Publication:
Surface characterization driven CMP optimization for gallium nitride

dc.contributor.authorKaragöz, Ayşe
dc.contributor.authorSiebert, M.
dc.contributor.authorLeunissen, P.
dc.contributor.authorBaşım, Gül Bahar
dc.contributor.departmentMechanical Engineering
dc.contributor.ozuauthorBAŞIM DOĞAN, Gül Bahar
dc.contributor.ozugradstudentKaragöz, Ayşe
dc.date.accessioned2017-07-26T12:09:19Z
dc.date.available2017-07-26T12:09:19Z
dc.date.issued2016
dc.description.abstractGallium nitride is a hard and chemically inert material demoting high material removal rates in the chemical mechanical planarization (CMP) applications. This paper focuses on the optimization of the process conditions to enhance material removal rates while controlling surface defectivity for GaN CMP. Two different crystallographic orientations of the GaN are characterized and compared to a commercial 2” GaN wafer to optimize the CMP performance on the basis of the wafer crystallographic nature, surface charge and topography. Slurry pH, the type of polishing pad and applied conditioning were evaluated to increase material removal rates of GaN while minimizing defect formation and enhancing the selectivity against silica.en_US
dc.identifier.doi10.1149/07218.0055ecsten_US
dc.identifier.endpage59en_US
dc.identifier.issn1938-5862en_US
dc.identifier.issue18en_US
dc.identifier.scopus2-s2.0-85019765601
dc.identifier.startpage55en_US
dc.identifier.urihttp://hdl.handle.net/10679/5485
dc.identifier.urihttps://doi.org/10.1149/07218.0055ecst
dc.identifier.volume72en_US
dc.language.isoengen_US
dc.peerreviewedyes
dc.publicationstatuspublisheden_US
dc.publisherECSen_US
dc.relation.ispartofECS Transactionsen_US
dc.relation.publicationcategoryInternational
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsChemical mechanical polishingen_US
dc.titleSurface characterization driven CMP optimization for gallium nitrideen_US
dc.typeConference paperen_US
dspace.entity.typePublication
relation.isOrgUnitOfPublicationdaa77406-1417-4308-b110-2625bf3b3dd7
relation.isOrgUnitOfPublication.latestForDiscoverydaa77406-1417-4308-b110-2625bf3b3dd7

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