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A Quantum-Well Charge-Trap Synaptic Transistor with Highly Linear Weight Tunability

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dc.contributor.authorYu, E.-
dc.contributor.authorCho, S.-
dc.contributor.authorRoy, K.-
dc.contributor.authorPark, B.-
dc.date.available2020-08-31T00:35:31Z-
dc.date.created2020-08-24-
dc.date.issued2020-07-
dc.identifier.issn2168-6734-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/78074-
dc.description.abstractIn this work, a novel synaptic transistor has been proposed and analyzed through technology computer-aided design (TCAD) simulation. The proposed device has merits of full-Si processing compatibility, short-and long-term plasticity, high energy efficiency, and linear and symmetric conductance adjustability. The proposed device consists of a quantum-well structure and a charge-trap unit for realizing both short-and long-term memories, respectively. The quantum-well charge-trap synaptic transistor (QW CTS) employs two independent gates to separate inference and weight adjustment operation. An optimally designed and validated QW CTS has demonstrated a highly linear and symmetric weight tunability, with an ultra-low energy consumption of 1.5 fJ per synaptic event. The QW CTS can be a core element in the hardware-driven Si neuromorphic system. CCBY-
dc.language영어-
dc.language.isoen-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.relation.isPartOfIEEE Journal of the Electron Devices Society-
dc.titleA Quantum-Well Charge-Trap Synaptic Transistor with Highly Linear Weight Tunability-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.wosid000559512700013-
dc.identifier.doi10.1109/JEDS.2020.3011409-
dc.identifier.bibliographicCitationIEEE Journal of the Electron Devices Society, v.8, pp.836 - 840-
dc.description.isOpenAccessN-
dc.identifier.scopusid2-s2.0-85089454381-
dc.citation.endPage840-
dc.citation.startPage836-
dc.citation.titleIEEE Journal of the Electron Devices Society-
dc.citation.volume8-
dc.contributor.affiliatedAuthorCho, S.-
dc.type.docTypeArticle-
dc.subject.keywordAuthorenergy efficiency-
dc.subject.keywordAuthorhardware-driven neuromorphic system.-
dc.subject.keywordAuthorlinear weight tunability-
dc.subject.keywordAuthorLogic gates-
dc.subject.keywordAuthorlong-term plasticity (LTP)-
dc.subject.keywordAuthorMathematical model-
dc.subject.keywordAuthorNeuromorphics-
dc.subject.keywordAuthorquantum-well charge-trap synaptic transistor-
dc.subject.keywordAuthorshort-term plasticity (STP)-
dc.subject.keywordAuthorSi-processing compatibility-
dc.subject.keywordAuthorSilicon-
dc.subject.keywordAuthorSilicon germanium-
dc.subject.keywordAuthorTransistors-
dc.subject.keywordAuthorTunneling-
dc.subject.keywordPlusCharge trapping-
dc.subject.keywordPlusElectronic design automation-
dc.subject.keywordPlusEnergy efficiency-
dc.subject.keywordPlusEnergy utilization-
dc.subject.keywordPlusSilicon-
dc.subject.keywordPlusAdjustability-
dc.subject.keywordPlusHigh energy efficiency-
dc.subject.keywordPlusLong term memory-
dc.subject.keywordPlusNeuromorphic systems-
dc.subject.keywordPlusQuantum well structures-
dc.subject.keywordPlusSynaptic events-
dc.subject.keywordPlusTechnology computer aided design-
dc.subject.keywordPlusUltra low energy-
dc.subject.keywordPlusSemiconductor quantum wells-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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