Cited 47 time in
Prospects and applications of volatile memristors
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kim, Dahye | - |
| dc.contributor.author | Jeon, Beomki | - |
| dc.contributor.author | Lee, Yunseok | - |
| dc.contributor.author | Kim, Doohyung | - |
| dc.contributor.author | Cho, Youngboo | - |
| dc.contributor.author | Kim, Sungjun | - |
| dc.date.accessioned | 2023-04-27T10:40:42Z | - |
| dc.date.available | 2023-04-27T10:40:42Z | - |
| dc.date.issued | 2022-07 | - |
| dc.identifier.issn | 0003-6951 | - |
| dc.identifier.issn | 1077-3118 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/2844 | - |
| dc.description.abstract | Since research on artificial intelligence has begun receiving much attention, interest in efficient hardware that can process a complex and large amount of information has also increased. The existing von Neumann computing architecture has significant limitations in terms of speed and energy efficiency. Volatile memristors are the most promising among several emerging memory semiconductor devices, because they have various features suitable for neuro-inspired applications. Therefore, a comprehensive review of volatile memristors is urgently needed for future research. Herein, we present the physical interpretation and latest research trends of the switching mechanisms of volatile memristors. We also review diverse promising applications using volatile memristors. In particular, we focus on selectors for array structures, synaptic devices for neuromorphic engineering, imitation of nociceptors, and reservoir computing for time-dependent input data processing. Finally, we discuss the future directions of volatile memristors and their applications. Published under an exclusive license by AIP Publishing. | - |
| dc.format.extent | 10 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | AIP Publishing | - |
| dc.title | Prospects and applications of volatile memristors | - |
| dc.type | Article | - |
| dc.publisher.location | 미국 | - |
| dc.identifier.doi | 10.1063/5.0093964 | - |
| dc.identifier.scopusid | 2-s2.0-85133964771 | - |
| dc.identifier.wosid | 000822955800003 | - |
| dc.identifier.bibliographicCitation | Applied Physics Letters, v.121, no.1, pp 1 - 10 | - |
| dc.citation.title | Applied Physics Letters | - |
| dc.citation.volume | 121 | - |
| dc.citation.number | 1 | - |
| dc.citation.startPage | 1 | - |
| dc.citation.endPage | 10 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Physics | - |
| dc.relation.journalWebOfScienceCategory | Physics, Applied | - |
| dc.subject.keywordPlus | SWITCHING CHARACTERISTICS | - |
| dc.subject.keywordPlus | RESISTIVE MEMORY | - |
| dc.subject.keywordPlus | SELECTOR | - |
| dc.subject.keywordPlus | RRAM | - |
| dc.subject.keywordPlus | DEVICES | - |
| dc.subject.keywordPlus | GRAPHENE | - |
| dc.subject.keywordPlus | ARRAY | - |
| dc.subject.keywordPlus | VO2 | - |
| dc.subject.keywordAuthor | Computer Architecture | - |
| dc.subject.keywordAuthor | Data Handling | - |
| dc.subject.keywordAuthor | Memristors | - |
| dc.subject.keywordAuthor | Amount Of Information | - |
| dc.subject.keywordAuthor | Array Structures | - |
| dc.subject.keywordAuthor | Computing Architecture | - |
| dc.subject.keywordAuthor | Emerging Memory | - |
| dc.subject.keywordAuthor | Large Amounts | - |
| dc.subject.keywordAuthor | Memristor | - |
| dc.subject.keywordAuthor | Neumann Computing | - |
| dc.subject.keywordAuthor | Physical Interpretation | - |
| dc.subject.keywordAuthor | Research Trends | - |
| dc.subject.keywordAuthor | Switching Mechanism | - |
| dc.subject.keywordAuthor | Energy Efficiency | - |
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