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Cited 5 time in webofscience Cited 12 time in scopus
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Comparative study on the energy efficiency of logic gates based on single-electron transistor technology

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dc.contributor.authorChoi, Changmin-
dc.contributor.authorLee, Jieun-
dc.contributor.authorPark, Sungwook-
dc.contributor.authorChung, In-Young-
dc.contributor.authorKim, Chang-Joon-
dc.contributor.authorPark, Byung-Gook-
dc.contributor.authorKim, Dong Myong-
dc.contributor.authorKim, Dae Hwan-
dc.date.accessioned2022-12-27T05:11:14Z-
dc.date.available2022-12-27T05:11:14Z-
dc.date.issued2009-06-
dc.identifier.issn0268-1242-
dc.identifier.issn1361-6641-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/26283-
dc.description.abstractThe performance and the power consumption of single-electron transistor (SET) technology-based ultra-energy-efficient signal processing circuits are compared based on the SPICE model including non-ideal effects of the experimental data for the first time. In terms of ultra-energy-efficient logic circuits, the binary decision diagram (BDD) logic circuit is the most promising with a dissipated power of 0.29 nW at V-dd = 0.1 V and f(in) = 50 MHz among the static complementary metal-oxide-semiconductor (CMOS)-like SET logic, the dynamic SET/CMOS hybrid logic, cellular nonlinear network (CNN) and BDD. This result means that the transition of a paradigm substituting the current for the voltage as a state variable of a signal processing is strongly required in post-CMOS signal processing and ultra-energy-efficient applications.-
dc.language영어-
dc.language.isoENG-
dc.publisherIOP PUBLISHING LTD-
dc.titleComparative study on the energy efficiency of logic gates based on single-electron transistor technology-
dc.typeArticle-
dc.publisher.location영국-
dc.identifier.doi10.1088/0268-1242/23/6/065007-
dc.identifier.scopusid2-s2.0-78349257054-
dc.identifier.wosid000266287000015-
dc.identifier.bibliographicCitationSEMICONDUCTOR SCIENCE AND TECHNOLOGY, v.24, no.6-
dc.citation.titleSEMICONDUCTOR SCIENCE AND TECHNOLOGY-
dc.citation.volume24-
dc.citation.number6-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaMaterials Science-
dc.relation.journalResearchAreaPhysics-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryMaterials Science, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryPhysics, Condensed Matter-
dc.subject.keywordPlusTO-DIGITAL CONVERTER-
dc.subject.keywordPlusCELLULAR NEURAL-NETWORKS-
dc.subject.keywordPlusSET MODEL-
dc.subject.keywordPlusDEVICES-
dc.subject.keywordPlusDESIGN-
dc.subject.keywordPlusFABRICATION-
dc.subject.keywordPlusMAJORITY-
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