One-dimensional organic artificial multi-synapses enabling electronic textile neural network for wearable neuromorphic applications
DC Field | Value | Language |
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dc.contributor.author | Ham, Seonggil | - |
dc.contributor.author | Kang, Minji | - |
dc.contributor.author | Jang, Seonghoon | - |
dc.contributor.author | Jang, Jingon | - |
dc.contributor.author | Choi, Sanghyeon | - |
dc.contributor.author | Kim, Tae-Wook | - |
dc.contributor.author | Wang, Gunuk | - |
dc.date.accessioned | 2021-08-30T19:47:46Z | - |
dc.date.available | 2021-08-30T19:47:46Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2020-07 | - |
dc.identifier.issn | 2375-2548 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/54472 | - |
dc.description.abstract | One-dimensional (1D) devices are becoming the most desirable format for wearable electronic technology because they can be easily woven into electronic (e-) textile(s) with versatile functional units while maintaining their inherent features under mechanical stress. In this study, we designed 1D fiber-shaped multi-synapses comprising ferroelectric organic transistors fabricated on a 100-mu m Ag wire and used them as multisynaptic channels in an e-textile neural network for wearable neuromorphic applications. The device mimics diverse synaptic functions with excellent reliability even under 6000 repeated input stimuli and mechanical bending stress. Various NOR-type textile arrays are formed simply by cross-pointing 1D synapses with Ag wires, where each output from individual synapse can be integrated and propagated without undesired leakage. Notably, the 1D multi-synapses achieved up to similar to 90 and similar to 70% recognition accuracy for MNIST and electrocardiogram patterns, respectively, even in a single-layer neural network, and almost maintained regardless of the bending conditions. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | AMER ASSOC ADVANCEMENT SCIENCE | - |
dc.subject | TIMING-DEPENDENT PLASTICITY | - |
dc.subject | DEVICES | - |
dc.subject | CLASSIFICATION | - |
dc.subject | TRANSISTORS | - |
dc.subject | SENSOR | - |
dc.subject | ARRAY | - |
dc.title | One-dimensional organic artificial multi-synapses enabling electronic textile neural network for wearable neuromorphic applications | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Wang, Gunuk | - |
dc.identifier.doi | 10.1126/sciadv.aba1178 | - |
dc.identifier.scopusid | 2-s2.0-85090534524 | - |
dc.identifier.wosid | 000548735600008 | - |
dc.identifier.bibliographicCitation | SCIENCE ADVANCES, v.6, no.28 | - |
dc.relation.isPartOf | SCIENCE ADVANCES | - |
dc.citation.title | SCIENCE ADVANCES | - |
dc.citation.volume | 6 | - |
dc.citation.number | 28 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalWebOfScienceCategory | Multidisciplinary Sciences | - |
dc.subject.keywordPlus | TIMING-DEPENDENT PLASTICITY | - |
dc.subject.keywordPlus | DEVICES | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordPlus | TRANSISTORS | - |
dc.subject.keywordPlus | SENSOR | - |
dc.subject.keywordPlus | ARRAY | - |
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