Flexible Graphene-Channel Memory Devices: A Review
DC Field | Value | Language |
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dc.contributor.author | Sattari-Esfahlan, S.M. | - |
dc.contributor.author | Kim, Chang-Hyun | - |
dc.date.accessioned | 2021-08-05T01:40:23Z | - |
dc.date.available | 2021-08-05T01:40:23Z | - |
dc.date.created | 2021-08-03 | - |
dc.date.issued | 2021-07-23 | - |
dc.identifier.issn | 2574-0970 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/81820 | - |
dc.description.abstract | There is an increasing importance of memory technologies in our ever-digitalizing society, which is characterized by the generation and use of a tremendous amount of real-time data. Beyond traditional performance requirements, mechanical flexibility of memory systems becomes therefore critical to enabling emerging applications such as the Internet of things. Graphene, now an established nanomaterial platform, is a promising element for building such high-performance memories with an unconventional form factor because of its exceptional electrical conductivities, outstanding mechanical properties, and processing versatility desirable for hybrid integration. Here, we provide an overview of recently developed flexible memory devices based on graphene and its functionalized counterparts. A defining feature of this review is that it exclusively compares and analyzes the devices that meet the following two criteria: (i) an explicit demonstration of working devices on a flexible substrate is reported; (ii) graphene is employed as an active channel rather than as an electrode. Our primary focus is to systematically classify various types of memories, in view of their materials, structural, and functional characteristics. For this, the shapes and compositions of the conductive channel, the key operational mechanisms underlying the electrical functionalities, and the major characteristics of representative device structures and materials systems are carefully evaluated. Furthermore, the applicability of flexible graphene memories to the neuromorphic computing area is discussed. Finally, we address several remaining issues that need to be solved for future technological advancements. © 2021 American Chemical Society. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | American Chemical Society | - |
dc.relation.isPartOf | ACS Applied Nano Materials | - |
dc.title | Flexible Graphene-Channel Memory Devices: A Review | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000677582900006 | - |
dc.identifier.doi | 10.1021/acsanm.1c01523 | - |
dc.identifier.bibliographicCitation | ACS Applied Nano Materials, v.4, no.7, pp.6542 - 6556 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-85110961200 | - |
dc.citation.endPage | 6556 | - |
dc.citation.startPage | 6542 | - |
dc.citation.title | ACS Applied Nano Materials | - |
dc.citation.volume | 4 | - |
dc.citation.number | 7 | - |
dc.contributor.affiliatedAuthor | Sattari-Esfahlan, S.M. | - |
dc.contributor.affiliatedAuthor | Kim, Chang-Hyun | - |
dc.type.docType | Article in Press | - |
dc.subject.keywordAuthor | flexible electronics | - |
dc.subject.keywordAuthor | graphene | - |
dc.subject.keywordAuthor | memory devices | - |
dc.subject.keywordAuthor | neuromorphic computing | - |
dc.subject.keywordAuthor | plastic substrates | - |
dc.subject.keywordPlus | Graphene | - |
dc.subject.keywordPlus | Electrical conductivity | - |
dc.subject.keywordPlus | Emerging applications | - |
dc.subject.keywordPlus | Functional characteristics | - |
dc.subject.keywordPlus | Mechanical flexibility | - |
dc.subject.keywordPlus | Neuromorphic computing | - |
dc.subject.keywordPlus | Operational mechanism | - |
dc.subject.keywordPlus | Performance requirements | - |
dc.subject.keywordPlus | Technological advancement | - |
dc.subject.keywordPlus | Graphene devices | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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