HYPERSPECTRAL IMAGING THIN FILM APPLICATIONS. Dr. Wulf Grählert /

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1 Dr. Wulf Grählert / wulf.graehlert@iws.fraunhofer.de

2 Motivation Coating processes: thin film application process stability What s about Monitoring? Random sampling? Real time analysis? 100% analysis? 2

3 Introduction Hyperspectral Imaging combination of spectroscopy and imaging analysis and evaluation of spatial differences of chemistry morphology topology Hypercube R, T = f(x, y, l) extraction of derived sample features 3

4 Information content monochrome 2 8 = 256 tonal values RGB (2 8 ) 3 = 16,7 Mio. colors monochrome 1 image RGB 3 images image analysis texture, topolgy, shape, structure hyperspectral (2 8 ) 1000 tonal values hyperspectral 1000 images 4

5 APPROACH Information content thin films Influence of layer features reflection properties of samples are influenced by: 1. stack composition 5. substrate defects 2. inclusions 6. contaminations 3. cracks and scratches 7. material gradient 4. (pin) holes 8. thickness gradient Influence of spectral characteristics 5

6 Hyperspectral Imaging line scan (pushbroom) HSI 6

7 Thin film analysis * hard modeling of thickness (d), refraction index (n) and absorption (k) evaluation of interferences Diamor thin film 1 cm DLC steel thin film thickness d refraction index n (@1100 nm) absorption k (@1100 nm) * P. Wollmann, F. Gruber, W. Grählert; 2014, patent pending 7

8 Analysis of conductivity and resistance * hard modeling (interferences) full surface resolution, no limitation to mean value (i.e. 4-point measurement) transparent conductive oxide (TCO) ITO glas photograph 2 cm sheet resistance * P. Wollmann, E. Weißenborn, W. Grählert; 2015, patent pending 8

9 Laser scribing / selective removal * derived feature extraction soft modeling of removal performance pulsed laser track 100 nm HDR nm ITO SiN ratio 150 nm SiN 20 µm organic layer PET foil * P. Wollmann, F. Gruber, W. Grählert; 2015, patent pending Laser power 9

10 Prediction of adhesion strength* derived feature extraction fast soft modeling (< 1 min) duration wedge test: ~500 h * P. Wollmann, F. Gruber, W. Grählert; 2015, patent pending

11 Prediction of water vapor transmission rate (WVTR) * derived feature extraction fast soft modeling (< 1 min) 200 µm duration WVTR determination Calcium test / LDS: h * P. Wollmann, F. Gruber, W. Grählert; 2015, patent pending 11

12 Prozess-Monitoring: HSI Zusammenfassung Service Development Process integration Licensing hardware & test sites continous processes patents feasibility studies, measurements algorithms, evaluation complex surfaces imanto pro

13 Prozess-Monitoring: HSI Zusammenfassung hardware control data recording data pretreatment data evaluation process interface imanto pro

14 Summary coating and process control defect and contamination screening* sample classification substrates metals, glas, polymer (-foils), wafer, ceramics, derived feature extraction process parameters, adhesion strength, wet film thickness, barrier capacity, * P. Wollmann, F. Gruber, W. Grählert; 2015, patent pending 14