Simultaneous In-Line Monitoring of the Conversion and the Coating

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Anal. Chem. 2010, 82, 8088–8094

Simultaneous In-Line Monitoring of the Conversion and the Coating Thickness in UV-Cured Acrylate Coatings by Near-Infrared Reflection Spectroscopy Gabriele Mirschel, Katja Heymann, and Tom Scherzer* Leibniz Institute of Surface Modification (IOM), Permoserstr. 15, D-04318 Leipzig, Germany Near-infrared (NIR) reflection spectroscopy was used for in-line analysis of the conversion and the coating thickness (5-20 µm) of UV-cured clear and pigmented acrylate coatings. The quantitative evaluation of the recorded spectra was carried out by partial least-squares (PLS) regression, in particular with the PLS2 algorithm, which allows simultaneous prediction of both parameters. The efficiency of this method was investigated in roll coating experiments at line speeds up to 100 m min-1. It was shown that the method is able to compensate for the effect of accidental variations of the coating thickness, which inevitably occur upon changes of the line speed, on the prediction of the conversion. Accordingly, the conversion could be determined with a precision of (2...3%, whereas the error in the measurement of the thickness was found to be about 0.5-1 µm. In-line analytical characterization during continuous processes is an issue, which becomes more and more common practice in the technical production of polymer materials. The warranty of increasing quality requirements as well as economic constraints with respect to a more efficient use of raw materials, energy, and other process media lead to a widespread use of process control systems, which help to ensure that the process proceeds within its specifications.1-3 One of the most powerful and versatile analytical methods used for process control is near-infrared (NIR) spectroscopy.4 Its high sensitivity allows measurements with excellent precision, in particular if it is used in combination with chemometric methods for the quantitative evaluation of the data. With respect to in-line monitoring it is highly advantageous, that NIR spectrometers can be equipped with optical fibers, which allow easy implementation in technical production lines. Because of its outstanding performance, NIR spectroscopy has found widespread use in agriculture, food processing, plastic waste sorting, pharmaceutics as well as * To whom correspondence should be addressed. E-mail: tom.scherzer@ iom-leipzig.de. Fax: +49-341-235-2584. (1) Callis, J. B.; Illmann, D. L.; Kowalski, B. R. Anal. Chem. 1987, 59, 624A– 637A. (2) Hassell, D. C.; Bowman, E. M. Appl. Spectrosc. 1998, 52, 18A–29A. (3) Bakeev, K. A. Process Analytical Technology; Blackwell Publishing: Oxford, U.K., 2005. (4) Siesler, H. W.; Ozaki, Y.; Kawata, S.; Heise, H. M., Eds. Near-Infrared Spectroscopy: Principles, Instruments, Applications; Wiley-VCH: Weinheim, Germany, 2002.

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in chemical industry.5 For example, several applications to monitor various polymerization reactions and polymer processing have been proposed in the past.6-11 In contrast, only very few attempts have been made so far to follow photopolymerization reactions by NIR spectroscopy.12-17 Photochemically initiated polymerization of acrylate and epoxy resins is a highly efficient method to produce thin polymer coatings. Because of the broad range of properties, which can be achieved by suitable composition of the lacquer formulation, such coatings are widely used in numerous applications.18,19 The high reaction rates, at which coatings can be cured, allow very high production speeds. However, one of the main problems during UV curing of such coatings is to ensure that the conversion is permanently held on a level, which complies with the requirements of the specific application. This is essential since on the one hand conversion is the key parameter, which directly influences the functional properties of the coatings such as mechanical and chemical resistance, weathering behavior, migration properties as well as processing properties such as wipe resistance. On the other hand, the conversion may be affected by numerous influencing factors. The most important one is the irradiation dose, which is applied to the coating and which depends on irradiance and line speed. Moreover, complex interac(5) Burns, D. A., Ciurczak, E. W., Eds. Near-Infrared Analysis, 3rd ed.; CRC Press: Boca Raton, FL, 2008. (6) Chang, S. Y.; Wang, N. S. In Multidimensional Spectroscopy of Polymers; Urban, M. W., Provder, T., Eds.; American Chemical Society: Washington, DC, 1995; pp 147-165. (7) Vilmin, F.; Dussap, C.; Coste, N. Appl. Spectrosc. 2006, 60, 619–630. (8) Alig, I.; Fischer, D.; Lellinger, D.; Steinhoff, B. Macromol. Symp. 2005, 230, 51–58. (9) Barnes, S. E.; Brown, E. C.; Sibley, M. G.; Edwards, H. G. M.; Scowen, I. J.; Coates, P. D. Appl. Spectrosc. 2005, 59, 611–619. (10) Rey, L.; Galy, J.; Sautereau, H.; Lachenal, G.; Henry, D.; Vial, J. Appl. Spectrosc. 2000, 54, 39–43. (11) Coats, P. D.; Barnes, S. E.; Sibley, M. G.; Brown, E. C.; Edwards, H. G. M.; Scowen, I. J. Polymer 2003, 44, 5937–5949. (12) Siesler, H. W. Macromol. Chem., Macromol. Symp. 1991, 52, 113–129. (13) Kip, B. J.; Berghmans, T.; Palmen, P.; van der Pol, A.; Huys, M.; Hartwig, H.; Scheepers, M.; Wenke, D. Vib. Spectrosc. 2000, 24, 75–92. (14) Botella, A.; Dupuy, J.; Roche, A. A.; Sautereau, H.; Verney, V. Macromol. Rapid Commun. 2004, 25, 1155–1158. (15) Steemann, P. A. M.; Dias, A. A.; Wienke, D.; Zwartkruis, T. Macromolecules 2004, 37, 7001–7007. (16) Lovell, L. G.; Berchthold, K. A.; Elliott, J. E.; Lu, H.; Bowman, C. N. Polym. Adv. Technol. 2001, 12, 335–345. (17) Lu, H.; Lovell, L. G.; Bowman, C. N. Macromolecules 2001, 34, 8021–8025. (18) Fouassier, J. P.; Rabek, J. F. Radiation Curing in Polymer Science and Technology; Elsevier: London, 1993. (19) Mehnert, R.; Pinkus, A.; Janovsky´, I. UV & EB Curing Technology & Equipment; Wiley-SITA: London, 1998. 10.1021/ac100933q  2010 American Chemical Society Published on Web 09/15/2010

tions of the ambient conditions (e.g., inertization, temperature, humidity) and process parameters (composition and homogeneity of the formulation, pollution, and aging of UV lamps) may affect the conversion achieved during irradiation of the coating. Another basic parameter, which has to be monitored during the coating and curing process, is the thickness of the coatings. The thickness can accidentally fluctuate as well, which may result from variations of the temperature and the viscosity of the varnish but also from variations of the line speed. However, several functional properties, such as barrier efficiency, optical appearance, and scratch resistance, depend on the thickness. Hence, it must not fall below a certain level, which is at least required for the specific application. On the other hand, the application of too thick layers should be avoided in order to ensure economic consumption of raw materials. In the past, we reported on the development of an in-line monitoring method for the conversion in UV-cured acrylate coatings, which is based on NIR reflection spectroscopy.20,21 In these studies, a simple band integration method was used for the quantitative evaluation of the spectral data. This approach requires that the thickness of the coatings remains constant all the time. However, this is hardly to guarantee in technical coating processes. Consequently, unintended changes of the thickness may cause incorrect measurements of the conversion. When the conversion was determined by use of chemometric techniques, it was found that accidental fluctuations of the thickness strongly affect these measurements as well, since calibration of the spectra to the conversion was carried out on samples with a specific thickness. So, to get correct results for the conversion, the thickness needs to be considered in the measuring process as well. Therefore, in the next step the NIR method was used to determine the thickness of the coating quantitatively.22-24 Data analysis was based on chemometric methods, that is, partial least-squares (PLS) regression. In in-line experiments, it was shown that variations of the thickness (e.g., after changes of the line speed) could be determined by this method under process conditions. The correction of the conversion data for the effect of changes of the thickness of the coating can be carried out by two different ways. In the previous work,25 we reported on a method, which was based on two NIR probe heads. The probe heads were used to record spectra both before and after UV curing. Quantitative data were obtained according to the Beer-Lambert law, i.e. by integration of the vinyl band in acrylates at 1620 nm (6172 cm-1). The conversion was obtained from the ratio of the band integrals. This way, the effect of thickness on the conversion is inherently compensated for. In the present study, we want to discuss an alternative approach. The variation of the thickness (in the range of 5-20 (20) Scherzer, T.; Mehnert, R.; Lucht, H. Macromol. Symp. 2004, 205, 151– 162. (21) Scherzer, T.; Mu ¨ ller, S.; Mehnert, R.; Volland, A.; Lucht, H. Polymer 2005, 46, 7072–7081. (22) Scherzer, T.; Heymann, K.; Mirschel, G.; Buchmeiser, M. R. J. Near Infrared Spectrosc. 2008, 16, 165–171. (23) Heymann, K.; Mirschel, G.; Scherzer, T.; Buchmeiser, M. R. Vibr. Spectr. 2009, 51, 152–155. (24) Heymann, K.; Mirschel, G.; Scherzer, T. Appl. Spectrosc. 2010, 64, 419– 425. (25) Mirschel, G.; Heymann, K.; Scherzer, T.; Buchmeiser, M. R. Polymer 2009, 50, 1895–1900.

µm) is directly included into the chemometric model for the determination of the conversion. This can be done by use of the PLS2 algorithm, which is able to predict two or more parameters from the same input data.26 This way, conversion and thickness of the coating can be studied independently, which allows simultaneous in-line monitoring of both parameters in technical coating processes. EXPERIMENTAL SECTION Preparation and Characterization of Samples for Calibration. All investigations in this study were carried out with an acrylate formulation made up of an aliphatic urethane diacrylate (EB 270, 2 parts) and an amine modified polyether acrylate (EB 81, 1 part), which was diluted with 10 wt % tripropylene glycol diacrylate (TPGDA). All acrylates were supplied by Cytec Surface Specialties (Drogenbos, Belgium). The amount of photoinitiator (ethyl (2,4,6-trimethylbenzoyl) phenylphosphinate, TPO-L from BASF, Ludwigshafen, Germany) was varied from 0.25 to 1.5 wt % to achieve samples with different conversions. Pigmented coatings were made by addition of 10 wt % of titanium dioxide (Kronos 2300, Kronos Titan GmbH, Leverkusen, Germany) to the clear lacquer formulation. The formulation was applied to polypropylene foil (OPP, 20 µm, Treophan GND 20) by use of a set of Baker applicators (TQC GmbH, Haan, Germany) and an automatic film application machine (SIMEX, Haan, Germany). Samples with nominal thicknesses from 5 to 20 µm were prepared for calibration. UV curing was carried out under inert conditions in a laboratory scale UV curing unit, which is equipped with a 120 W cm-1 medium pressure mercury lamp (IST Strahlentechnik Metz, Nu ¨ rtingen, Germany). Samples were irradiated with various doses between 70 and 700 mJ cm-2 to prepare samples with a broad range of conversions. The resulting thickness of the coatings after UV irradiation was determined with a digital thickness gauge with a resolution of 0.2 µm (Heidenhain ND 221B, Johannes Heidenhain GmbH, Traunreut, Germany). The conversion in the coatings was obtained from FTIR transmission spectra using the acrylate band of the CH2 scissor deformation mode at 1405 cm-1.27 Spectra were recorded with a Digilab FTS 6000 spectrometer before and after UV irradiation. Values obtained from various positions of each sample were averaged for further quantitative analysis. Pilot-Scale Coating Trials. In-line monitoring trials were performed on a pilot-scale roll coating machine at IOM, which is equipped with a medium pressure mercury lamp (160 W cm-1, PrintConcept UV Systeme, Ko ¨ngen, Germany). At a line speed of 10 m min-1, an irradiation dose of 850 mJ cm-2 is achieved. The intensity of the lamp can be varied between 30 and 100% of its maximum power (8 kW). Coatings with different conversions were prepared by irradiation with different UV doses, that is, either by changing the intensity of the UV lamp or by variation of the line speed. The coating thickness was intentionally varied by stepwise increasing the gap between the applicator rolls. Moreover, thickness changes inevitably result from changes of the line speed. (26) Martens, H.; Næs, T. Multivariate Calibration; Wiley: Chichester, U.K., 1989. (27) Colthup, N. B.; Daly, L. H.; Wiberley, S. E. Introduction to Infrared and Raman Spectroscopy, 3rd ed.; Academic Press; San Diego, CA, 1990; p 304.

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Pilot-scale coating trials were carried out with a photoinitiator content of 0.25 wt % in clear coatings and 1.5 wt % in whitepigmented layers. NIR Spectroscopy. NIR spectra were recorded in transflection mode using a Kusta 4004 S process spectrometer unit and a PSPD reflection probe head (LLA, Berlin, Germany). The spectrometer is equipped with an InGaAs photodiode array detector, which covers a range from 1405 to 1915 nm (7117-5222 cm-1) with a spectral resolution of 2 nm. Measurements were carried out against a ceramic reflector behind the sample. A more detailed description of the spectrometer system is given in ref 20. To avoid any influence of postcuring on the calibration procedure to the conversion, NIR spectra for laboratory investigations were recorded immediately after irradiation. Sample stripes were slowly drawn through the focus of the probe beam, while about 1000 accumulations were taken, which were finally averaged to one spectrum. Ten spectra were recorded in this way for each sample. Some typical spectra are shown in Figure S-1 in the Supporting Information. For in-line studies at the roll coating machine, the NIR probe head was mounted above the moving web just behind the UV lamp. Special attention had to be paid to the geometric arrangement of the probe head and the foil, which must be exactly the same like in the laboratory, since even minor differences strongly affect the precision of the results. In order to minimize the effect of the vibrations of the moving foil, the probe head was mounted close to a guide roll. Moreover, it was tilted by 15° against vertical incidence. This leads to a suppression of interferences, which occur in thin transparent polymer films such as the 20 µm OPP foil. NIR spectra were recorded continuously at a rate of 140 spectra min-1. Multivariate data analysis of the spectra was carried out with the software package KustaSpec, which was supplied with the process spectrometer. Most calibration models were based on the PLS2 algorithm, which is able to predict more than one parameter (conversion and coating thickness) from the data sets. For some preliminary investigations, the PLS1 method was used, which can handle either conversion or thickness data. RESULTS AND DISCUSSION Effect of Changes of the Coating Thickness on the InLine Monitoring of the Conversion. In technical coating processes, unintended changes of the thickness of the applied layers may occur. Such changes can result from variations in temperature, viscosity, etc. Moreover, they can be also caused by simple changes of the line speed. The extent of such changes depends on the specific application method and the speed range. A typical example of the effect of the web speed on the resulting thickness in roll coating is shown in Figure 1. When the speed is increased from 10 to 80 m min-1, the thickness of the coating increases by more than 40%, although the gap between the applicator rolls was not changed. Additionally, the conversion, which was reached in the coatings during irradiation, was determined. It was monitored in-line with NIR reflection spectroscopy by use of a PLS1 calibration model, which has been established previously.25 For comparison, the conversion was also determined off-line by using FTIR spectros8090

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Figure 1. Effect of the web speed on the thickness of a coating applied by roll coating (with constant gap between the applicator rolls) and its impact on the in-line determination of the acrylate conversion by NIR spectroscopy using a former PLS model.25 Conversion data determined off-line by FTIR spectroscopy are given for comparison.

copy. Results of both methods are plotted in Figure 1 as well. It is obvious, that they are in accordance at low line speeds only, whereas they more and more differ from each other at speeds higher than 20 m min-1. The conversion predicted from NIR in-line data seemingly stronger drops down with increasing line speed than the reference values. It has been shown that this discrepancy is due to the change of the coating thickness upon increase of the line speed.25 The PLS1 calibration to the conversion was carried out with samples with a well-defined thickness (nominal thickness 10 µm). Since the spectra are not only influenced by the conversion of the samples, but also by their thickness, correct predictions of the conversion are only obtained for samples with a thickness around 10 µm, which in fact can be observed in Figure 1. With increasing line speed, the coating thickness more and more increases, which leads to an increasing divergence between the predicted and the actual conversion. Therefore, the effect of the changing coating thickness needs to be considered, when the conversion is determined in-line. In the previous paper,25 it was shown, that correct conversion data can be determined from the ratio of the band integrals of the acrylate band at 1620 nm (6172 cm-1), when separate spectra are taken before and after UV irradiation by use of two NIR probe heads. This way, the influence of variations of the thickness on the acrylate conversion is compensated for. This method works without chemometrics and consequently does not require extensive calibration. However, an additional probe head is needed. In the present study, another approach will be presented, which is based on chemometrics. When the PLS1 algorithm is replaced by the PLS2 method, the variation of the thickness can be directly included into the chemometric model for the determination of the conversion. This method is not only expected to correct the conversion for the influence of the thickness fluctuations, but it also allows simultaneous monitoring of both conversion and thickness from the same input data. In the chemometric literature, it is sometimes recommended to avoid the use of the PLS2 algorithm in favor of the consecutive application of two PLS1 calibrations, which is reported to result

Table 1. Effect of Various Pretreatments of the Spectra of Clear Acrylate Coatings on the Resulting PLS2 Model model

spectral range [nm]

pretreatment

RMSEP (conversion) [%]

RMSEP (thickness) [µm]

R2 (conversion)

R2 (thickness)

1 2 3 4 5 6

1405-1915 1405-1915 1405-1840 1405-1915 1405-1840 1405-1915

none normalization normalization 1st derivative 1st derivative 2nd derivative

4.221 4.117 3.973 3.575 3.090 3.476

1.659 1.531 1.374 1.120 0.981 1.355

86.87 87.32 88.71 91.74 92.96 90.99

87.41 88.15 88.01 89.57 92.03 83.98

in higher precision of the individual parameters to be predicted.28 Therefore, all calculations in this study were carried out with both the PLS2 approach and with combined PLS1 calibration models. Results are given in the Supporting Information in Tables S-1 and S-2. Generally, the PLS2 method was found to lead to better results. For this reason, it was preferred in this work. Development of PLS2 Calibration Models. Calibration Model for Clear Lacquer Formulations. The use of multivariate analytical methods requires the development of dedicated calibration models, which have to relate the spectral information to the parameters of interest. If the model should be used for the prediction of more than one parameter, calibration has to be carried out to the complete range of each parameter, which may occur during application of the model. Moreover, for a sufficient stability of the model, an adequate amount of samples is required for calibration. Therefore, for the development of a PLS2 model for the calibration to the conversion and the coating thickness, 160 samples with different conversions and thicknesses were prepared. Their actual conversion after UV irradiation was determined by FTIR transmission spectroscopy. Since NIR spectra in in-line monitoring have to be measured directly after UV curing, FTIR spectra were recorded immediately after UV irradiation as well to avoid significant postcuring, which would otherwise affect the precision of the prediction. The samples covered a conversion range from 50 to almost 100% and coating thicknesses from 5 to 20 µm. The thickness of cured layers was found to be lower than that of uncured coatings because of shrinkage, which occurs during UV curing of acrylates. The spectral data were split into a calibration set with 100 samples and a validation set with 60 samples. On the basis of these data sets, a number of chemometric models were developed using the PLS2 algorithm and the test set validation method. The models were optimized by variation of the preprocessing methods, which were applied to the spectra (normalization, derivatives, etc.), and optional limitation of the spectral range. The latter might be required, for instance, to exclude the absorption range of water vapor, since the atmospheric humidity may vary rapidly, which has a strong negative impact on the prediction performance of the models. All chemometric models were evaluated on the basis of the root-mean-square error of prediction (RMSEP) and the coefficient of determination (R2), which is a measure of the explained variance (i.e., the variance of the model’s predictions in comparison with the total variance of the data). Table 1 summarizes the effect of various spectral pretreatments on the parameters of a selected PLS2 model. Model 5 shows the highest R2 and one of the lowest RMSEP. Therefore, this model was selected for further investigations. (28) Brereton, R. Chemometrics: Data Analysis for the Laboratory and the Chemical Plant; Wiley: Chichester, U.K., 2003.

The corresponding calibration data are shown in Figure 2. For reasons of clarity, the calibration curves to the conversion and the thickness of the coating are given separately as 2D projections from the multidimensional model. The capability of the developed model to predict the properties of unknown samples from their NIR spectra was verified with additional samples, which were included neither in the calibration nor in the validation set. For both conversion and thickness a close correlation with reference data from FTIR spectroscopy or thickness gauge, respectively, was found (conversion SD ) 3.1%, r2 ) 0.955; thickness SD ) 1.8 µm, r2 ) 0.956), which confirms the high performance of the developed PLS2 calibration model. In particular, it could be proven that variations of the thickness do not any longer affect the correct determination of the acrylate conversion.

Figure 2. PLS2 calibration for clear acrylate coatings: Projection of the calibration data to the conversion (a) and the thickness variable (b), respectively. Analytical Chemistry, Vol. 82, No. 19, October 1, 2010

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Table 2. Effect of Various Pretreatments of the Spectra of Pigmented Acrylate Coatings on the Resulting PLS2 Model model

spectral range [nm]

pretreatment

RMSEP (conversion) [%]

RMSEP (thickness) [µm]

R2 (conversion)

R2 (thickness)

1 2 3 4 5 6

1405-1915 1405-1840 1405-1840 1405-1915 1405-1840 1405-1915

none none normalization 1st derivative 1st derivative 2nd dervative

4.194 3.728 3.699 3.997 4.298 4.480

0.978 0.953 0.914 1.019 1.030 1.092

83.83 87.93 90.93 89.74 86.23 84.99

79.36 81.07 88.01 82.61 80.17 78.98

Calibration Model for White-Pigmented Lacquer Formulations. White-pigmented systems are widely used in technical applications. However, UV curing of such coatings is a challenging task because of the effect of the pigments, which prevent sufficient penetration of UV light into the deeper layers of the coating. Depending on the pigment concentration, this may lead to a distinct conversion gradient, even if an acylphosphineoxide photoinitiator, such as TPO-L, whose absorption spectrum is adapted to this application, is used for initiation.29 The conversion gradient may have significant consequences for the application properties of the coatings, in particular for the adhesion to the substrate. Therefore, monitoring of the conversion is even more important in pigmented than in clear lacquer formulations. Titanium dioxide, which is the most important white pigment, does not significantly absorb in the near-infrared,30 which allows a reasonably homogeneous penetration of NIR radiation into pigmented layers. In fact, it was already shown previously,21,24,25 that NIR spectroscopy can be used for the determination of the conversion in thick pigmented coatings. In the present study, both conversion and coating thickness in pigmented coatings shall be determined by use of the chemometric approach on the basis of the PLS2 algorithm. The outline of the calibration procedure was the same like for the clear coatings. The acrylate formulation was pigmented with 10 wt % titanium dioxide, and samples with different conversions and coating thicknesses were prepared (distribution see Figure S-2 in the Supporting Information). After division of the data of the 170 samples into calibration and validation set, a chemometric model was built up and optimized by application of various pretreatments to the spectra. The influence of these pretreatments on the parameters of the calibration model is summarized in Table 2. The PLS2 model with the best parameters (model 3) was obtained by simple minimum-maximum normalization of the NIR spectra and exclusion of the hydroxyl absorption region beyond 1840 nm (5435 cm-1). It was used for subsequent in-line monitoring trials. Figure 3a and b shows the calibration curves to the conversion and the coating thickness, respectively. Again, the performance of the chemometric model was evaluated with independent test samples. A close correlation of the predicted conversion and thickness with the corresponding reference values was found (conversion SD ) 3.8%, r2 ) 0.964; thickness SD ) 1.1 µm, r2 ) 0.902), which also means that there is no effect of the thickness on the determination of the conversion.

In-Line Monitoring of Conversion and Coating Thickness in Roll Coating Trials. Clear Coatings. The predicting performance of the PLS2 calibration models was evaluated in several pilot-scale coating trials, which were carried out on a roll coating machine. At first, it was used to follow conversion and coating thickness of acrylic clear coats. Both parameters were varied jointly by incremental increasing of the line speed from 20 to 100 m min-1. In contrast, the power of the UV lamp was kept constant. NIR spectra were taken continuously, that is, at a sampling rate of 2.3 spectra s-1. At line speeds up to 60 m min-1, spectra were recorded for 1 min, at higher speeds for 30 s only. Both the conversion and the thickness were predicted from each spectrum by use of the PLS2 calibration shown in Figure 2a and b. The results given in Figure 4 show the predicted data for the various web speeds. For comparison, mean reference values, which were determined off-line after the end of the machine trial, are provided.

(29) Scherzer, T. Appl. Spectrosc. 2002, 56, 1403–1412. (30) Batra, J.; Khettry, A.; Hansen, M. G. Polym. Eng. Sci. 1994, 34, 1767– 1772.

Figure 3. PLS2 calibration for pigmented acrylate coatings: Projection of the calibration data to the conversion (a) and the coating thickness (b), respectively.

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Figure 4. In-line monitoring of the conversion and the coating thickness of a clear acrylate coating at various line speeds. For comparison, actual values obtained off-line by reference methods are shown.

The acrylate conversion decreased in accordance with the stepwise decrease of the applied irradiation dose. After each change of the line speed, an immediate response of the conversion could be observed. Moreover, the increase of the line speed also led to variations of the thickness of the coating, although the nip between the applicator rolls was kept constant. At low line speeds up to 60 m min-1, a slight increase of the thickness of the coating was observed. However, at higher line speeds, this trend was found to reverse, that is, the coating thickness decreased again. The rise and the fall of the thickness of coatings with increasing web speed is a well-known phenomenon in roll coating technology. It is attributed to complex interactions between several physical and technological factors. Acrylate formulations are non-Newtonian fluids. Consequently, their viscosity depends on the shear rate. Numerical simulations31,32 clearly confirm the influence of rheological parameters, such as viscosity, capillary, and Reynolds number, etc., as well as their dependence on temperature and shear rate on the applied thickness. Moreover, they also substantiate the effect of the rotational speed of the applicator rolls. During the complete pilot-scale coating trial, close correlation was observed between the results, which were obtained from the NIR spectra by use of the PLS2 calibration model, and the reference data, which were determined by either FTIR spectroscopy or the thickness gauge, respectively. The average deviation of the predicted values from the reference data was maximum 3% for the conversion and less than 1 µm for the coating thickness. These results clearly demonstrate that NIR reflection spectroscopy in combination with the PLS2 algorithm is effectively able to compensate for the effect of unavoidable thickness changes on the determination of the acrylate conversion and to monitor in this way both process parameters simultaneously. White-Pigmented Coatings. The PLS2 calibration model, which was developed for the white-pigmented system, was tested in a pilot-scale study on the roll coating machine as well. Similarly to the trial with the clear acrylate formulation, the applied irradiation dose was varied by changing the web speed, which was stepwise (31) Greener, Y.; Middleman, S. Polym. Eng. Sci. 1975, 15, 1–10. (32) Hao, Y.; Haber, S. Int. J. Numer. Meth. Fluids 1999, 30, 635–652.

Figure 5. In-line monitoring of the conversion and the coating thickness of a white-pigmented acrylate coating at various line speeds. For comparison, actual values obtained off-line by reference methods are shown.

increased from 20 to 80 m min-1 at constant power of the UV lamp. NIR spectra were recorded for 1 min at line speeds up to 50 m min-1 and for 30 s at the two higher speeds. The results of a typical in-line monitoring trial are shown in Figure 5. As expected, both conversion and thickness of the pigmented coatings show similar behavior like in clear acrylic coatings. Accordingly, it can be seen in Figure 5 that the acrylate conversion decreases with increasing line speed. However, in comparison with the clear coating shown in Figure 4, the effect of the decreasing irradiation dose on the conversion in the pigmented coating is much stronger, although similar irradiation conditions have been chosen. Whereas at a web speed of 80 m min-1 about 65% of the acrylic double bonds in the clear coat were converted, the conversion in the pigmented layer is only 53%. It is obvious that this difference is related to the pigment particles dispersed in the lacquer formulation. All white pigments show a high degree of reflection and scattering of the incident light in almost the complete spectral region, which impairs the penetration of light into the deeper lying layers, at least in comparison to unpigmented systems. Consequently, the decrease of the conversion observed in the roll coating experiment shown in Figure 5 is due to the combined effect of the increasing thickness of the coating and the screening effect of the pigments. Similar to the observations for the clear coating, the thickness of the pigmented coating increases by about 2 µm, when the line speed is raised from 20 to 50 m min-1, what is followed by a slight decline at even higher speeds. Reference values, which were determined off-line and which are shown in Figure 5 as well, perfectly match the in-line data. The average deviation of the latter from the reference data was less than 2% for the conversion and less than 0.5 µm for the coating thickness. These results show that conversion and coating thickness can be simultaneously monitored under process conditions by use of NIR reflection spectroscopy also for pigmented coatings, if powerful multivariate methods, such as the PLS2 algorithm, are used for quantification of the spectral data. CONCLUSIONS Changes of the thickness of UV-cured coatings, which may occur accidentally in technical coating processes as a consequence Analytical Chemistry, Vol. 82, No. 19, October 1, 2010

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of changes of the ambient conditions or process parameters (e.g., temperature, line speed, etc.), had been found to preclude the correct determination of the conversion after UV irradiation by NIR spectroscopy assisted by chemometric evaluation methods. In the present study, it was shown, that these problems can be overcome by multivariate calibration models, which make use of the PLS2 algorithm, that is, this method compensates for the influence of the thickness on the determination of the conversion. The efficiency of this approach was demonstrated in several pilot scale roll coating experiments. The predicted thickness and conversion data were compared with reference data, which were determined off-line by independent methods. Depending on the specific lacquer formulation, the conversion could be determined with a precision of ±2...3% whereas the error in the measurement of the thickness was found to be ∼0.5-1 µm. Hence, this high accuracy as well as the sampling rate, which can be achieved, enable the use of this analytical method for technical process control.

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ACKNOWLEDGMENT The authors wish to acknowledge the financial support by the AiF association (Berlin/Cologne, Germany), which was given under the grant number KF 0189 603 FK6. Moreover, we are grateful to Udo Trimper and So¨ren Pyczak (IOM) for technical assistance with the pilot-scale experiments and LLA GmbH (Berlin, Germany) for continuous support of this project.

SUPPORTING INFORMATION AVAILABLE Additional material as described in the text. This material is available free of charge via the Internet at http://pubs.acs.org.

Received for review April 9, 2010. Accepted August 16, 2010. AC100933Q