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Programmable Threshold Logic Implementations in a Memristor Crossbar Array

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dc.contributor.authorYoun, Sangwook-
dc.contributor.authorLee, Jungjin-
dc.contributor.authorKim, Sungjoon-
dc.contributor.authorPark, Jinwoo-
dc.contributor.authorKim, Kyuree-
dc.contributor.authorKim, Hyungjin-
dc.date.accessioned2024-11-28T14:01:06Z-
dc.date.available2024-11-28T14:01:06Z-
dc.date.issued2024-03-
dc.identifier.issn1530-6984-
dc.identifier.issn1530-6992-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/196726-
dc.description.abstractIn this study, we demonstrate the implementation of programmable threshold logics using a 32 x 32 memristor crossbar array. Thanks to forming-free characteristics obtained by the annealing process, its accurate programming characteristics are presented by a 256-level grayscale image. By simultaneous subtraction between weighted sum and threshold values with a differential pair in an opposite way, 3-input and 4-input Boolean logics are implemented in the crossbar without additional reference bias. Also, we verify a full-adder circuit and analyze its fidelity, depending on the device programming accuracy. Lastly, we successfully implement a 4-bit ripple carry adder in the crossbar and achieve reliable operations by read-based logic operations. Compared to stateful logic driven by device switching, a 4-bit ripple carry adder on a memristor crossbar array can perform more reliably in fewer steps thanks to its read-based parallel logic operation.-
dc.format.extent9-
dc.language영어-
dc.language.isoENG-
dc.publisherAmerican Chemical Society-
dc.titleProgrammable Threshold Logic Implementations in a Memristor Crossbar Array-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1021/acs.nanolett.3c04073-
dc.identifier.scopusid2-s2.0-85187666105-
dc.identifier.wosid001183908200001-
dc.identifier.bibliographicCitationNano Letters, v.24, no.12, pp 3581 - 3589-
dc.citation.titleNano Letters-
dc.citation.volume24-
dc.citation.number12-
dc.citation.startPage3581-
dc.citation.endPage3589-
dc.type.docTypeArticle; Early Access-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaScience & Technology - Other Topics-
dc.relation.journalResearchAreaMaterials Science-
dc.relation.journalResearchAreaPhysics-
dc.relation.journalWebOfScienceCategoryChemistry, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryChemistry, Physical-
dc.relation.journalWebOfScienceCategoryNanoscience & Nanotechnology-
dc.relation.journalWebOfScienceCategoryMaterials Science, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryPhysics, Applied-
dc.relation.journalWebOfScienceCategoryPhysics, Condensed Matter-
dc.subject.keywordPlusMEMORY-
dc.subject.keywordPlusOPERATIONS-
dc.subject.keywordAuthormemristors-
dc.subject.keywordAuthorneuromorphic-
dc.subject.keywordAuthorcomputing-in-memory-
dc.subject.keywordAuthorthreshold logic-
dc.subject.keywordAuthorfull adder-
dc.identifier.urlhttps://pubs.acs.org/doi/10.1021/acs.nanolett.3c04073-
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