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  4. Towards in-line real-time characterization of roll-to-roll produced ZTO/Ag/ITO thin films by hyperspectral imaging
 
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2023
Journal Article
Title

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

Abstract
Large 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.
Author(s)
Dogan-Surmeier, Susanne
Technische Universität Dortmund  
Gruber, Florian  
Fraunhofer-Institut für Werkstoff- und Strahltechnik IWS  
Maurer, Christian
Bruker AXS GmbH
Bieder, Steffen
Technische Universität Dortmund  
Schlenz, Patrick
Fraunhofer-Institut für Organische Elektronik, Elektronenstrahl- und Plasmatechnik FEP  
Paulus, Michael
Technische Universität Dortmund  
Albers, Christian
Technische Universität Dortmund  
Schneider, Eric
Technische Universität Dortmund  
Thiering, Nicola
Technische Universität Dortmund  
Tolan, Metin
Technische Universität Dortmund  
Wollmann, Philipp  
Fraunhofer-Institut für Werkstoff- und Strahltechnik IWS  
Cornelius, Steffen  
Fraunhofer-Institut für Organische Elektronik, Elektronenstrahl- und Plasmatechnik FEP  
Sternemann, Christian
Technische Universität Dortmund  
Journal
Journal of Physics. D. Applied Physics  
Project(s)
Multimodal X-ray and Hyperspectral Thin-Film Nano-material Evaluation and Quality Imaging  
Funder
European Commission  
Open Access
DOI
10.1088/1361-6463/acd8c9
Language
English
Fraunhofer-Institut für Organische Elektronik, Elektronenstrahl- und Plasmatechnik FEP  
Fraunhofer-Institut für Werkstoff- und Strahltechnik IWS  
Keyword(s)
  • hyperspectral imaging

  • x-ray reflectivity

  • machine learning

  • thickness prediction

  • thin films

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