Towards in-line real-time characterization of roll-to-roll produced ZTO/Ag/ITO thin films by hyperspectral imaging

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dc.contributor.authorDogan-Surmeier, Susanne
dc.contributor.authorGruber, Florian
dc.contributor.authorBieder, Steffen
dc.contributor.authorSchlenz, Patrick
dc.contributor.authorPaulus, Michael
dc.contributor.authorAlbers, Christian
dc.contributor.authorSchneider, Eric
dc.contributor.authorThiering, Nicola
dc.contributor.authorMaurer, Christian
dc.contributor.authorTolan, Metin
dc.contributor.authorWollmann, Philipp
dc.contributor.authorCornelius, Steffen
dc.contributor.authorSternemann, Christian
dc.date.accessioned2024-07-19T12:23:33Z
dc.date.available2024-07-19T12:23:33Z
dc.date.issued2023-06-08
dc.description.abstractLarge area manufacturing processes of thin films such as large-area vacuum roll-to-roll coating of dielectric and gas permeation barrier layers in industry require a precise control of e.g. film thickness, homogeneity, chemical compositions, crystallinity and surface roughness. In order to determine these properties in real time, hyperspectral imaging is a novel, cost-efficient, and fast tool as in-line technology for large-area quality control. We demonstrate the application of hyperspectral imaging to characterize the thickness of thin films of the multilayer system ZTO/Ag/ITO produced by roll-to-roll magnetron sputtering on 220 mm wide polyethylene terephthalate substrate. X-ray reflectivity measurements are used to determine the thickness gradients of roll-to-roll produced foils with sub nanometer accuracy that serve as ground truth data to train a machine learning model for the interpretation of the hyperspectral imaging spectra. Based on the model, the sub-layer thicknesses on the complete substrate foil area were predicted which demonstrates the capabilities of this approach for large-scale in-line real-time quality control for industrial applications.en
dc.identifier.urihttp://hdl.handle.net/2003/42606
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-24441
dc.language.isoende
dc.relation.ispartofseriesJournal of physics / D, Applied physics;56(36)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/de
dc.subjecthyperspectral imagingen
dc.subjectx-ray reflectivityen
dc.subjectmachine learningen
dc.subjectthickness predictionen
dc.subjectthin filmsen
dc.subject.ddc530
dc.titleTowards in-line real-time characterization of roll-to-roll produced ZTO/Ag/ITO thin films by hyperspectral imagingen
dc.typeTextde
dc.type.publicationtypeArticlede
dcterms.accessRightsopen access
eldorado.secondarypublicationtruede
eldorado.secondarypublication.primarycitationSusanne Dogan-Surmeier et al 2023 J. Phys. D: Appl. Phys. 56 365102de
eldorado.secondarypublication.primaryidentifierhttps://doi.org/10.1088/1361-6463/acd8c9de

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