On-line size exclusion chromatography–pyrolysis-gas chromatography–mass spectrometry for copolymer characterization and additive analysis

Journal of Chromatography A, 1143 (2007) 182–189

On-line size exclusion chromatography–pyrolysis-gas chromatography–mass spectrometry for copolymer characterization and additive analysis Erwin R. Kaal a,b,∗ , Geert Alkema b , Mitsuhiro Kurano b , Margit Geissler c , Hans-Gerd Janssen a,d a

Polymer-Analysis Group, van’t Hoff Institute for Molecular Sciences, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, the Netherlands b ATAS GL International, P.O. Box 17, 5500 AA Veldhoven, the Netherlands c Shimadzu Europe, Albert-Hahn-Strasse 6-10, 47269 Duisburg, Germany d Unilever Research and Development, Advanced Measurement and Imaging, P.O. Box 114, 3130 AC Vlaardingen, the Netherlands Received 23 October 2006; received in revised form 15 December 2006; accepted 19 December 2006 Available online 21 December 2006

Abstract On-line coupled size exclusion chromatography–pyrolysis gas chromatography mass spectrometry (SEC–Py-GC–MS) is studied as a novel tool for the characterization of complex polymer samples. An automated system for on-line SEC–Py-GC–MS allowing transfer of multiple fractions was developed based on stop-flow operation of the SEC dimension, syringe-based transfer of the SEC fraction to the GC instrument and solvent elimination with subsequent pyrolysis in a programmed temperature vaporization (PTV) injector. After optimization the system was applied to the characterization of a complex terpolymer composed of very similar monomers. The use of the system for combined pyrolysis and additive analyses in polycarbonate was also demonstrated. Results obtained with the new method indicate the interesting potentials of the method for detailed characterization of polymeric materials. © 2006 Elsevier B.V. All rights reserved. Keywords: Online SEC–pyrolysis-GC–MS; Hyphenation; Copolymer characterization; Polymer additives

1. Introduction Polymeric commodities and specialty products are widely used in modern life. Virtually all of these products are complex mixtures where compositions of both the actual polymers, as well as of the additives have been carefully fine-tuned to obtain the desired properties. Detailed information on the levels of the additives and the chemical structure and molecular weight of the polymer is crucial for understanding and improving the properties of a product. It is for this reason that the development of analytical tools for such analyses has received a great deal of attention.

∗ Corresponding author at: Polymer-Analysis Group, van’t Hoff Institute for Molecular Sciences, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, the Netherlands. Tel.: +31 40 254 9531; fax: +31 40 254 9779. E-mail address: [email protected] (E.R. Kaal).

0021-9673/$ – see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.chroma.2006.12.054

The most important compositional parameters of polymeric materials are the composition of the polymer phase on the one hand and of the additive package on the other. Even for the simplest polymeric systems a full characterization is not trivial. Several distributions will generally be present in the polymer, i.e. distributions of chain length, degree of branching, end-groups, etc. For mixtures of homopolymers or for copolymers this is even more complex. Particularly difficult, but at the same time also highly relevant, is the determination of copolymer composition as a function of molecular weight (MW). To obtain this information, a combination of a size separation and a method for obtaining chemical composition (CC) information is needed [1]. This can most elegantly be realised by combining SEC and LC. Especially comprehensively coupled SEC and LC is a very powerful tool for the determination of the CC and its distribution as a function of molecular weight [2–5]. Despite significant progress in this area however, the practical use of SEC × LC or LC × SEC is still highly demanding.

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Hyphenation of SEC to spectroscopic detectors is widely used to obtain CC versus MW information [1]. Although it does not provide composition-distribution information as comprehensive LC × LC methods do, hyphenated SEC is a valuable tool in e.g. composition-drift studies. A wide range of spectroscopic detectors has been hyphenated to SEC. These include UV, IR, MS and NMR. The easiest combination is SEC–UV. Unfortunately, UV spectra are not really specific making UV detection only suited for characterization of copolymers containing monomers with very specific absorption bands. SEC–IR and SEC–NMR in this respect are more powerful because they provide much more detailed spectra [6–10]. However, also these methods suffer from a number of disadvantages; for example in case of NMR, the high price of the equipment, the stringent solvent requirements and the limited sensitivity and dynamic range. The main disadvantage of IR is still the difficulty for obtaining truly quantitative information [11,12]. For a limited number of applications, especially if low MW copolymers are concerned, also mass spectrometry can yield compositional information [8,13–16]. Montaudo [8] for example applied MALDI (and SEC) for the quantitative characterization of polybutylacrylate (PBA) and polymethylmethacrylate (PMMA) copolymers. Unfortunately, this technique cannot give detailed information for copolymers with MWs above approximately 50,000 Da because of mass-resolution limitations [16]. Py-GC can be an attractive alternative for spectroscopic detection after SEC. As a stand-alone method Py-GC has been applied for copolymer characterization by various authors [17–22]. As an example, Wang et al. [17] used Py-GC-FID for the structure elucidation of styrene/methyl methacrylate copolymers. So far Py-GC–MS has not really been used as a compositional detector after SEC. This is mainly because of difficulties in automation and the time consuming nature of the experiments. A problem in automation is the solvent elimination step that is required if dissolved polymers are studied. Due to the limited size of conventional pyrolysers, only (sub) microliter sample quantities can be accommodated, making it impossible to perform solvent elimination of large volumes and pyrolysis in one device. This renders automation difficult. Using a so-called programmed temperature vaporization (PTV) injector it would be possible to perform solvent elimination of large volumes and the subsequent pyrolysis of the remaining high molecular weight material in one instrument. In GC, the PTV injector has been widely used for large volume injections [23,24]. It has also been shown to be a flexible device for thermal desorption and pyrolysis GC [25]. The versatile nature of the PTV injector finally was also exploited by de Koning et al. who applied it as an interface in comprehensive LC × GC [26]. In that work the LC was operated in the stop-flow mode and subsequent fractions of the LC effluent were transferred to the PTV-injector for solvent elimination and fast GC-analysis. By incorporating a pyrolysis step after the solvent elimination, a similar system can also be used for comprehensive SEC × Py-GC. By varying the PTV operational settings during the SEC analysis, a comprehensive compositional characterization of the copolymer and a detailed additive analysis can be performed in one SEC run.

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In this article we will describe the development of a novel system for automated online SEC–Py-GC–MS based on a PTVinjector as the interface. The entire SEC chromatogram is fractionated into multiple fractions for subsequent Py-GC characterization. Fast GC separation is used in the second dimension to reduce the total time required for the full characterization of the polymeric sample. The conditions for solvent elimination and pyrolysis are optimized and fast GC–MS settings for identification and quantification of the pyrolysis fragments and additives are determined. Also the effect of the use of stop-flow operation in SEC on the band width of the eluting polymers is evaluated. The system is applied for the compositional characterization of several (co)polymers, as well as for the identification and quantification of polymer additives. 2. Experimental 2.1. Samples and materials Narrow dispersity PS and PMMA standards and poly(styrene-co-methyl methacrylate) copolymers with different styrene contents and MWs were obtained from PSS (Mainz, Germany). Three different terpolymers consisting of the monomers MMA, butylacrylate (BA) and caprolacton (CL) were prepared at the University of Eindhoven (Eindhoven, the Netherlands). The preparation of these terpolymers is described in detail by van Hulst et al. [27]. Poly(bisphenol A)carbonate and the additives octadecyl-3,5-di-tert-butyl-4-hydoxy-hydrocinnamate (Irganox 1076) and 1,3,5-tris(3,5-di-tert-butyl-4-hydroxybenzyl)1,3,5triazine-2,4,6(1H,3H,5H)-trione (Irganox 3114) were purchased from Ciba (Basle, Switzerland). All polymers and additives were dissolved in THF (Biosolve, Valkenswaard, the Netherlands) prior to analysis. 2.2. SEC analysis The SEC system consisted of a Shimadzu Prominence LC pump LC-20AD (Den Bosch, the Netherlands) and a Spectrasystem UV detector (Thermo electron corporation, Basingstoke, UK). It was equipped with a Focus XYZ robotic autosampler with a 12 ␮l sample loop (ATAS GL, Veldhoven, the Netherlands), which was used for the introduction of the sample into the SEC as well as for transfer of the SEC fractions to the Py-GC (see below). Two Mixed C (Polymer Labs., Amherts, USA) SEC columns of 7.8 × 300 mm i.d. were used. The mobile phase was THF at a flow rate of 0.5 ml/min. At the exit of the SEC column the effluent was split. Approximately 70% was sent to the UV detector. The remainder was directed to the PTV–SEC–GC interface. 2.3. SEC–GC transfer Automated transfer of the fractions from the SEC to the GC was carried out using an 80 ␮l ‘side port’ syringe (ATAS GL, Veldhoven, the Netherlands) installed in the robotic auto sampler. The side port syringe contains a fluid entrance at the top of the barrel, in that way creating a storage volume of 80 ␮l. To

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allow on-line interfacing, the SEC dimension is operating in the stop-flow mode. In short: the SEC flow is on for a short time, e.g. 15 s. During this time the effluent eluting from the SEC column is collected in the syringe barrel. At the end of the collection interval the SEC–flow is stopped and the sample stored in the syringe is transferred to the PTV-injector at a controlled rate. At the SEC-flow rate, split ratio and fraction time used here fraction volumes were approximately 40 ␮l. The fractions were transferred to the PTV injector at a rate of 54 ␮l/min. Conventional 1 ␮l injections of standards were carried out at a speed of 100 ␮l/s. 2.4. Solvent elimination and pyrolysis Solvent elimination was performed in the PTV injector at a temperature of 100 ◦ C. The additional solvent vent time applied after completion of the transfer of a fraction was 30 s. For pyrolysis, the PTV was programmed from 100 to 550 ◦ C at 30 ◦ C/s. The split flow rate was 150 ml/min during solvent elimination and 10 ml/min during pyrolysis and sample transfer (3 min) with a subsequent increase to 50 ml/min for the remainder of the run. The GC-program was started once the PTV-injector had reached the final pyrolysis temperature. For additive analysis pyrolysis evidently is not necessary. For this part of the SEC run different PTV conditions were applied. After solvent elimination the PTV temperature was programmed to 490 ◦ C at 3 ◦ C/s: the split flow initially was 10 ml/min. After 5 min it was increased to 50 ml/min. 2.5. Gas chromatographic analysis All Py-GC–MS experiments were performed on a Shimadzu GCMS-QP2010 (Shimadzu Cooperation, Japan) equipped with an Optic 3 PTV injector (ATAS GL) containing a fritted liner. GC analyses were carried out on a 30 m × 0.25 mm i.d. TC 5MS (5% phenyl-methylpolysiloxane) column with a film thickness of 0.25 ␮m (GL Sciences, Tokyo, Japan) using helium as carrier gas at a flow rate of 1 ml/min. The temperature program used in the Py-GC–MS characterization of PS, PMMA and their blends started at 150 ◦ C with programming to 320 ◦ C at 100 ◦ C/min. The initial and final holds were 30 s and 1.5 min, respectively. The temperature program for the analysis of the PBA-PMMAPCL terpolymer and for PC analysis started at 70 ◦ C (2 min initial hold). Here the final temperature was 150 ◦ C (2 min) and the programming rate was 100 ◦ C/min. For additive analysis a different oven temperature program was used; 2 min at 70 ◦ C then programmed at 40 ◦ C/min to 325 ◦ C with a 7 min hold. 3. Results and discussion The transport of fractions from the SEC to the GC and the subsequent solvent elimination are the biggest challenges in the development of a system for automated on-line SEC–PyGC–MS. Especially solvent elimination is an issue because conventional SEC columns have rather large inner diameters, typically 7.8 mm, which means that the volumes of the sample fractions are also large. An evident option to reduce the fraction

volume is to use SEC columns with a reduced inner diameter. Although the use of such columns has been demonstrated, their resolution and peak capacity so far is generally poorer than that of standard columns [28]. For this reason we opted for the use of standard 7.8 mm columns with flow splitting. The PTV injector has been used as a solvent elimination interface in on-line LC–GC by several authors [26,29,30]. The principle of on-line PTV LC–GC is fairly simple: the fluid flow coming from the LC enters the liner of the injector via a transfer capillary. The solvent now starts to evaporate and solvent vapors formed are discharged via the split exit. The liner generally is equipped with some type of a packing to accommodate the liquid sample. The injector temperature and split flow have to be optimized to find conditions were the evaporation rate approximately equals the rate of liquid introduction. Once the transfer of the LC fraction is completed, the split flow is reduced and the compounds are transferred to the column by heating the injector. In our case a PTV final temperature is selected that is sufficiently high for rapid pyrolysis of the polymers. Optimization of the conditions for solvent elimination in our case is not very critical since no volatile compounds are involved. A situation that should be avoided, however, is the use of injector conditions that result in the evaporation rate being much lower than the rate of liquid introduction. Under these conditions liquid sample will accumulate in the liner and eventually rinse the injector washing away the sample components via the split exit. To obtain a high evaporation rate, solvent elimination was performed at a high injector temperature; 40 ◦ C above the boiling point of THF at ambient pressure. The split flow applied was 150 ml/min. At these conditions the solvent evaporation rate, and hence the maximum speed of liquid introduction, was found to be approximately 60 ␮l/min. A second issue to consider is the total analysis time of a SEC–Py-GC–MS experiment. To obtain maximum detail, at least a few fractions across a SEC peak should be transferred to the second dimension Py-GC–MS analysis. This can easily result in some 30–60 second-dimensional analyses for every sample. Minimizing the time for the second-dimension separation is therefore crucial. In addition to that, only relevant fractions, i.e. those eluting in the time window between the total exclusion time and the total permeation volume, should be transferred. As regards the GC–MS run, the most time consuming step is the heating and cooling of the oven. Therefore, the use of an isothermal oven temperature is preferable. Unfortunately this was not possible because of traces of the SEC mobile phase remaining in the liner of the injector which than co-eluted with the volatile pyrolysis fragments. By using a GC capable of rapid heating and cooling the GC–MS run time for one fraction could be kept below approximately 5 min. We opted to operate the SEC dimension in the stop-flow mode. The SEC flow was stopped during the solvent elimination, the Py-GC injection, and the GC separation of a fraction. Once the GC run was finished the flow was resumed and the next fraction was stored in the syringe, etc. This process was repeated until the last relevant SEC fraction had been analyzed. Evidently, the repeated stop-flow periods will result in additional band broadening for the polymers. Fortunately, polymers have very low diffusion coefficients meaning

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that band broadening due to longitudinal diffusion will be limited. To confirm that stop-flow operation indeed did not cause excessive band broadening, the peak width of two narrow standards was determined for stop-flow times up to 6 h. The results of these experiments are shown in Fig. 1 and indeed confirm that stop-flow operation had little or no effect on the band width for PS 96,000 Da. For the much smaller 2100 Da standard a small but acceptable effect was seen. To evaluate whether the PTV injector can be used for pyrolysis of PS and PMMA, standards of these materials were pyrolysed at different settings. Fig. 2 shows the Py-GC–MS chromatogram of a mixture of the homopolymers PS and PMMA. Both polymers give rather simple chromatograms where polymer-characteristic peaks can easily be found. At the characteristic mass of m/z 100 for MMA only one peak is seen. For the PS a series of oligomers are formed where the styrene monomer is the most abundant fragment. The on-line SEC–Py-GC–MS system was used to construct typical SEC calibration curves of MW versus elution volume. To construct these curves, mixtures of narrow standards of PS and PMMA were analyzed. In Fig. 3 the peak areas of the monomers formed upon pyrolysis are plotted versus the elution volume to reconstruct the actual SEC chro-

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Fig. 1. Effect of stop-flow time on band broadening for two PS homopolymers. (Column) Two mixed C 7.8 mm × 300 mm i.d. columns; (mobile phase) THF at 1 ml/min at room temperature; (detector) UV at 262 nm; (sample) 10 ␮l of a 1 mg/ml standard solution.

matograms. The peak tops of the reconstructed chromatograms were used to obtain the calibration curve. These are shown in the insert. The correlation coefficients of the curves were 0.9949 and 0.9918 for PMMA and PS, respectively. These results

Fig. 2. Py-GC–MS chromatogram of a mixture of the homopolymers PMMA and PS. Solvent elimination and pyrolysis conditions: injector temperature 100 ◦ C for 30 s then programmed to 550 ◦ C at 30 ◦ C/s; (sample) 50 ␮l of a 10 ␮g/ml standard solution. For other conditions, see Section 2.

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E.R. Kaal et al. / J. Chromatogr. A 1143 (2007) 182–189 Table 1 Comparison of experimental molar ratios of pyrolysis products with manufacturer-specified molar ratios of the monomers

Fig. 3. Reconstructed SEC–Py-GC–MS chromatogram of a mixture of nine narrow homopolymers of PS and PMMA for calibration of the SEC. Solvent elimination and pyrolysis conditions as in Fig. 2, fraction width is 15 s. The insert shows the SEC calibration curves.

demonstrate the reliability of the on-line SEC–Py-GC–MS method. In our work pyrolysis GC–MS is not only used for polymer identification and MW characterization, but also to obtain quantitative compositional information as e.g. monomer ratios. To obtain reliable quantitative information a number of requirements have to be met [17]. Firstly, a quantitative relationship should exist between the intensity of the fragments in the PyGC–MS run and the actual mass of the respective monomers in the SEC fraction prior to pyrolysis. This irrespective of the composition and the molecular weight of the polymer or the concentration of the polymer in the effluent. During SEC analysis all these factors are continuously changing. To study the impact of all these changes a series of model experiments was performed. The influence of molecular weight was evaluated by injecting equal masses of seven narrow standards of PMMA and eight standards of PS in the MW range of 2000 to 2,000,000 Da. The absolute areas obtained for the MMA and styrene fragments in the large volume injection-solvent elimination-pyrolysis experiments of the standards showed a random variation with RSDs of 6 and 7%, for PMMA and PS, respectively. This demonstrates that there is no effect of the MW on the pyrolysis process. A second item studied was the influence of the mass of polymer pyrolysed on the peak areas of the fragments formed. This parameter is relevant because the concentration of the polymer in the SEC effluent will vary continuously during a SEC run. The influence of the sample mass was studied by injecting increasing masses of narrow dispersity standards of PMMA and PS. A good linear relationship was found in the range of 5–100 ng of polymer injected. For PMMA and PS the correlation coefficients found were 0.9980 and 0.9986, respectively. A last factor to consider is the possible influence of the composition of the polymer on the intensities of the pyrolysis products formed. To study this effect the Py-GC–MS peak areas of styrene and MMA were recorded for di-block poly(styrene-co-methyl methacrylate) copolymers of varying (known) composition. Ratios of the monomers were determined using the calibration curves obtained for Py-GC of the separate homopolymers. The results of these experiments are given

MW PS/PMMA copolymer

Manufacturer specifications

Experimental Py-GC–MS ratio

20.500 50.000 65.000 108.000 124.000 184.000 680.000

0.92 0.79 1.02 1.00 1.00 0.94 1.86

0.93 0.81 1.02 0.99 1.01 0.91 1.90

in Table 1. They show an excellent agreement of the experimental Py-GC monomer ratios and the levels specified by the manufacturer. Since our Py-GC system was calibrated using homopolymers this also indicates that, at least for the polymers studied here, peak intensities of pyrolysis products coming from homopolymers or from copolymers are identical. Unfortunately, because of the complexity of the pyrolysis process, this conclusion might not be generally valid and should be verified for all application individually. To demonstrate the potentials of on-line SEC–Py-GC–MS it was applied in the characterization of a tri-block PMMA-PBAPCL terpolymer. In the synthesis of this terpolymer different routes were followed [27]. In the first method, to a PBA homopolymer (activated on one end) MMA was added to give a di-block PMMA-PBA copolymer with PBA on one side and PMMA on the other. Next, PCL was added to obtain the PCLPBA-PMMA terpolymer. In the second protocol, PCL was added to a modified initiator. Next BA was added to form a PCL-PBA copolymer to which finally MMA was added. The third protocol is similar to the second; the only difference is in the first step, now an initiator is added to modified PCL. To enable composition calculations of the terpolymers, concentration calibration curves were prepared for each of the

Fig. 4. Fast GC–MS chromatogram after pyrolysis of a SEC fraction of the PMMA-PBA-PCL terpolymer recorded in the SIM-mode. Fast GC conditions: 70 ◦ C (2 min), 100 ◦ C/min to 150 ◦ C (hold 2 min). All other experimental conditions, see Section 2.

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Table 2 Average chemical composition of the three terpolymers studied Polymer

Reagent, ratio (%)

Protocol 1, ratio (%)

Protocol 2, ratio (%)

Protocol 3, ratio (%)

PMMA PBA PCL

80 13 7

77 16 7

68 25 7

61 31 8

monomers. To this end, mixtures of homopolymer standards were analyzed using Py-GC–MS. Fragments characteristic for the respective monomers were chosen to construct the calibration curves. In all cases the most abundant peak was the monomer itself. To improve the detection limits the MS was operated in the selected ion monitoring (SIM) mode. The m/z values selected were 71, 84 and 100 for BA, CL and MMA respectively. Fig. 4 shows a Py-GC–MS chromatogram of one SEC-fraction of the PCL-PMMA-PBA terpolymer recorded in the SIM mode. Characteristic peaks are seen for each of the monomers. Fast GC was employed here to keep the total analysis time at an acceptable level. The cycle time including cooling and re-equilibration is less than approximately 5 min. Excellent calibration curves of peak area versus mass pyrolysed were obtained having correlation coefficients better than 0.997 for all homopolymers. The first step in the characterization of the terpolymer was the determination of the average chemical composition. This was done by direct injection of the polymer in solution into the solvent elimination Py-GC–MS system. The results of this experiment are summarized in Table 2. As expected, the average chemical compositions of the three terpolymers were only slightly different. The data in Table 2 also show a good agreement between the molar ratio of the monomers at the start of the reaction and the finished products. Fig. 5 shows the results of the SEC–Py-GC–MS analysis of the different terpolymers. The figure was constructed by plotting the concentrations of the three monomer fragments in the fractions versus the fraction number. Large differences were found between the three terpolymers, especially with regard to the distribution of PCL. In case of the terpolymer prepared according to the first protocol clearly no PCL has been attached to the PMMAPBA. The MW distribution of PCL in this ‘terpolymer’ is the same as for the starting PCL homopolymer (data not shown) and at no point in the SEC chromatogram all three monomers are found simultaneously. Interesting to notice are the shifted MW distributions of PMMA and PBA. The different locations of the curves clearly prove that these monomers are not present in the same molecules. The preparation of the terpolymer here clearly failed. In case of the second protocol a small amount of PCL is attached in the lower MW range as is evidenced by the shift towards higher MWs, of the PCL peak. Oppositely, PCL clearly is bound over the entire distribution range in the polymer prepared using the third protocol. In this polymer MMA and BA show identical time profiles. It is hence likely to assume that now a real terpolymer is formed, although in principle it would also be possible that two homopolymers with identical hydrodynamic volumes are present. A more detailed discussion of the terpolymerization reaction is beyond the scope of the present article. Clearly however, the new SEC–Py-GC–MS

method is probably complementary to techniques like SEC–IR and SEC–NMR. The second application studied using our on-line SEC–PyGC–MS system is the characterization of polycarbonate (PC) with simultaneous quantification of two additives, Irganox 1076 and Irganox 3114. Sample preparation methods for additive analysis are generally labour intensive. However they are necessary

Fig. 5. SEC–Py-GC–MS plots of PMMA-PBA-PCL terpolymers prepared according to three different synthesis routes. Fast GC conditions: 70 ◦ C (2 min), 100 ◦ C/min to 150 ◦ C (hold 2 min). All other experimental conditions, see Section 2.

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Fig. 6. Simultaneous polymer characterization and additive analysis using SEC–Py-GC–MS. Sample: polycarbonate (all other experimental conditions see text).

because the additives are usually present at low concentrations in a complex and interfering polymer matrix. In our system the SEC column can be used for additive isolation with direct interfacing to GC–MS analysis. To this end the fraction containing the additives is transferred to the PTV injector for pre-concentration prior to GC–MS identification and quantification. In this way fully automated additive analysis is possible. The results obtained in the combined pyrolysis and additives analysis of the PC sample are shown in Fig. 6. In the pyrolysis part only two pyrolysis fractions were taken. The first fraction was taken in the high molecular weight range, the second in the lower MW range of the SEC peak. As expected no differences were found. The Py-GC–MS chromatogram of the polymer part of the sample shows only one main peak, the monomer bisphenol A. When adapting our method to additive analysis a problem was encountered. In our system we adopted the concept of syringebased LC–GC interfacing as developed by de Koning et al. [26]. An important advantage of the syringe interface is its flexibility, i.e. rapid switching from large volume injection or LC–GC experiments to standard injections is possible. A drawback of the syringe interface is that there is a maximum transfer volume, the volume of the syringe. In the isolation of additives using our 7.8 mm i.d. SEC columns despite the flow splitting the fraction volume of the additive fraction exceeds the storage capacity of the syringe. We considered three options to circumvent this problem. The possibility of continuous effluent transfer through the syringe into the injector with continues solvent elimination was abandoned as it was expected to give unacceptable band broadening as a result of the rather large syringe volume. The second option would be to collect the additives from a few fractions in the PTV injector before actually heating the injec-

tor and starting the GC-run. In this method solvent elimination is performed after the transfer of each fraction. Transfer of the collected additives to the GC is only performed after transfer of the last fraction containing additives. We opted for the third option where the additive peak is sampled as a (limited) number of fractions. Not only is this easier from the programming perspective, it also gives an improved overall resolution as now SEC resolution is not nullified prior to the GC-run. To collect the two additives in a limited number of fractions, the width of the fractions was increased to 25 s once the polymer had eluted. The fraction volume collected is than approximately 70 ␮l and the additives are eluting in three fractions. After solvent elimination the injector was heated at a rate of 5 ◦ C/s instead of 30 ◦ C/s to a final temperature of 490 ◦ C. At these settings the additives and other low molecular weight materials are transferred intact from the injector to the analytical column. To improve the GC separation the programming rate of the oven was reduced to 40 ◦ C/min. The peaks in the GC–MS chromatogram were identified by comparison of the obtained spectra with NIST library spectra. Quantification of the additives was done using calibration curves prepared from standard solutions of the additives in THF. The total amount of an additive present in the polymer was calculated as the sum of the concentrations found in the three fractions. In addition to the additives also several other compounds were found. These included for example the residual monomers bisphenol A and phenol. The levels of the two additives were approximately 50 ␮g/g for both Irganox 1076 and Irganox 3114. The recoveries determined using spiked PC were 102 and 104% for Irganox 1076 and 3114, respectively. These results clearly indicate the feasibility of the current method for combined (co)polymer characterization and additive analysis.

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4. Conclusion The automated online SEC–Py-GC–MS method developed here holds great potential for the two-dimensional characterization of the chemical composition as function of the molecular weight of copolymers. For the polymers studied here the MW and the composition of the (co)polymer have no influence on the pyrolysis products formed. Therefore, quantitative compositional analysis of complex copolymers is possible using homopolymer standards. The method was successfully applied for the characterization of three different PMMA-PBA-PCL terpolymers. The new method showed excellent performance in terms of selectivity, repeatability and reliability. Also demonstrated is the possibility to identify and quantify low MW material such as additives in the same run. The proposed technique can be complimentary to, or in some cases probably even replace, other more complex and expensive hyphenated techniques as e.g. SEC–MALDI, SEC–NMR and SEC–FTIR. Acknowledgements The terpolymers used in this work were prepared by T. leBlanc at the Technical University of Eindhoven. We also thank Rob Edam for support with the SEC analyses and Monique van Hulst for donation of the polymers. References [1] [2] [3] [4]

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