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Multi-ion controllable metal halide ionic structure for selective short- and long-term memorable synaptic devices
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Lee, Daseul | - |
| dc.contributor.author | Lee, Seung-Jea | - |
| dc.contributor.author | Kim, Jae Ho | - |
| dc.contributor.author | Kim, Geonguk | - |
| dc.contributor.author | Jung, Wan-Gil | - |
| dc.contributor.author | Park, Juyun | - |
| dc.contributor.author | Kang, Yong-Cheol | - |
| dc.contributor.author | Kim, Young-Hoon | - |
| dc.contributor.author | Song, Myungkwan | - |
| dc.contributor.author | Kim, Han Seul | - |
| dc.contributor.author | Choi, Jin Woo | - |
| dc.date.accessioned | 2024-11-28T14:01:37Z | - |
| dc.date.available | 2024-11-28T14:01:37Z | - |
| dc.date.issued | 2024-04 | - |
| dc.identifier.issn | 1748-0132 | - |
| dc.identifier.issn | 1878-044X | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/196780 | - |
| dc.description.abstract | Development of memristors based on artificial synapses is a significant advancement in modeling biological synapses that utilize short-term plasticity (STP) and long-term plasticity (LTP). Herein, we present a novel multimode mechanism memristor based on Cs2AgI3 with 1D [AgI4]3− tetrahedral nanowire that allows for the simultaneous manipulation of temporally expanded plasticity through controllable multi-ions. The ion-transport mechanisms are controlled by the energy barriers of vacancy transportation and metal-ion injection, depending on the bias voltage. Finally, the conductance states of the multimode memristors are determined through the distinct rate-determining steps of the dominant ion migrations. To realize a multimode conductance state, the LTP is further expanded to short-lived (SL) and long-lasting (LL) plasticity by adjusting the length of the memory timescale through bias voltage. SL-LTP maintains a relatively low value (≈0.4 mS) for ∼750 ms, whereas the conductance of LL-LTP gradually decreases from ≈1.5 mS to ≈0.5 mS over 23 h. The accuracies achieved for each respective mode simulation in the perception rate of an artificial neural network based on multimode memristors are ≈91% and ≈88%. Therefore, the Cs2AgI3 memristor is capable of a new breakthrough in the development of next-generation neuromorphic computing as a multimode perceptron by simultaneously utilizing temporal plasticity. | - |
| dc.format.extent | 9 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | Elsevier BV | - |
| dc.title | Multi-ion controllable metal halide ionic structure for selective short- and long-term memorable synaptic devices | - |
| dc.type | Article | - |
| dc.publisher.location | 영국 | - |
| dc.identifier.doi | 10.1016/j.nantod.2024.102184 | - |
| dc.identifier.scopusid | 2-s2.0-85183985041 | - |
| dc.identifier.wosid | 001179587100001 | - |
| dc.identifier.bibliographicCitation | Nano Today, v.55, pp 1 - 9 | - |
| dc.citation.title | Nano Today | - |
| dc.citation.volume | 55 | - |
| dc.citation.startPage | 1 | - |
| dc.citation.endPage | 9 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Chemistry | - |
| dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
| dc.relation.journalResearchArea | Materials Science | - |
| dc.relation.journalWebOfScienceCategory | Chemistry, Multidisciplinary | - |
| dc.relation.journalWebOfScienceCategory | Nanoscience & Nanotechnology | - |
| dc.relation.journalWebOfScienceCategory | Materials Science, Multidisciplinary | - |
| dc.subject.keywordPlus | Bias voltage | - |
| dc.subject.keywordPlus | Memristors | - |
| dc.subject.keywordPlus | Metal halides | - |
| dc.subject.keywordPlus | Metal ions | - |
| dc.subject.keywordAuthor | Artificial synaptic device | - |
| dc.subject.keywordAuthor | Ionic migration | - |
| dc.subject.keywordAuthor | Low-dimensional metal halides | - |
| dc.subject.keywordAuthor | Memristor | - |
| dc.subject.keywordAuthor | Perceptron | - |
| dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S1748013224000392?via%3Dihub | - |
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