- Email: [email protected]
Rapid characterization of plastics using laser-induced plasma spectroscopy (LIPS)
ARTICLE IN PRESS
POLYMER TESTING Polymer Testing 25 (2006) 623–627 www.elsevier.com/locate/polytest
Analysis Method
Rapid characterization of plastics using laser-induced plasma spectroscopy (LIPS) Jesu´s Anzano, Marı´ a-Esther Casanova, Marı´ a-Soledad Bermu´dez, Roberto-Jesu´s Lasheras Laser Analytical Spectroscopy Lab, Department of Analytical Chemistry, Faculty of Sciences, University of Zaragoza, Pedro Cerbuna #12, 50009-Zaragoza, Spain Received 10 March 2006; accepted 19 April 2006
Abstract In the recycling of post-consumer plastic waste there is a pressing need for rapid, on-line or at-line measurement technologies for simple identification of the various commercial plastic materials. These include widely used household and industrial plastics such as polyethylene terephthalate (PET), high-density polyethylene (HDPE), polyvinyl chloride (PVC), low-density polyethylene (LDPE), polyethylene (PE), polypropylene (PP) and polystyrene (PS). To maintain the economics of recycling with extremely large volumes of waste materials, rapid, correct identification of these plastics is crucial. The goal of this work was instant identification of post-consumer plastics by laser-induced plasma spectrometry (LIPS). LIP spectra from plastics in a 200–800 nm spectral window were compared with reference spectral libraries stored in a computer. The libraries consisted of representative spectra from different groups of recycled plastic samples. The plasma emission spectra of PET, HDPE, PVC, LDPE, PP and PS were studied. Simple statistical correlation methods including linear and rank correlations were used. This technique is useful for application to the recycling of plastics. r 2006 Elsevier Ltd. All rights reserved. Keywords: LIPS; Laser-induced breakdown spectroscopy; Correlation analysis; Plastics
1. Introduction Although plastic materials are relatively new, they have become basic and indispensable in our life. To provide against contamination and conserve them, food products are distributed in different plastic packages: bags, bottles, boxes, etc that Corresponding author. Tel.: +34 976 762684;
fax: +34 976 761292. E-mail address: [email protected] (J. Anzano). URL: http://www.unizar.es/janzano. 0142-9418/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.polymertesting.2006.04.005
contain all kinds of edible products: liquid (water, milk, cold beveragesy) or solid (fruit, meat, fish, frozen foods, etc.). The group of commercial plastics, also termed commodity plastics, consists of the most used polymers in terms of volume and number of applications. They are mainly polystyrene (PS), polypropylene (PP), high- and low-density polyethylene (HDPE, LDPE), polyethylene terephthalate (PET) and, in lower proportion, polycarbonate (PC). [1] Raman spectroscopy has also been evaluated for discrimination between plastics. Raman spectra
ARTICLE IN PRESS 624
J. Anzano et al. / Polymer Testing 25 (2006) 623–627
have an abundance of sharp, well-resolved bands and provide structural fingerprint information that can be investigated for uniquely identifying plastics. It is demonstrated the potential of Raman spectroscopy for computerized classification of common post-consumer plastics. Moreover, it is able to discriminate between HDPE and LDPE.[2] Infrared spectroscopy is one of the most important techniques to identify plastics and has been subject to great development. For example, the identification of plastics by infrared absorption using InGaAsP laser diode [3], or the combination of IR spectroscopy and a flexible pyrolysis probe for rapid identification of plastics [4], and the application of a spectroscopic infrared focal plane array sensor for remote and on-line measurements on a macroscopic scale [5]. LIPS has been applied to polymer samples in order to investigate the possibility of using this method for the identification of different materials [6–8]. For some cases, LIPS can be used to complement NIR spectroscopy which can also be applied for the identification of polymer, as mentioned previously. However, it is not suitable for dark-coloured samples. Some studies have investigated different effects during laser polymer ablation: co-occurrence of photochemical and thermal effects using 248-nm excimer laser [9] modification of surfaces after excimer laser treatment [10] or characteristics of the plume generated [11]. Laser-induced plasma using a compact Nd:YAG laser has also been used for recycled plastic materials identification [12]. This method has been developed for instant reliable classification (90–99%) of different groups of plastic materials by means of statistical correlation analysis. Although a limitation exists for identification because of the loss of molecular information in the plasma, the technique has excellent potential for online, real-time analysis of recycled materials, which is really of interest in order to obtain plastics separation faster and more effective. Nd:YAG laser has been used for other applications due to its simplicity, easy operation, high efficiency, low cost and suitability. Despite all works and publications on LIPS that have appeared in recent years, the laser plasma can offer new advantages for plastics identification and separation in accordance with new exigencies of polymer industry and science. In previous papers [13] we have shown that simple statistical correlation methods, such as linear and rank correlations, can be successfully applied for
identification of solid and particulate materials. A compact LIP spectrometer was used for instant identification of solids. Spectra were collected with a compact dual channel fibre optic spectrometer and monitored either in a 230–310 nm or a 200–800 nm spectral window. Parametric (linear) and nonparametric (rank) correlation methods were applied for identification of steel and cast iron samples which had very similar composition. A nearly 100% reliable identification was achieved. In the other work, identification of particulate materials, such as iron ores and iron oxides, also yielded nearly 100% accuracy. In this paper, we demonstrate the application of parametric (linear) and non-parametric (rank) correlations for identification of various plastics. The goal of this work is to use LIPS, in which plasma is made by means of a Nd:YAG laser, to obtain household plastics spectra in order to identify them such a simple, fast, low cost and effective method. Their success is based on the use of thousands of data points (pixels) representing the sample spectrum in a relatively large spectral window.
2. Experimental 2.1. Samples used The samples were plastic materials used for Spanish food containers, they were known a priori from recycling marks on the containers. Table 1 shows the analysed samples, colour, trademark and the type of polymer they belong to.
Table 1 Recycled plastic samples Library samples Polyethylene terephthalate (PET) High-density polyethylene (HDPE) Low-density polyethylene (LDPE) Polypropylene (PP) Polystyrene (PS) Identification samples PET-1: Water plastic bottle, blue HDPE-1: Yoghourt container, white LDPE-1: Bread container, blue and white PP-1: Chocolate mousse container, white PS-1: Rice and milk container, white
ARTICLE IN PRESS J. Anzano et al. / Polymer Testing 25 (2006) 623–627
2.2. Sample preparation
625
DAQCard—700 interface (National Instruments, USA).
Little sample preparation was necessary. The result is increased throughput, greater convenience and fewer opportunities for contamination to occur. The food containers were cut into small pieces (approximately 3 3 cm) and then they were placed on a double-sided tape stuck to a glass slide. The piece of plastic must be completely stuck to the slide in order to avoid air between them. In some cases this was not possible so it also required one-sided tape stuck to the extremes of the plastic. Five randomly chosen plastics, belonging to five different types, were used to construct a library, whereas other samples were used as subjects for identification. 2.3. Instrumentation and instrumental parameters The equipment used (Fig. 1) consisted of a Nd:YAG laser (Quantel, model Ultra CFR). The laser and the spectrometer are synchronized by a trigger pulse from a home-made compact pulse generator. The radiation from the laser spark is collected with a bifurcated optical fibre connected to a dual-channel Ocean Optics mini spectrometer (SD2000, Ocean Optics, Inc., Dunedin, FL, USA). The spectrometer has the following characteristics: channel one (slave), 230–310 spectral range; and channel two (master), 200–850 spectral range. The spectrometer is driven from a laptop computer (hp invent, Omnibook XE3) via a
2.4. LIPS libraries Three LIPS libraries were compiled for identification of the six recycled plastic materials: PET, HDPE, LDPE, PP and PS. The library spectra were obtained by inducing the laser spark on 10 random surface spots and averaging the resulting 10 emission spectra. All libraries were stored in a computer and used on a day-to-day basis without being renewed. A program for correlation analysis was developed using Visual Basic 6.0 and the LabView drivers supplied with the Ocean Optics spectrometer. The computer calculates all mutual correlation coefficients between the current spectrum and all library spectra [11]. 3. Results and discussion 3.1. Instrumental parameters The most important instrumental parameters studied were the position of the optical fibre, the optimum energy, the slow wasting of the plastic and the homogeneity of the sample. Before starting we used one of the samples to optimise the response of the optical fibre. It consisted of moving the fibre until the moment at
Fig. 1. Instrumentation set up
ARTICLE IN PRESS J. Anzano et al. / Polymer Testing 25 (2006) 623–627
626
which we obtained the solid angle and the spectrum showed in the computer was the best one. The optimum energy of the laser pulse was studied in some samples. Different energy laser pulses (the energy ranged between 1 and 10) were used and, after that, the 10 spectra were compared. The best spectrum (with the most resolved and high peaks) belonged to the optimum energy which was 7 in most of the cases. The homogeneity of the sample was studied by shooting at different points of the sample. The spectra we obtained were very similar so
the conclusion was that the sample was homogeneous. 3.2. Characterization of plastic containers of food Molecular materials like plastics are almost entirely atomized when exposed to intense laser radiation sufficient for breakdown. This implies that limitations exist in application of LIPS for identification of polymers because of the loss of molecular information in the plasma. However, as will be shown below, the large amount of spectroscopic
500
600
LDPE
HDPE 500
PP
500
400 400
Intensity (counts)
400 300 300 300 200 200
200 100
100
100
0
0 100 200 300 400 500 600 700 800 900
0
100 200 300 400 500 600 700 800 900
Wavelength (nm)
Wavelength (nm)
100 200 300 400 500 600 700 800 900
Wavelength (nm)
600
600 550
PS
PET 500
500 450
400
Intensity (counts)
400 350
300
300 250
200
200 150
100
100 50
0
0 -50 100 200 300 400 500 600 700 800 900
Wavelength (nm)
100 200 300 400 500 600 700 800 900
Wavelength (nm)
Fig. 2. Spectra from high-density polyethylene (HDPE), low-density polyethylene (LDPE), polypropylene (PP) polystyrene (PS) and polyethylene terephthalate (PET).
ARTICLE IN PRESS J. Anzano et al. / Polymer Testing 25 (2006) 623–627
data (2048 pixels-points), used all at once in the correlation procedure, allows original information about the sample nature to be obtained. The correlation methodology was first applied to ‘‘library’’ plastics. Ten shot-averaged spectra from these samples are shown in Fig. 2. The most prominent feature in all the spectra is an unresolved group of N II lines near 500 nm due to atmospheric nitrogen. A group of O II lines also appear in the region 350–450 nm and the O I triplet at 777.2–777.5 nm is also visible. Other features include a strong carbon line at 247.86 nm and the H line at 656.28 nm. Each emission spectrum consists of 2048 points (pixels); therefore enough statistical material is available to permit the use of simple correlation methods like linear correlation and non-parametric rank correlation. Besides the apparent differences in correlation coefficients, strict statistical criteria must be used in order to quantify the level of significance of these differences. To do this, we applied a simple Student’s t-test. The values for the Student’s t were calculated differently depending on whether the two distributions had the same or different variances. To check this, an F-test was applied (F denoting the ratio of the variances). If the calculated significance of F did not exceed 0.1, the difference in variances was considered as significant and t was calculated in a slightly different way than in the case where the distributions had the same variances. On the basis of these t-values, the probabilities that two distributions of correlation coefficients had different means were calculated. The results of these calculations are shown in Table 2. The diagonal elements in Table 2 correspond to the correlation of the sample with itself, all exhibiting a zero probability of difference. All the probabilities given in the table as unity differ from unity by negligibly small Table 2 Calculated probabilities that differences plastics reference samples for the library were detected using 10 shot averaged library spectra Corr. type Linear correlation (rank correlation) Sample
PET
HDPE
LDPE
PET-1 HDPE-1 LDPE-1 PP-1 PS-1
0 1 1 1 1
1 0 1 1 1
1 (1) 1 (1) 0.9987 (1) 0.9934 (0.9987) 0 (0) 0.9943 (0.9994) 1 (1) 0 (0) 1 (1) 0.9965 (0.9979)
(0) (0.9992) (1) (1) (1)
(1) (0) (1) (0.9878) (1)
PP
PS 1 1 1 1 0
(1) (1) (1) (1) (0)
627
numbers, less than 10 8. As seen from Table 2, both correlations show very high (499%) probabilities of correct identification, for both the linear and rank correlation. 4. Summary A compact laser-induced plasma spectrometer has been developed for instant reliable classification of different groups of plastic materials by using statistical correlation analysis. A software package was developed combining both data acquisition and data processing functions. Linear and non-parametric (rank) correlations were applied for classification of spectral data with approximately the same results. The robustness of the technique was demonstrated by the 90–99% reliable identification of almost all analysed plastics. The technique has excellent potential for on-line, real-time analysis of recycling materials. Acknowledgment This work was supported by Spanish Environmental Government 2.7-241/2005/ 2-B. References [1] http://www.pharmaportal.com.ar/tem-packaging-02.htm. [2] V. Allen, J.H. Kalivas, R.G. Rodrı´ guez, Appl. Spectrosc. 53 (6) (1999) 672. [3] K. Inada, R. Matsuda, C. Fujiwara, M. Nomura, T. Tamon, I. Nishihara, T. Takao, T. Fujita, Resour. Conserv. Recycling 33 (2001) 131. [4] A. Murase, N. Sato, Appl. Spectrosc. 53 (6) (1999) 745. [5] W.H.A.M. Van den Broek, D. Wienke, W.J. Melssen, R. Feldhoff, T. Huth-Fehre, T. Kantimm, L.M.C. Buydens, Appl. Spectrosc. 51 (6) (1997) 856. [6] D.R. Anderson, C.W. McLeod, T.A. Smith, J. Anal. At. Spectrom. 9 (2) (1994) 67. [7] H. Fink, U. Panne, R. Niessner, Anal. Chim. Acta 440 (1) (2001) 17. [8] H. Fink, U. Panne, R. Niessner, Anal. Chem. 74 (17) (2002) 4334. [9] Y. Feng, Z.Q. Liu, X.-S. Yi, Appl. Surf. Sci. 156 (2000) 177. [10] P. Laurens, M.O. Bouali, F. Meducin, B. Sadras, Appl. Surf. Sci. 154 (2000) 211. [11] D.K.Y. Low, M.J.J. Schmidt, L. Li, Appl. Surf. Sci. 168 (2000) 170. [12] R. Sattmann, I. Mo¨nch, H. Krause, R. Noll, S. Couris, A. Hatziapostolou, A. Mavromanolakis, C. Fotakis, E. Larrauri, R. Miguel, Appl. Spectrosc. 52 (3) (1998) 456. [13] I.B. Gornushkin, A. Ruiz-Medina, J.M. Anzano, B.W. Smith, J.D. Winefordner, J. Anal. At. Spectrom. 15 (2000) 581.
POLYMER TESTING Polymer Testing 25 (2006) 623–627 www.elsevier.com/locate/polytest
Analysis Method
Rapid characterization of plastics using laser-induced plasma spectroscopy (LIPS) Jesu´s Anzano, Marı´ a-Esther Casanova, Marı´ a-Soledad Bermu´dez, Roberto-Jesu´s Lasheras Laser Analytical Spectroscopy Lab, Department of Analytical Chemistry, Faculty of Sciences, University of Zaragoza, Pedro Cerbuna #12, 50009-Zaragoza, Spain Received 10 March 2006; accepted 19 April 2006
Abstract In the recycling of post-consumer plastic waste there is a pressing need for rapid, on-line or at-line measurement technologies for simple identification of the various commercial plastic materials. These include widely used household and industrial plastics such as polyethylene terephthalate (PET), high-density polyethylene (HDPE), polyvinyl chloride (PVC), low-density polyethylene (LDPE), polyethylene (PE), polypropylene (PP) and polystyrene (PS). To maintain the economics of recycling with extremely large volumes of waste materials, rapid, correct identification of these plastics is crucial. The goal of this work was instant identification of post-consumer plastics by laser-induced plasma spectrometry (LIPS). LIP spectra from plastics in a 200–800 nm spectral window were compared with reference spectral libraries stored in a computer. The libraries consisted of representative spectra from different groups of recycled plastic samples. The plasma emission spectra of PET, HDPE, PVC, LDPE, PP and PS were studied. Simple statistical correlation methods including linear and rank correlations were used. This technique is useful for application to the recycling of plastics. r 2006 Elsevier Ltd. All rights reserved. Keywords: LIPS; Laser-induced breakdown spectroscopy; Correlation analysis; Plastics
1. Introduction Although plastic materials are relatively new, they have become basic and indispensable in our life. To provide against contamination and conserve them, food products are distributed in different plastic packages: bags, bottles, boxes, etc that Corresponding author. Tel.: +34 976 762684;
fax: +34 976 761292. E-mail address: [email protected] (J. Anzano). URL: http://www.unizar.es/janzano. 0142-9418/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.polymertesting.2006.04.005
contain all kinds of edible products: liquid (water, milk, cold beveragesy) or solid (fruit, meat, fish, frozen foods, etc.). The group of commercial plastics, also termed commodity plastics, consists of the most used polymers in terms of volume and number of applications. They are mainly polystyrene (PS), polypropylene (PP), high- and low-density polyethylene (HDPE, LDPE), polyethylene terephthalate (PET) and, in lower proportion, polycarbonate (PC). [1] Raman spectroscopy has also been evaluated for discrimination between plastics. Raman spectra
ARTICLE IN PRESS 624
J. Anzano et al. / Polymer Testing 25 (2006) 623–627
have an abundance of sharp, well-resolved bands and provide structural fingerprint information that can be investigated for uniquely identifying plastics. It is demonstrated the potential of Raman spectroscopy for computerized classification of common post-consumer plastics. Moreover, it is able to discriminate between HDPE and LDPE.[2] Infrared spectroscopy is one of the most important techniques to identify plastics and has been subject to great development. For example, the identification of plastics by infrared absorption using InGaAsP laser diode [3], or the combination of IR spectroscopy and a flexible pyrolysis probe for rapid identification of plastics [4], and the application of a spectroscopic infrared focal plane array sensor for remote and on-line measurements on a macroscopic scale [5]. LIPS has been applied to polymer samples in order to investigate the possibility of using this method for the identification of different materials [6–8]. For some cases, LIPS can be used to complement NIR spectroscopy which can also be applied for the identification of polymer, as mentioned previously. However, it is not suitable for dark-coloured samples. Some studies have investigated different effects during laser polymer ablation: co-occurrence of photochemical and thermal effects using 248-nm excimer laser [9] modification of surfaces after excimer laser treatment [10] or characteristics of the plume generated [11]. Laser-induced plasma using a compact Nd:YAG laser has also been used for recycled plastic materials identification [12]. This method has been developed for instant reliable classification (90–99%) of different groups of plastic materials by means of statistical correlation analysis. Although a limitation exists for identification because of the loss of molecular information in the plasma, the technique has excellent potential for online, real-time analysis of recycled materials, which is really of interest in order to obtain plastics separation faster and more effective. Nd:YAG laser has been used for other applications due to its simplicity, easy operation, high efficiency, low cost and suitability. Despite all works and publications on LIPS that have appeared in recent years, the laser plasma can offer new advantages for plastics identification and separation in accordance with new exigencies of polymer industry and science. In previous papers [13] we have shown that simple statistical correlation methods, such as linear and rank correlations, can be successfully applied for
identification of solid and particulate materials. A compact LIP spectrometer was used for instant identification of solids. Spectra were collected with a compact dual channel fibre optic spectrometer and monitored either in a 230–310 nm or a 200–800 nm spectral window. Parametric (linear) and nonparametric (rank) correlation methods were applied for identification of steel and cast iron samples which had very similar composition. A nearly 100% reliable identification was achieved. In the other work, identification of particulate materials, such as iron ores and iron oxides, also yielded nearly 100% accuracy. In this paper, we demonstrate the application of parametric (linear) and non-parametric (rank) correlations for identification of various plastics. The goal of this work is to use LIPS, in which plasma is made by means of a Nd:YAG laser, to obtain household plastics spectra in order to identify them such a simple, fast, low cost and effective method. Their success is based on the use of thousands of data points (pixels) representing the sample spectrum in a relatively large spectral window.
2. Experimental 2.1. Samples used The samples were plastic materials used for Spanish food containers, they were known a priori from recycling marks on the containers. Table 1 shows the analysed samples, colour, trademark and the type of polymer they belong to.
Table 1 Recycled plastic samples Library samples Polyethylene terephthalate (PET) High-density polyethylene (HDPE) Low-density polyethylene (LDPE) Polypropylene (PP) Polystyrene (PS) Identification samples PET-1: Water plastic bottle, blue HDPE-1: Yoghourt container, white LDPE-1: Bread container, blue and white PP-1: Chocolate mousse container, white PS-1: Rice and milk container, white
ARTICLE IN PRESS J. Anzano et al. / Polymer Testing 25 (2006) 623–627
2.2. Sample preparation
625
DAQCard—700 interface (National Instruments, USA).
Little sample preparation was necessary. The result is increased throughput, greater convenience and fewer opportunities for contamination to occur. The food containers were cut into small pieces (approximately 3 3 cm) and then they were placed on a double-sided tape stuck to a glass slide. The piece of plastic must be completely stuck to the slide in order to avoid air between them. In some cases this was not possible so it also required one-sided tape stuck to the extremes of the plastic. Five randomly chosen plastics, belonging to five different types, were used to construct a library, whereas other samples were used as subjects for identification. 2.3. Instrumentation and instrumental parameters The equipment used (Fig. 1) consisted of a Nd:YAG laser (Quantel, model Ultra CFR). The laser and the spectrometer are synchronized by a trigger pulse from a home-made compact pulse generator. The radiation from the laser spark is collected with a bifurcated optical fibre connected to a dual-channel Ocean Optics mini spectrometer (SD2000, Ocean Optics, Inc., Dunedin, FL, USA). The spectrometer has the following characteristics: channel one (slave), 230–310 spectral range; and channel two (master), 200–850 spectral range. The spectrometer is driven from a laptop computer (hp invent, Omnibook XE3) via a
2.4. LIPS libraries Three LIPS libraries were compiled for identification of the six recycled plastic materials: PET, HDPE, LDPE, PP and PS. The library spectra were obtained by inducing the laser spark on 10 random surface spots and averaging the resulting 10 emission spectra. All libraries were stored in a computer and used on a day-to-day basis without being renewed. A program for correlation analysis was developed using Visual Basic 6.0 and the LabView drivers supplied with the Ocean Optics spectrometer. The computer calculates all mutual correlation coefficients between the current spectrum and all library spectra [11]. 3. Results and discussion 3.1. Instrumental parameters The most important instrumental parameters studied were the position of the optical fibre, the optimum energy, the slow wasting of the plastic and the homogeneity of the sample. Before starting we used one of the samples to optimise the response of the optical fibre. It consisted of moving the fibre until the moment at
Fig. 1. Instrumentation set up
ARTICLE IN PRESS J. Anzano et al. / Polymer Testing 25 (2006) 623–627
626
which we obtained the solid angle and the spectrum showed in the computer was the best one. The optimum energy of the laser pulse was studied in some samples. Different energy laser pulses (the energy ranged between 1 and 10) were used and, after that, the 10 spectra were compared. The best spectrum (with the most resolved and high peaks) belonged to the optimum energy which was 7 in most of the cases. The homogeneity of the sample was studied by shooting at different points of the sample. The spectra we obtained were very similar so
the conclusion was that the sample was homogeneous. 3.2. Characterization of plastic containers of food Molecular materials like plastics are almost entirely atomized when exposed to intense laser radiation sufficient for breakdown. This implies that limitations exist in application of LIPS for identification of polymers because of the loss of molecular information in the plasma. However, as will be shown below, the large amount of spectroscopic
500
600
LDPE
HDPE 500
PP
500
400 400
Intensity (counts)
400 300 300 300 200 200
200 100
100
100
0
0 100 200 300 400 500 600 700 800 900
0
100 200 300 400 500 600 700 800 900
Wavelength (nm)
Wavelength (nm)
100 200 300 400 500 600 700 800 900
Wavelength (nm)
600
600 550
PS
PET 500
500 450
400
Intensity (counts)
400 350
300
300 250
200
200 150
100
100 50
0
0 -50 100 200 300 400 500 600 700 800 900
Wavelength (nm)
100 200 300 400 500 600 700 800 900
Wavelength (nm)
Fig. 2. Spectra from high-density polyethylene (HDPE), low-density polyethylene (LDPE), polypropylene (PP) polystyrene (PS) and polyethylene terephthalate (PET).
ARTICLE IN PRESS J. Anzano et al. / Polymer Testing 25 (2006) 623–627
data (2048 pixels-points), used all at once in the correlation procedure, allows original information about the sample nature to be obtained. The correlation methodology was first applied to ‘‘library’’ plastics. Ten shot-averaged spectra from these samples are shown in Fig. 2. The most prominent feature in all the spectra is an unresolved group of N II lines near 500 nm due to atmospheric nitrogen. A group of O II lines also appear in the region 350–450 nm and the O I triplet at 777.2–777.5 nm is also visible. Other features include a strong carbon line at 247.86 nm and the H line at 656.28 nm. Each emission spectrum consists of 2048 points (pixels); therefore enough statistical material is available to permit the use of simple correlation methods like linear correlation and non-parametric rank correlation. Besides the apparent differences in correlation coefficients, strict statistical criteria must be used in order to quantify the level of significance of these differences. To do this, we applied a simple Student’s t-test. The values for the Student’s t were calculated differently depending on whether the two distributions had the same or different variances. To check this, an F-test was applied (F denoting the ratio of the variances). If the calculated significance of F did not exceed 0.1, the difference in variances was considered as significant and t was calculated in a slightly different way than in the case where the distributions had the same variances. On the basis of these t-values, the probabilities that two distributions of correlation coefficients had different means were calculated. The results of these calculations are shown in Table 2. The diagonal elements in Table 2 correspond to the correlation of the sample with itself, all exhibiting a zero probability of difference. All the probabilities given in the table as unity differ from unity by negligibly small Table 2 Calculated probabilities that differences plastics reference samples for the library were detected using 10 shot averaged library spectra Corr. type Linear correlation (rank correlation) Sample
PET
HDPE
LDPE
PET-1 HDPE-1 LDPE-1 PP-1 PS-1
0 1 1 1 1
1 0 1 1 1
1 (1) 1 (1) 0.9987 (1) 0.9934 (0.9987) 0 (0) 0.9943 (0.9994) 1 (1) 0 (0) 1 (1) 0.9965 (0.9979)
(0) (0.9992) (1) (1) (1)
(1) (0) (1) (0.9878) (1)
PP
PS 1 1 1 1 0
(1) (1) (1) (1) (0)
627
numbers, less than 10 8. As seen from Table 2, both correlations show very high (499%) probabilities of correct identification, for both the linear and rank correlation. 4. Summary A compact laser-induced plasma spectrometer has been developed for instant reliable classification of different groups of plastic materials by using statistical correlation analysis. A software package was developed combining both data acquisition and data processing functions. Linear and non-parametric (rank) correlations were applied for classification of spectral data with approximately the same results. The robustness of the technique was demonstrated by the 90–99% reliable identification of almost all analysed plastics. The technique has excellent potential for on-line, real-time analysis of recycling materials. Acknowledgment This work was supported by Spanish Environmental Government 2.7-241/2005/ 2-B. References [1] http://www.pharmaportal.com.ar/tem-packaging-02.htm. [2] V. Allen, J.H. Kalivas, R.G. Rodrı´ guez, Appl. Spectrosc. 53 (6) (1999) 672. [3] K. Inada, R. Matsuda, C. Fujiwara, M. Nomura, T. Tamon, I. Nishihara, T. Takao, T. Fujita, Resour. Conserv. Recycling 33 (2001) 131. [4] A. Murase, N. Sato, Appl. Spectrosc. 53 (6) (1999) 745. [5] W.H.A.M. Van den Broek, D. Wienke, W.J. Melssen, R. Feldhoff, T. Huth-Fehre, T. Kantimm, L.M.C. Buydens, Appl. Spectrosc. 51 (6) (1997) 856. [6] D.R. Anderson, C.W. McLeod, T.A. Smith, J. Anal. At. Spectrom. 9 (2) (1994) 67. [7] H. Fink, U. Panne, R. Niessner, Anal. Chim. Acta 440 (1) (2001) 17. [8] H. Fink, U. Panne, R. Niessner, Anal. Chem. 74 (17) (2002) 4334. [9] Y. Feng, Z.Q. Liu, X.-S. Yi, Appl. Surf. Sci. 156 (2000) 177. [10] P. Laurens, M.O. Bouali, F. Meducin, B. Sadras, Appl. Surf. Sci. 154 (2000) 211. [11] D.K.Y. Low, M.J.J. Schmidt, L. Li, Appl. Surf. Sci. 168 (2000) 170. [12] R. Sattmann, I. Mo¨nch, H. Krause, R. Noll, S. Couris, A. Hatziapostolou, A. Mavromanolakis, C. Fotakis, E. Larrauri, R. Miguel, Appl. Spectrosc. 52 (3) (1998) 456. [13] I.B. Gornushkin, A. Ruiz-Medina, J.M. Anzano, B.W. Smith, J.D. Winefordner, J. Anal. At. Spectrom. 15 (2000) 581.