Dimensionality Dependent Plasticity in Halide Perovskite Artificial Synapses for Neuromorphic Computing

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dc.contributor.authorKim, Sung-Ilko
dc.contributor.authorLee, Yeongjunko
dc.contributor.authorPark, Min-Hoko
dc.contributor.authorGo, Gyeong-Takko
dc.contributor.authorKim, Young-Noonko
dc.contributor.authorXu, Wentaoko
dc.contributor.authorLee, Hyeon-Dongko
dc.contributor.authorKim, Hobeomko
dc.contributor.authorSeo, Dae-Gyoko
dc.contributor.authorLee, Wanheeko
dc.contributor.authorLee, Tae-Wooko
dc.date.accessioned2024-03-04T01:00:18Z-
dc.date.available2024-03-04T01:00:18Z-
dc.date.created2024-02-26-
dc.date.created2024-02-26-
dc.date.issued2019-09-
dc.identifier.citationADVANCED ELECTRONIC MATERIALS, v.5, no.9-
dc.identifier.issn2199-160X-
dc.identifier.urihttp://hdl.handle.net/10203/318355-
dc.description.abstractThe hysteretic behavior of organic-inorganic halide perovskites (OHPs) are exploited for application in neuromorphic electronics. Artificial synapses with 2D and quasi-2D perovskite are demonstrated that have a bulky organic cation (phenethylammonium (PEA)) to form structures of (PEA)(2)MA(n)(-1)Pb(n)Br(3)(n)(+1). The OHP films have morphological properties that depend on their structure dimensionality (i.e., n value), and artificial synapses fabricated from them show synaptic responses such as short-term plasticity, paired-pulse facilitation, and long-term plasticity. The operation mechanism of OHP artificial synapses are also analyzed depending on the dimensionality and it is found that quasi-2D (n = 3-5) OHP artificial synapses show much longer retention than 2D and 3D OHP counterparts. The calculated energy consumption of a 2D OHP artificial synapse (approximate to 0.7 fJ per synaptic event) is comparable to that of biological synapses (1-10 fJ per synaptic event). These OHP artificial synapses may enable development of neuromorphic electronics that use very little energy.-
dc.languageEnglish-
dc.publisherWILEY-
dc.titleDimensionality Dependent Plasticity in Halide Perovskite Artificial Synapses for Neuromorphic Computing-
dc.typeArticle-
dc.identifier.wosid000486206400019-
dc.identifier.scopusid2-s2.0-85063589682-
dc.type.rimsART-
dc.citation.volume5-
dc.citation.issue9-
dc.citation.publicationnameADVANCED ELECTRONIC MATERIALS-
dc.identifier.doi10.1002/aelm.201900008-
dc.contributor.localauthorLee, Yeongjun-
dc.contributor.nonIdAuthorKim, Sung-Il-
dc.contributor.nonIdAuthorPark, Min-Ho-
dc.contributor.nonIdAuthorGo, Gyeong-Tak-
dc.contributor.nonIdAuthorKim, Young-Noon-
dc.contributor.nonIdAuthorXu, Wentao-
dc.contributor.nonIdAuthorLee, Hyeon-Dong-
dc.contributor.nonIdAuthorKim, Hobeom-
dc.contributor.nonIdAuthorSeo, Dae-Gyo-
dc.contributor.nonIdAuthorLee, Wanhee-
dc.contributor.nonIdAuthorLee, Tae-Woo-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorneuromorphic electronics-
dc.subject.keywordAuthorneuromorphic memory-
dc.subject.keywordAuthorperovskite synapses-
dc.subject.keywordAuthorquasi-2D perovskite-
dc.subject.keywordAuthorsynaptic devices-
dc.subject.keywordPlusLEAD-IODIDE-
dc.subject.keywordPlusMIGRATION-
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