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Open AccessCommunication
J. Imaging 2016, 2(2), 12; doi:10.3390/jimaging2020012

Quality Control of Slot-Die Coated Aluminum Oxide Layers for Battery Applications Using Hyperspectral Imaging

Department Chemical Surface and Reaction Technology, Fraunhofer Institute for Material and Beam Technology (IWS) Dresden, Winterbergstr. 28, Dresden 01277, Germany
These authors contributed equally to this work.
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Academic Editors: Erik Cuevas and Gonzalo Pajares Martinsanz
Received: 30 November 2015 / Revised: 23 March 2016 / Accepted: 1 April 2016 / Published: 7 April 2016
(This article belongs to the Special Issue Soft Computing in Image Processing)
View Full-Text   |   Download PDF [5083 KB, uploaded 7 April 2016]   |  

Abstract

Hyperspectral inspection using imaging systems is becoming more and more important for quality control tasks in several industries, replacing well trained operators or established machine vision systems based on RGB-systems. Hyperspectral imaging (HSI) on thin coated substrates is challenging due to the high reflectivity of the substrates. Nevertheless, the thin films contribute to the spectral data and can be evaluated. Therefore, the performance of inspection systems can be increased significantly. However, the large amount of data generated by HSI has to be processed and evaluated for quality information about the product. In this paper, thin aluminum oxide (Al2O3) layers on stainless steel foil are investigated by HSI. These substrates can be used for the growth of vertically aligned carbon nanotubes (VA-SWCNT) for battery electrodes. HSI and spectral ellipsometry in combination with Partial Least Squares regression (PLS) was used to estimate the thickness of the Al2O3 layers and to calculate quality parameters for a possible monitoring process. The PLS model shows a R2CV of 0.979 and a RMSECV of 3.6. View Full-Text
Keywords: visual inspection; spectral imaging; partial least squares regression; slot-die coating; aluminum oxide; battery technology; VA-SWCNT visual inspection; spectral imaging; partial least squares regression; slot-die coating; aluminum oxide; battery technology; VA-SWCNT
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Gruber, F.; Wollmann, P.; Schumm, B.; Grählert, W.; Kaskel, S. Quality Control of Slot-Die Coated Aluminum Oxide Layers for Battery Applications Using Hyperspectral Imaging. J. Imaging 2016, 2, 12.

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