POLYMERTESTING

Polymer Testing 25 (2006) 623–627

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Analysis Method

Rapid characterization of plastics using laser-inducedplasma spectroscopy (LIPS)

Jesus Anzano�, Marıa-Esther Casanova, Marıa-Soledad Bermudez,Roberto-Jesus 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 ourlife. To provide against contamination and conservethem, food products are distributed in differentplastic packages: bags, bottles, boxes, etc that

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ss: janzano@unizar.es (J. Anzano).

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contain all kinds of edible products: liquid (water,milk, cold beveragesy) or solid (fruit, meat, fish,frozen foods, etc.). The group of commercialplastics, also termed commodity plastics, consistsof the most used polymers in terms of volume andnumber of applications. They are mainly polystyr-ene (PS), polypropylene (PP), high- and low-densitypolyethylene (HDPE, LDPE), polyethylene ter-ephthalate (PET) and, in lower proportion, poly-carbonate (PC). [1]

Raman spectroscopy has also been evaluated fordiscrimination between plastics. Raman spectra

.

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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

J. Anzano et al. / Polymer Testing 25 (2006) 623–627624

have an abundance of sharp, well-resolved bandsand provide structural fingerprint information thatcan be investigated for uniquely identifying plastics.It is demonstrated the potential of Raman spectro-scopy for computerized classification of commonpost-consumer plastics. Moreover, it is able todiscriminate between HDPE and LDPE.[2]

Infrared spectroscopy is one of the most im-portant techniques to identify plastics and has beensubject to great development. For example, theidentification of plastics by infrared absorptionusing InGaAsP laser diode [3], or the combinationof IR spectroscopy and a flexible pyrolysis probe forrapid identification of plastics [4], and the applica-tion of a spectroscopic infrared focal plane arraysensor for remote and on-line measurements on amacroscopic scale [5].

LIPS has been applied to polymer samples inorder to investigate the possibility of using thismethod for the identification of different materials[6–8]. For some cases, LIPS can be used tocomplement NIR spectroscopy which can also beapplied for the identification of polymer, as men-tioned previously. However, it is not suitable fordark-coloured samples. Some studies have investi-gated different effects during laser polymer abla-tion: co-occurrence of photochemical and thermaleffects using 248-nm excimer laser [9] modificationof surfaces after excimer laser treatment [10] orcharacteristics of the plume generated [11].

Laser-induced plasma using a compact Nd:YAGlaser has also been used for recycled plasticmaterials identification [12]. This method has beendeveloped for instant reliable classification(90–99%) of different groups of plastic materialsby means of statistical correlation analysis.Although a limitation exists for identificationbecause of the loss of molecular information in theplasma, the technique has excellent potential for on-line, real-time analysis of recycled materials, whichis really of interest in order to obtain plasticsseparation faster and more effective. Nd:YAG laserhas been used for other applications due to itssimplicity, easy operation, high efficiency, low costand suitability. Despite all works and publicationson LIPS that have appeared in recent years, thelaser plasma can offer new advantages for plasticsidentification and separation in accordance withnew exigencies of polymer industry and science.

In previous papers [13] we have shown that simplestatistical correlation methods, such as linear andrank correlations, can be successfully applied for

identification of solid and particulate materials. Acompact LIP spectrometer was used for instantidentification of solids. Spectra were collected with acompact dual channel fibre optic spectrometer andmonitored either in a 230–310 nm or a 200–800 nmspectral window. Parametric (linear) and non-parametric (rank) correlation methods were appliedfor identification of steel and cast iron sampleswhich had very similar composition. A nearly 100%reliable identification was achieved. In the otherwork, identification of particulate materials, such asiron ores and iron oxides, also yielded nearly 100%accuracy.

In this paper, we demonstrate the application ofparametric (linear) and non-parametric (rank)correlations for identification of various plastics.The goal of this work is to use LIPS, in whichplasma is made by means of a Nd:YAG laser, toobtain household plastics spectra in order toidentify them such a simple, fast, low cost andeffective method. Their success is based on the useof thousands of data points (pixels) representing thesample spectrum in a relatively large spectralwindow.

2. Experimental

2.1. Samples used

The samples were plastic materials used forSpanish food containers, they were known a priorifrom recycling marks on the containers. Table 1shows the analysed samples, colour, trademark andthe type of polymer they belong to.

ARTICLE IN PRESSJ. Anzano et al. / Polymer Testing 25 (2006) 623–627 625

2.2. Sample preparation

Little sample preparation was necessary. Theresult is increased throughput, greater convenienceand fewer opportunities for contamination to occur.

The food containers were cut into small pieces(approximately 3� 3 cm) and then they were placedon a double-sided tape stuck to a glass slide. Thepiece of plastic must be completely stuck to the slidein order to avoid air between them. In some casesthis was not possible so it also required one-sidedtape stuck to the extremes of the plastic.Five randomly chosen plastics, belonging to fivedifferent types, were used to construct a library,whereas other samples were used as subjects foridentification.

2.3. Instrumentation and instrumental parameters

The equipment used (Fig. 1) consisted of aNd:YAG laser (Quantel, model Ultra CFR). Thelaser and the spectrometer are synchronized by atrigger pulse from a home-made compact pulsegenerator. The radiation from the laser spark iscollected with a bifurcated optical fibre connected toa 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; andchannel two (master), 200–850 spectral range.

The spectrometer is driven from a laptopcomputer (hp invent, Omnibook XE3) via a

Fig. 1. Instrument

DAQCard—700 interface (National Instruments,USA).

2.4. LIPS libraries

Three LIPS libraries were compiled for identifica-tion of the six recycled plastic materials: PET,HDPE, LDPE, PP and PS. The library spectra wereobtained by inducing the laser spark on 10 randomsurface spots and averaging the resulting 10 emis-sion spectra. All libraries were stored in a computerand used on a day-to-day basis without beingrenewed.

A program for correlation analysis was developedusing Visual Basic 6.0 and the LabView driverssupplied with the Ocean Optics spectrometer. Thecomputer calculates all mutual correlation coeffi-cients between the current spectrum and all libraryspectra [11].

3. Results and discussion

3.1. Instrumental parameters

The most important instrumental parametersstudied were the position of the optical fibre, theoptimum energy, the slow wasting of the plastic andthe homogeneity of the sample.

Before starting we used one of the samples tooptimise the response of the optical fibre. Itconsisted of moving the fibre until the moment at

ation set up

ARTICLE IN PRESSJ. Anzano et al. / Polymer Testing 25 (2006) 623–627626

which we obtained the solid angle and the spectrumshowed in the computer was the best one.

The optimum energy of the laser pulse wasstudied in some samples. Different energy laserpulses (the energy ranged between 1 and 10) wereused and, after that, the 10 spectra were compared.The best spectrum (with the most resolved and highpeaks) belonged to the optimum energy which was 7in most of the cases.

The homogeneity of the sample was studiedby shooting at different points of the sample.The spectra we obtained were very similar so

100 200 300 400 500 600 700 800 900

0

100

200

300

400

500

600

HDPE

Inte

nsity

(co

unts

)

Wavelength (nm)100 200 300 400 5

0

100

200

300

400

500

Wavele

100 200 300 400 500 600 700 800 900-50

0

50

100

150

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600

Wavelength (nm)

PS

Inte

nsity

(co

unts

)

100 200 300 400 5

0

100

200

300

400

500

600

Wavele

Fig. 2. Spectra from high-density polyethylene (HDPE), low-density

polyethylene terephthalate (PET).

the conclusion was that the sample was homo-geneous.

3.2. Characterization of plastic containers of food

Molecular materials like plastics are almostentirely atomized when exposed to intense laserradiation sufficient for breakdown. This implies thatlimitations exist in application of LIPS for identi-fication of polymers because of the loss of molecularinformation in the plasma. However, as will beshown below, the large amount of spectroscopic

00 600 700 800 900

ngth (nm)

LDPE

100 200 300 400 500 600 700 800 900

0

100

200

300

400

500

Wavelength (nm)

PP

00 600 700 800 900

PET

ngth (nm)

polyethylene (LDPE), polypropylene (PP) polystyrene (PS) and

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data (2048 pixels-points), used all at once in thecorrelation procedure, allows original informationabout the sample nature to be obtained. Thecorrelation methodology was first applied to ‘‘li-brary’’ plastics. Ten shot-averaged spectra fromthese samples are shown in Fig. 2. The mostprominent feature in all the spectra is an unresolvedgroup of N II lines near 500 nm due to atmosphericnitrogen. A group of O II lines also appear in theregion 350–450 nm and the O I triplet at777.2–777.5 nm is also visible. Other featuresinclude a strong carbon line at 247.86 nm and theH line at 656.28 nm.

Each emission spectrum consists of 2048 points(pixels); therefore enough statistical material isavailable to permit the use of simple correlationmethods like linear correlation and non-parametricrank correlation.

Besides the apparent differences in correlationcoefficients, strict statistical criteria must be used inorder to quantify the level of significance of thesedifferences. To do this, we applied a simpleStudent’s t-test. The values for the Student’s t werecalculated differently depending on whether the twodistributions had the same or different variances. Tocheck this, an F-test was applied (F denoting theratio of the variances). If the calculated significanceof F did not exceed 0.1, the difference in varianceswas considered as significant and t was calculated ina slightly different way than in the case where thedistributions had the same variances. On the basisof these t-values, the probabilities that two distribu-tions of correlation coefficients had different meanswere calculated. The results of these calculationsare shown in Table 2. The diagonal elements inTable 2 correspond to the correlation of the samplewith itself, all exhibiting a zero probability ofdifference. All the probabilities given in the tableas unity differ from unity by negligibly small

Table 2

Calculated probabilities that differences plastics reference sam-

ples for the library were detected using 10 shot averaged library

spectra

Corr. type Linear correlation (rank correlation)

Sample PET HDPE LDPE PP PS

PET-1 0 (0) 1 (1) 1 (1) 1 (1) 1 (1)

HDPE-1 1 (0.9992) 0 (0) 0.9987 (1) 0.9934 (0.9987) 1 (1)

LDPE-1 1 (1) 1 (1) 0 (0) 0.9943 (0.9994) 1 (1)

PP-1 1 (1) 1 (0.9878) 1 (1) 0 (0) 1 (1)

PS-1 1 (1) 1 (1) 1 (1) 0.9965 (0.9979) 0 (0)

numbers, less than 10�8. As seen from Table 2,both correlations show very high (499%) prob-abilities of correct identification, for both the linearand rank correlation.

4. Summary

A compact laser-induced plasma spectrometerhas been developed for instant reliable classificationof different groups of plastic materials by usingstatistical correlation analysis. A software packagewas developed combining both data acquisition anddata processing functions. Linear and non-para-metric (rank) correlations were applied for classifi-cation of spectral data with approximately the sameresults. The robustness of the technique wasdemonstrated by the 90–99% reliable identificationof almost all analysed plastics. The technique hasexcellent potential for on-line, real-time analysis ofrecycling materials.

Acknowledgment

This work was supported by Spanish Environ-mental Government 2.7-241/2005/ 2-B.

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