaptic behaviors from an Ag-GeTe based chalcogenide material | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Tae Geun | - |
dc.identifier.doi | 10.1016/j.jmrt.2021.09.044 | - |
dc.identifier.scopusid | 2-s2.0-85115090051 | - |
dc.identifier.wosid | 000734459800005 | - |
dc.identifier.bibliographicCitation | JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T, v.15, pp.1984 - 1995 | - |
dc.relation.isPartOf | JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T | - |
dc.citation.title | JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T | - |
dc.citation.volume | 15 | - |
dc.citation.startPage | 1984 | - |
dc.citation.endPage | 1995 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Materials Science | - |
dc.relation.journalResearchArea | Metallurgy & Metallurgical Engineering | - |
dc.relation.journalWebOfScienceCategory | Materials Science, Multidisciplinary | - |
dc.relation.journalWebOfScienceCategory | Metallurgy & Metallurgical Engineering | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordPlus | OXIDE | - |
dc.subject.keywordPlus | RRAM | - |
dc.subject.keywordPlus | STATES | - |
dc.subject.keywordAuthor | Amorphous Ag-GeTe | - |
dc.subject.keywordAuthor | Convolutional neural network edge detection | - |
dc.subject.keywordAuthor | Multilevel resistive switching | - |
dc.subject.keywordAuthor | Neuromorphic computing | - |
dc.subject.keywordAuthor | Selector device | - |
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