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Determination of accelerators and antioxidants in vulcanized rubber by fourier transform infrared spectrophotometry
ANALYTICA CHIMICA ACTA
ELSEVIER
Analytica
Chimica Acta 353 (1997) 351-358
Determination of accelerators and antioxidants in vulcanized rubber by fourier transform infrared spectrophotometry M. Blanco*, J. Coello, H. Iturriaga, S. Maspoch, E. Bertran Departament de Quhica,
Unitat de Quimica Analitica, Facultat de Citncies, Universitat Authoma de Barcelona, E-08193 Bellaterru, Spain Received
3 March 1997; received in revised form 11 June 1997; accepted
13 June 1997
Abstract During vulcanization, rubber is treated with different substances that have a marked influence on the properties of the end product. Identifying and determining the chemical species responsible for such properties is rendered difficult by the fact that some are incorporated into the vulcanizate or decompose during the process. In this work, we developed a new method for the determination of vulcanization accelerators and antioxidants based on Fourier Transform Infrared spectra of the CC& extracts of vulcanized rubber specimens. Calibration is performed by using Partial Least-Squares Regression (PLSR); the additive concentrations prior to vulcanization are related to the spectra of the fragments or decomposition products extracted from the polymer matrix following vulcanization. The effects of the spectral mode (absorbance or first-derivative) and wavenumber range were assessed by constructing various models to ensure accurate determinations. The proposed method was applied to two vulcanizates obtained by two different procedures; the results were quite satisfactory in both cases. :Q 1997 Elsevier Science B.V. Keywords: Multivariate calibration; Fourier Antioxidants; Vulcanization accelerators
Transform
Infrared
(FT-IR);
Rubber
additives;
Partial
Least-Squares
Regression
(PLSR); _
1. Introduction Rubber is a highly deformable plastic material. For the product to be useful, polymer chains must be linked to form an elastic network. The process that facilitates the transformation of the plastic material into an elastic material, i.e. vulcanization, is carried out at a high temperature and, usually, in the presence of elemental sulphur. Occasionally, the sulphur is replaced by an S-donor (a ‘vulcanizer’) that decomposes at the vulcanization temperature to establish *Corresponding author. Tel.: +34 +34 (3) 581 2477; e-mail: [email protected].
(3)
581
1367;
fax:
0003-2670/97/$17.00 % 1997 Elsevier Science B.V. All rights reserved. PII SOOO3-2670(97)00389-9
bridges consisting of a single sulphur atom between polymer chains. Such bridges are thermally more resistant than the disulphide and polysulphide bridges typically formed in the traditional vulcanization process based on elemental sulphur. The mixture of polymer and vulcanizing agents is supplied with vulcanization accelerators to increase the rate of reaction between both components and to save vulcanizing ingredients, as well as with antioxidants to protect the mixture from potential oxidation reactions. Also reinforcing agents and fillers that usually make the mixture more resistant to tear and abrasion, and plasticizers that facilitate the incorporation of all the additives, are added. The physical
352
M. Blanco et al. /Analytica
Chimica Acta 353 (1997) 351-358
properties of the rubber thus obtained depends on the ingredients and procedure used in its vulcanization. The wide variety of additives used and their low concentrations, the total additive content is typically less than 5% phr (phr stands for ‘parts per hundred rubber’, a concentration unit defined as g of additive added to 100 g of polymer-copolymer), in addition to the transformations they may undergo at the vulcanization temperature, and their role in the process, make their determination rather complex. For these reasons, analysis of this type of sample are more often carried out by using physical tests and identifying and estimating the polymer composition and its reinforcing agents [ 11. Analysing for rubber additives always entails their prior extraction; there are, however, some reported procedures for the direct determination of antioxidants in rubber, which can only be applied under special circumstances (e.g. to freshly aged rubber of known composition containing no carbon black) [2]. Usually, the additives in vulcanized materials can be partly or fully extracted by using an appropriate solvent, Thus, ketone extracts of rubber contain primarily oils and plasticizers, whereas chloroform and alcoholic extracts can contain most accelerators. In any case, the extracts are complex mixtures of the starting materials, vulcanizers, and cleavage products from both, oils accompanying the polymer itself, etc. Extracts can be analysed by using spectrometric techniques. Thus, UV spectrophotometry was used to determine some accelerators and S [3]; plasticizers are usually identified from the infrared spectrum of the residue obtained after the additives are extracted and the solvent evaporated [4]. Chromatographic techniques have also been used in the analysis of extracts, both to identify polymers and additives [5-91, and to quantify some of them [lO,l 11. Major breakthroughs in Fourier Transform Infrared and Near Infrared (FT-IR and NIR) spectrophotometry and the power of chemometric techniques have facilitated the determination of polymer components in mixtures with no prior separation [12-171. However, all applications reported in this respect are concerned with non-vulcanized polymer system, which facilitate quantitative extraction and avoid altering the initial products by the high temperatures involved in the vulcanization process. Recently [18], IT-IR and Partial Least-Squares Regression (PLSR) were used for
the analysis of mixtures of additives supplied to the polymer prior to vulcanizing. In this work, we investigated the determination of some rubber additives present in a vulcanized polymer matrix by solvent extraction and subsequent FT-IR spectrophotometric quantitation, using PLSR calibration. For this purpose, the additive concentrations supplied to the polymer were correlated with the spectra obtained after vulcanization.
2. Experimental
2.1. Apparatus and software All measurements were made on a Perkin-Elmer 1760 FT-IR spectrophotometer using the IRDM software package to acquire and process spectra. PLSR calibration was performed as implemented in the programme Unscrambler v. 3.54, from CAM0 A/S, using spectra exported in JCAMP format. 2.2. Composition of vulcanizates We studied two different vulcanizate formulations. One (vulcanizate I) consisted of 60 : 40 styrene-butadiene polymer to which sulphur was added as vulcanizing agent. The other (vulcanizate II) was composed of 80 : 20 poly-isoprene-butadiene and several Sdonor additives that made up a more complex vulcanizing system. The composition of both formulations is shown in Table 1. Single values are proportions (in phr), which were maintained constant; all other values are the concentration ranges used to prepare the different samples. 2.3. Preparation of samples and recording of extract spectra An appropriate amount of polymer was mixed with the required amounts of vulcanization additives. The additives were incorporated into the polymer in an open cylinder mixer consisting of two parallel, convergent metal rollers rotating at a different rate in opposite directions. The additive mixture was added to the polymer dough as this was passed through the mixer rollers. This operation was repeated until a polymer sheet with additives, as uniformly distributed
M. Blanc0 et al. /Analytica Chimica Acra 353 (1997) 351-358 Table 1 Composition
of additives in the vulcanizates,
353
in parts per hundred rubber (phr) Vulcanizate I Styrene-butadiene
Vulcanizate II Polyisoprene-butadiene
Basic recipes ZnO Stearic acid
5 0.5-3.0
5 0.5-2.5
Reinforcing agents Carbon black 50
50
80
Polymer Additives
(phr)
Accelerators and vulcanizers Copper dimethyldithiocarmamate Sulphur Tetramethylthiuram monosulfide (TMTS) Tetraethylthiuramdisultide (TET) Tetramethylthiuramdisulfide (TMTD) N-cyclohexyl-2-benzothiazole-sulfenamide Antioxidants 1,2-dihydro-2,2,4 Softeners Aromatic
trybutylquinoline
processing
0.11 0.34 1.0-3.5 0.5-2.5 0.5-2.5 0.5-2.5
(CBS)
(TBQ)
0.5-2.5
0.5-4.0
3.0-8.0
oil (AR)
as possible, was obtained. Finally, the rubber sheet was pressed and cut into three squares of approximate dimensions 15 x 15 x0.3 cm. Each sheet was vulcanized separately at 165°C for 5 min. Only the last sheet was used as sample in order to avoid contamination and to ensure reproducibility of the vulcanization conditions. The vulcanized sheets were cut into pieces of 0.5 cm*. About 5 g of vulcanized material was treated with 75 ml of Ccl4 in a Soxhlet apparatus for 6-8 h. The extract thus obtained was concentrated to 5 ml with the aid of an IR beam lamp. The spectra for the Ccl4 extract from each mixture was recorded in a liquid cuvette with NaCl windows and a light path of 150 pm. Spectra were recorded at 4cm-’ intervals over the wavenumber range 4000500 cm-‘. Overall 50 scans per extract were performed. Spectral recordings were converted into absorbance measurements, none of which exceeded 1.6 absorbance units. The solvent spectrum was recorded under the same conditions and subtracted from those for the extracts. First-derivative spectra were obtained from absorbance spectra by using the Savitzky-Golay algorithm [ 191.
O3 r7
20001800
;,
1500
I
1400
1300
WAVENUMBER
1200
1100
1000
900
(cm-‘)
Fig. 1. Absorbance spectrum for the CC14 extract of a sample of: Vulcanizate I (Additive contents in phr: stearic acid 2.3; (-) TBQ 2.7; TMTS 3.0). (- - - -) Vulcanizate II (Additive contents in phr: stearic acid 0.5; CBS 0.5; TMTD 2.5; TET 1.8; TBQ 2.5: AR 8.0.
Fig. 1 shows the spectra for the extract from a mixture of each of the two vulcanizates studied. 3. Results and discussion The chemical transformations undergone by the different additives involved in the vulcanization pro-
354
hf. Blanc0 et al. /Analytica
cess lead to extracts containing also products resulting from their decomposition; it is therefore impossible to select an optimum zone for quantitation from the individual spectra for the additives prior to vulcanization. We studied different spectral ranges that were chosen so as to include the more significant bands in the absorption spectra for the extract of each formulation. As a rule, we discarded those spectral zones where absorption was negligible so as to avoid introducing variables with a very low signal-to-noise ratio in the calibration, which might detract from precision. We also excluded the range from 4000 to 1800 cm-’ owing to its poor distinguishing power (absorption in this range was mostly due to C-H stretching, which is very strong and exhibited by most rubber additives). The range from 1650-1500 cm-’ was also avoided owing to the high noise in the CC14 absorption (even if the solvent spectrum was subtracted). The calibration technique used with all the additives was PLSR [20,21]. Each additive was calibrated by using an individual model. We employed both absorbance and first-derivative spectra that were always autoscaled. The models were internally validated by cross-validation, using the leave-one-out method [22]. The number of PLS components to be used in each case was determined by applying Thomas and Haaland’s criterion to the residual variance obtained in the cross-validation [23]. The results obtained with the different models were compared via the relative standard error of prediction (%RSEP) [24], defined as
where m is the total number of samples, Ci the calculated concentration in sample i and Ci the theoretical concentration of additive introduced prior to vulcanization. 3.1. Vulcanizate I A set of 23 samples containing variable amounts of three additives (stearic acid, TBQ and TMTS) was prepared. Twelve of the samples were used as the calibration set and the other eleven as the validation set. Calibration samples were chosen in such a way that they spanned the entire additive concentration range.
Chimica Acta 353 (1997) 351-358
Most of the steak acid was converted into stearate [25], so if it was extracted its absorption band in the extract would be interfered by CC& absorption. Also, most of it accumulated at the rubber sheet surface in the form of a thin white film that was partly removed in handling the vulcanized sheet. This precluded correlating the amount of steak acid initially added to the sample with the information contained in the spectrum for the extract, so only the additives TBQ and TMTS were quantified. Different wavenumber ranges were studied in order to select the most appropriate range for constructing an effective calibration model. As can be seen in absorption bands were only Fig. 1, significant observed in the region from 1.500 to 900 cm-‘; also, three bands appeared below 1300 cm-’ that were used to establish the suitable spectral ranges, viz. 1500900, 1500-l 100 and 1500-1200 cm-‘. The polymer and its additives (surfactants, oils, etc.) were also extracted into CCL and absorbed in the region 1500-1400 cm-‘, so the above models were assayed from 1400 cm-‘, as well. The results predicted for TMS and TBQ (as %RSEP) from the different wavenumber ranges studied in the absorbance and first-derivative spectral modes are given in Table 2. As a rule, %RSEP values were smaller for first-derivative spectra than for absorbance spectra. The use of first-derivative spectra led to more simple models (i.e. with fewer PLS components required to construct them) in the determination of TBQ; also, %RSEP values increased as the wavenumber range was shortened. The model obtained by using the first derivative spectra over the range 1500900 cm-’ was chosen as optimal because it gave rise to %RSEP values virtually identical with those of the absorbance model over the range 1400-900 cm-’ and required two PLS components only. The spectral model and wavenumber range were found to influence the determination of TMTS similarly to that of TBQ. Differences in % RSEP among the different wavenumber ranges studied were not too large in the first-derivative spectral mode; also, the lowest % RSEP values were obtained in the region 1500-900 cm-‘, which can be ascribed to better resolution of overlapped bands and a decreased baseline shift by effect of extract turbidity.
355
M. Blanco et al. /Analytica Chimica Acta 353 (1997) 351-358 Table 2 %RSEP values for the calibration Range (cm
‘)
samples as obtained by using the different models tested with vulcanizate
Mode
1500-1100 1500-1200
I400-900 I 400. I 100 1400-1200
TMTS
TBQ
Abs 1st D Abs 1st D Abs 1st D Abs 1st D Abs 1st D Abs 1st D
1500-900
CONCENTRATION
TBP
PLS components
RSEP
PLS components
RSEP
4 2 3 2 3 2 5 2 3 2 3 2
12.5 7.1 21.1 12.7 22.9 13.0 7.3 8.8 11.1 14.8 14.1 16.2
3 2 2 2 2 2 2
8.6 6.9 1.5 7.6 8.7 7.6 10.7
(phr)
. ...
0
3
.
0 0
: -15
L-L-i.,
05
10
-.
15
20
CONCENTRATION
25
30
35
I
t
40
TMTS ,,,hr)
Fig. 2. Plot of scores for the TMTS model, constructed from firstderivative spectra recorded over the wavenumber range 1500900 cm-‘, against the TMTS and TBQ concentrations. (0) First PLS component. (0) Second PLS component.
1 2 1
7.3 9.6 7.6 12.5 8.0
nization was highly correlated with some additive concentrations prior to it. The fact that the best results were obtained in the wider ranges (1500-900 and 1400-900 cm-‘) suggests that all the absorption bands in the spectrum contain relevant information for both additives. Table 3 gives the figures of merit for the straight lines obtained by plotting Gaddedagainst Ground for the calibration and prediction samples for both additives. The parameters for the regression line at a 95% significance level are consistent with a unity slope and zero intercept in all instances. Table 4 gives the individual results obtained for the prediction samples. Quantitation differences were similar for both additives. 3.2. Vulcanizate
The scores for the two PLS components were directly related to the concentration of each additive present in the sample prior to vulcanization (Fig. 2). The black circles in the figure correspond to the values of the scores for the first PLS component with the TMTS concentration and exhibit a positive correlation. The white circles represent the values of the second PLS component with the additive concentration and exhibit a negative correlation. Therefore, the first two PLS components contained virtually all the information required to determine both additives-the two components accounted for 96.0 and 98.2% of the overall variance in each model. Also, the calibration performed from spectra for the extracts after vulca-
1 2
II
Of the 20 samples of vulcanizate II prepared, 13 were used as the calibration set and 7 as the validation set. This was a more complex formulation than vulcanizate I because it contained 6 additives (see Table 1). We studied only four of them. Similarly to the previous vulcanizate, stearic acid was excluded from the model for the same reasons, Also, the aromatic oil exhibited a similar behaviour: it migrated to the vulcanizate surface by exudation and was removed from it. As with vulcanizate I, the optimum spectral range was selected in terms of the spectrum for an extract of
356
M. Blanco et al. /Analytica
Chimica Acta 353 (1997) 351-3.58
Table 3 Figures of merit for the straight lines obtained by plotting the initial additive concentrations the PLSR model for vulcanizate I. The confidence interval is given
prior to vulcanization
Additive
Calibration
Prediction
-0.04fO.23 l.OlZtO.09 0.14
-0.03f0.31 1.OOfO. 13 0.19
O.Olf0.29 0.99Zto. 12 0.13
0.22f0.80 0.89f0.28 0.20
TMTS
Model
C ad&d vs.
1.500-900
Intercept:
1st derivative 2 PLS camp.
Slope: Standard
1500-900 1st derivative 2 PLS camp.
Intercept: Slope: Standard error:
Table 4 Results obtained in the individual vulcanizate I (all in phr)
quantitation
TBQ Sample 1 2 3 4 5 6 7 8 9 10 11
150&900 15@0-1100 1500-1200 1400-900 1400-l 100 1400-1200
of mixtures
of
C Ad&d
C Found
cAdded
C Found
2.0 1.0 4.0 4.0 1.3 1.3 2.7 1.5 2.0 2.0 1.3
2.0 1.0 3.6 4.3 1.1 1.2 2.8 1.6 2.1 1.9 1.3
3.0 2.0 2.8 2.8 3.3 3.3 3.1 1.8 3.0 3.0 3.3
3.1 1.7 2.6 2.6 3.3 3.1 2.8 2.1 3.1 2.8 3.1
Mode
Abs 1st D Abs 1st D Abs 1st D Abs 1st D Abs 1st D Abs 1st D
error:
TMTS
Table 5 % RSEP values for the calibration Range (cm-‘)
CfO”“d
by
the system (Fig. l), using the same criteria as in the previous case. Table 5 shows the predictions obtained in the spectral ranges considered. The lowest %RSEP values were obtained with a model using first-derivative spectra for the range 1400-900 cm, except for CBS, which provided better results with absorbance spectra recorded over the same range. This may be the result of this product contributing little to the spectrum for the extract in this region, and deriving the spectrum might have decreased the sensitivity to this component and hence its predictive capacity for it. Table 6 gives the figures of merit for the straight lines obtained by plotting Gaddedagainst Cfound for the calibration and prediction samples. At a 95% significance level, the lines had a unity slope and a zero intercept; however, the line for CBS (with a far from unity, highly imprecise slope) curved at high concen-
samples as obtained by using the different models tested with vulcanizate CBS
against those calculated
TET
TMTD
II
TBQ
PLS components
RSEP
PLS components
RSEP
PLS components
RSEP
PLS components
RSEP
4 3 3 3 4 4 4 3 5 5 3 6
10.1 10.2 12.9 9.9 18.1 11.1 7.5 10.5 20.2 11.1 11.3 11.6
4 4 3 3 4 5 4 4 3 4 4 4
7.4 7.4 21.6 12.3 6.7 10.8 7.8 6.7 11.4 10.7 8.8 11.0
3 2 4 2 3 3 3 2 3 2 3 2
9.3 3.8 6.7 4.6 111.9 3.9 5.2 3.8 5.8 4.8 6.6 4.2
3 2 3 2 3 2 3 2 3 2 3 3
5.7 5.0 11.1 7.7 14.3 7.7 7.3 4.3 6.5 5.7 8.7 6.1
M. Blanco et al./Analytica
Chimica Acta 353 (1997) 351-358
Table 6 Figures of merit for the straight lines obtained by plotting the initial additive concentrations the PLSR model for vulcanizate II. The confidence interval is given Additive
Model
c ad&d vs.
CBS
1400-900 Absorbance 4 PLS camp.
TMTD
TET
TnQ
Table I Results obtained Sample
351
prior to vulcanization
against those calculated
Calibration
Prediction
Intercept: Slope: Standard error:
0.02ztO.26 0.98-+0.14 0.10
0.44f0.59 0.75f0.32 0.13
14OG900 1st derivative 4 PLS camp.
Intercept: Slope: Standard error:
0.02f0.09 0.98ztO.06 0.06
0.0110.16 1.05f0.13 0.05
1400-900 Absorbance 2 PLS camp.
Intercept: Slope:
0.02+0.13 0.98*0.08 0.09
-0.0310.16 0.07
1400-900
Intercept:
1st derivative 2 PLS camp.
Slope: Standard error:
0.13ztO.32 0.92kO.19 0.18
0.03z!cO.29 0.99fO. 18 0.08
in the individual
quantitation
CBS
Standard
Cfoulld
error:
of mixtures of vulcanizate
by
1.0310.09
II (all in phr)
TMTD
TET
TBQ
CAdded
C Found
C Added
C Found
CAdded
C Found
CAdded
C Found
1.8
1.7
1.0
1.1
1.5
1.5
0.5
-
0.8 I .5
I .9
1.5
1.8 0.5
0.5
1.8 2.5
1.8 2.4
2.2 1.0
2.2 I .6 1.1 2.5
2.2 1.8 1.2 2.2
0.7 1.2 1.6 1.6
0.8 1.2 1.7 1.7
0.7
0.6 1.2 2.1 0.5
0.8 1.6
2.3 1.0 0.8 1.5 2.0 1.4
trations, thus suggesting incomplete extraction of this additive. Table 7 shows the individual results for the different samples of the prediction set. The errors were within +O. 1 phr for all additives except CBS, which gave an error of -0.3 phr in the most concentrated sample; hence the small slope of its Gadded vs. Ground plot. The absence of two values for CBS and TBQ was due to samples with contents below 0.5 phr in both additives, which could not be determined as they lay outside the calibration range. The scores for the first two PLS components in each of the models adopted as optimal were found to be linearly related to the additive concentrations in the samples. In the TBQ and TET models, the first two PLS components contained virtually the whole information; they accounted for 90-98% of the overall
1.2 2.1 0.5
1.9 1.5
0.0 1
2
3
4
5
8
7
8
9
PLs-wmponent5
Fig. 3. MSECV values proposed models.
obtained
in the cross-validation
of the
358
M. Blanco et al./Analytica
variance, depending on the particular additive (Fig. 3). In the TMTD model, the first two PLS components accounted for only 70% of the overall variance; 4 components were required to explain 94% of the variance and ensure correct determination of this additive. Finally, CBS also required 4 components, which gave a sharp minimum in the residual variance obtained in validating the model (see Fig. 3).
Chimica Acta 353 (1997) 351-358
[21 R.G.T. Miller, H.A. Willis, Spectrochim. [31
[41 [51
M [71
4. Conclusions FT-IR spectrometry in combination with multivariate (PLSR) calibration enables the determination of some accelerators and antioxidants added to rubber prior to vulcanizing from the spectra for the CC4 extracts of the vulcanizates, with satisfactory results, when the additive or its products are extractable. As a rule, the use of first-derivative spectra provides the best results and decreases the number of PLS components required to construct the model. However, absorbance spectra are required when there is a low contribution of some additive to the overall spectrum. The wavenumber range must be chosen empirically from the spectra for the Ccl4 extracts since the IR spectra for the individual products produced in the vulcanization process are unknown. Usually, quantitation errors are less than fO.l phr.
[81 [91 UOI 1111 1121 [I31 [I41 [I51 1161 [I71 Df31 [I91 WI
Acknowledgements The authors are grateful to DGCyT for financial support of this work as part of Project PB 93-899, and to Bendix Espafia, S.A. for preparing and processing the samples.
WI 1231
References [l] W.C. Wake, B.K. Tidd, M.J.R. Loadman, Analysis of Rubber and Rubber-like London, 1983.
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Polymers,
Applied
Science
Publishers,
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Acta 19 (1959) 119. V.S. Fikhlengol’ts, R.V. Zolotareva, Y.A. L’vov, Ultra Violet Spectra of Elastomers and Rubber Chemicals (A.E. Stubbs, Trans.), Plenum Press, Data Divn, New York, 1966. ED. Snell, EM. Biffen, Commercial Methods of Analysis, Chemical Publishing Company, Inc., New York, 1964. J.A. Sidwell, High Performance Liquid ChromatographyAnalytical Applications in the Rubber and Plastics Industries, RAPRA Members Report no. 49, 1982. J.B. Pausch, Anal. Chem. 54 (1982) 89A. S.M. Rappaport, D.A. Frase, Anal. Chem. 48 (1976) 476. R.P. Lattimer, R.E. Harris, C.K. Rhee, H. Schulten H, Rubber Chem. Technol. 61 (1988) 639. J.A.J. Jansen, Fresenius’ J. Anal. Chem. 337 (1990) 398. J.L. Gaeta, E.W. Shulter, A.G. Attma, Rubber Age (N.Y.) 101 (1969) 47. H. Egsgaard, E. Larsen, W.B. Pedersen, L. Carlsen, Trends Anal. Chem. 11 (1992) 164. T. Kumar, Analyst 115 (1990) 1319. C.E. Miller, B.E. Eichinger, T.W. Gurley, J.G. Hermiller, Anal. Chem. 62 (1984) 1778. C.E. Miller, P. Edelman, B. Ratner, Appl. Spectrosc. 44 (1990) 574. T. Kumar, Analyst 115 (1990) 1597. B. Vigerust, K. Kolset, S. Nordenson, A. Henriksen, K. Kleveland, Appl. Spectrosc. 45 (1991) 173. J.V. Karstang, A. Henriksen, Chem. Intell. Lab. Sys. 14 (1992) 331. M. Blanco, J. Coello, H. Iturriaga, S. Maspoch, E. Berman, Appl. Spectrosc. 49 (1995) 747. A. Savitzky, M.J.E. Golay, Anal. Chem. 36 (1964) 1627. H. Wold, in: P.R. Krishnaiah (Ed.), Estimation of Principal Components and Related Models by Iterative Least Squares, Multivariate Analysis, Academic Press, New York, 1996. S. Wold, C. Albano, W.J. Dunn III, V. Edlund, B. Eliasson, E. Johansson, B. Norden, M. Sjostriim, in: K.G. Joreskog, H. Wold (Eds.), The Indirect Observation of Molecular Chemical Systems, Systems Under Indirect Observation (Vols. I and II), North-Holland, Amsterdam, 1982. S. Wold, Technometrics 20 (1978) 397. D.M. Haaland, E.V. Thomas, Anal. Chem. 60 (1988) 1193. M. Otto, W. Wegscheider, Anal. Chem. 57 (1985) 63. M. Vidal de Carter, Gauchos y Elastomeros, Barcelona, 1984.
ELSEVIER
Analytica
Chimica Acta 353 (1997) 351-358
Determination of accelerators and antioxidants in vulcanized rubber by fourier transform infrared spectrophotometry M. Blanco*, J. Coello, H. Iturriaga, S. Maspoch, E. Bertran Departament de Quhica,
Unitat de Quimica Analitica, Facultat de Citncies, Universitat Authoma de Barcelona, E-08193 Bellaterru, Spain Received
3 March 1997; received in revised form 11 June 1997; accepted
13 June 1997
Abstract During vulcanization, rubber is treated with different substances that have a marked influence on the properties of the end product. Identifying and determining the chemical species responsible for such properties is rendered difficult by the fact that some are incorporated into the vulcanizate or decompose during the process. In this work, we developed a new method for the determination of vulcanization accelerators and antioxidants based on Fourier Transform Infrared spectra of the CC& extracts of vulcanized rubber specimens. Calibration is performed by using Partial Least-Squares Regression (PLSR); the additive concentrations prior to vulcanization are related to the spectra of the fragments or decomposition products extracted from the polymer matrix following vulcanization. The effects of the spectral mode (absorbance or first-derivative) and wavenumber range were assessed by constructing various models to ensure accurate determinations. The proposed method was applied to two vulcanizates obtained by two different procedures; the results were quite satisfactory in both cases. :Q 1997 Elsevier Science B.V. Keywords: Multivariate calibration; Fourier Antioxidants; Vulcanization accelerators
Transform
Infrared
(FT-IR);
Rubber
additives;
Partial
Least-Squares
Regression
(PLSR); _
1. Introduction Rubber is a highly deformable plastic material. For the product to be useful, polymer chains must be linked to form an elastic network. The process that facilitates the transformation of the plastic material into an elastic material, i.e. vulcanization, is carried out at a high temperature and, usually, in the presence of elemental sulphur. Occasionally, the sulphur is replaced by an S-donor (a ‘vulcanizer’) that decomposes at the vulcanization temperature to establish *Corresponding author. Tel.: +34 +34 (3) 581 2477; e-mail: [email protected].
(3)
581
1367;
fax:
0003-2670/97/$17.00 % 1997 Elsevier Science B.V. All rights reserved. PII SOOO3-2670(97)00389-9
bridges consisting of a single sulphur atom between polymer chains. Such bridges are thermally more resistant than the disulphide and polysulphide bridges typically formed in the traditional vulcanization process based on elemental sulphur. The mixture of polymer and vulcanizing agents is supplied with vulcanization accelerators to increase the rate of reaction between both components and to save vulcanizing ingredients, as well as with antioxidants to protect the mixture from potential oxidation reactions. Also reinforcing agents and fillers that usually make the mixture more resistant to tear and abrasion, and plasticizers that facilitate the incorporation of all the additives, are added. The physical
352
M. Blanco et al. /Analytica
Chimica Acta 353 (1997) 351-358
properties of the rubber thus obtained depends on the ingredients and procedure used in its vulcanization. The wide variety of additives used and their low concentrations, the total additive content is typically less than 5% phr (phr stands for ‘parts per hundred rubber’, a concentration unit defined as g of additive added to 100 g of polymer-copolymer), in addition to the transformations they may undergo at the vulcanization temperature, and their role in the process, make their determination rather complex. For these reasons, analysis of this type of sample are more often carried out by using physical tests and identifying and estimating the polymer composition and its reinforcing agents [ 11. Analysing for rubber additives always entails their prior extraction; there are, however, some reported procedures for the direct determination of antioxidants in rubber, which can only be applied under special circumstances (e.g. to freshly aged rubber of known composition containing no carbon black) [2]. Usually, the additives in vulcanized materials can be partly or fully extracted by using an appropriate solvent, Thus, ketone extracts of rubber contain primarily oils and plasticizers, whereas chloroform and alcoholic extracts can contain most accelerators. In any case, the extracts are complex mixtures of the starting materials, vulcanizers, and cleavage products from both, oils accompanying the polymer itself, etc. Extracts can be analysed by using spectrometric techniques. Thus, UV spectrophotometry was used to determine some accelerators and S [3]; plasticizers are usually identified from the infrared spectrum of the residue obtained after the additives are extracted and the solvent evaporated [4]. Chromatographic techniques have also been used in the analysis of extracts, both to identify polymers and additives [5-91, and to quantify some of them [lO,l 11. Major breakthroughs in Fourier Transform Infrared and Near Infrared (FT-IR and NIR) spectrophotometry and the power of chemometric techniques have facilitated the determination of polymer components in mixtures with no prior separation [12-171. However, all applications reported in this respect are concerned with non-vulcanized polymer system, which facilitate quantitative extraction and avoid altering the initial products by the high temperatures involved in the vulcanization process. Recently [18], IT-IR and Partial Least-Squares Regression (PLSR) were used for
the analysis of mixtures of additives supplied to the polymer prior to vulcanizing. In this work, we investigated the determination of some rubber additives present in a vulcanized polymer matrix by solvent extraction and subsequent FT-IR spectrophotometric quantitation, using PLSR calibration. For this purpose, the additive concentrations supplied to the polymer were correlated with the spectra obtained after vulcanization.
2. Experimental
2.1. Apparatus and software All measurements were made on a Perkin-Elmer 1760 FT-IR spectrophotometer using the IRDM software package to acquire and process spectra. PLSR calibration was performed as implemented in the programme Unscrambler v. 3.54, from CAM0 A/S, using spectra exported in JCAMP format. 2.2. Composition of vulcanizates We studied two different vulcanizate formulations. One (vulcanizate I) consisted of 60 : 40 styrene-butadiene polymer to which sulphur was added as vulcanizing agent. The other (vulcanizate II) was composed of 80 : 20 poly-isoprene-butadiene and several Sdonor additives that made up a more complex vulcanizing system. The composition of both formulations is shown in Table 1. Single values are proportions (in phr), which were maintained constant; all other values are the concentration ranges used to prepare the different samples. 2.3. Preparation of samples and recording of extract spectra An appropriate amount of polymer was mixed with the required amounts of vulcanization additives. The additives were incorporated into the polymer in an open cylinder mixer consisting of two parallel, convergent metal rollers rotating at a different rate in opposite directions. The additive mixture was added to the polymer dough as this was passed through the mixer rollers. This operation was repeated until a polymer sheet with additives, as uniformly distributed
M. Blanc0 et al. /Analytica Chimica Acra 353 (1997) 351-358 Table 1 Composition
of additives in the vulcanizates,
353
in parts per hundred rubber (phr) Vulcanizate I Styrene-butadiene
Vulcanizate II Polyisoprene-butadiene
Basic recipes ZnO Stearic acid
5 0.5-3.0
5 0.5-2.5
Reinforcing agents Carbon black 50
50
80
Polymer Additives
(phr)
Accelerators and vulcanizers Copper dimethyldithiocarmamate Sulphur Tetramethylthiuram monosulfide (TMTS) Tetraethylthiuramdisultide (TET) Tetramethylthiuramdisulfide (TMTD) N-cyclohexyl-2-benzothiazole-sulfenamide Antioxidants 1,2-dihydro-2,2,4 Softeners Aromatic
trybutylquinoline
processing
0.11 0.34 1.0-3.5 0.5-2.5 0.5-2.5 0.5-2.5
(CBS)
(TBQ)
0.5-2.5
0.5-4.0
3.0-8.0
oil (AR)
as possible, was obtained. Finally, the rubber sheet was pressed and cut into three squares of approximate dimensions 15 x 15 x0.3 cm. Each sheet was vulcanized separately at 165°C for 5 min. Only the last sheet was used as sample in order to avoid contamination and to ensure reproducibility of the vulcanization conditions. The vulcanized sheets were cut into pieces of 0.5 cm*. About 5 g of vulcanized material was treated with 75 ml of Ccl4 in a Soxhlet apparatus for 6-8 h. The extract thus obtained was concentrated to 5 ml with the aid of an IR beam lamp. The spectra for the Ccl4 extract from each mixture was recorded in a liquid cuvette with NaCl windows and a light path of 150 pm. Spectra were recorded at 4cm-’ intervals over the wavenumber range 4000500 cm-‘. Overall 50 scans per extract were performed. Spectral recordings were converted into absorbance measurements, none of which exceeded 1.6 absorbance units. The solvent spectrum was recorded under the same conditions and subtracted from those for the extracts. First-derivative spectra were obtained from absorbance spectra by using the Savitzky-Golay algorithm [ 191.
O3 r7
20001800
;,
1500
I
1400
1300
WAVENUMBER
1200
1100
1000
900
(cm-‘)
Fig. 1. Absorbance spectrum for the CC14 extract of a sample of: Vulcanizate I (Additive contents in phr: stearic acid 2.3; (-) TBQ 2.7; TMTS 3.0). (- - - -) Vulcanizate II (Additive contents in phr: stearic acid 0.5; CBS 0.5; TMTD 2.5; TET 1.8; TBQ 2.5: AR 8.0.
Fig. 1 shows the spectra for the extract from a mixture of each of the two vulcanizates studied. 3. Results and discussion The chemical transformations undergone by the different additives involved in the vulcanization pro-
354
hf. Blanc0 et al. /Analytica
cess lead to extracts containing also products resulting from their decomposition; it is therefore impossible to select an optimum zone for quantitation from the individual spectra for the additives prior to vulcanization. We studied different spectral ranges that were chosen so as to include the more significant bands in the absorption spectra for the extract of each formulation. As a rule, we discarded those spectral zones where absorption was negligible so as to avoid introducing variables with a very low signal-to-noise ratio in the calibration, which might detract from precision. We also excluded the range from 4000 to 1800 cm-’ owing to its poor distinguishing power (absorption in this range was mostly due to C-H stretching, which is very strong and exhibited by most rubber additives). The range from 1650-1500 cm-’ was also avoided owing to the high noise in the CC14 absorption (even if the solvent spectrum was subtracted). The calibration technique used with all the additives was PLSR [20,21]. Each additive was calibrated by using an individual model. We employed both absorbance and first-derivative spectra that were always autoscaled. The models were internally validated by cross-validation, using the leave-one-out method [22]. The number of PLS components to be used in each case was determined by applying Thomas and Haaland’s criterion to the residual variance obtained in the cross-validation [23]. The results obtained with the different models were compared via the relative standard error of prediction (%RSEP) [24], defined as
where m is the total number of samples, Ci the calculated concentration in sample i and Ci the theoretical concentration of additive introduced prior to vulcanization. 3.1. Vulcanizate I A set of 23 samples containing variable amounts of three additives (stearic acid, TBQ and TMTS) was prepared. Twelve of the samples were used as the calibration set and the other eleven as the validation set. Calibration samples were chosen in such a way that they spanned the entire additive concentration range.
Chimica Acta 353 (1997) 351-358
Most of the steak acid was converted into stearate [25], so if it was extracted its absorption band in the extract would be interfered by CC& absorption. Also, most of it accumulated at the rubber sheet surface in the form of a thin white film that was partly removed in handling the vulcanized sheet. This precluded correlating the amount of steak acid initially added to the sample with the information contained in the spectrum for the extract, so only the additives TBQ and TMTS were quantified. Different wavenumber ranges were studied in order to select the most appropriate range for constructing an effective calibration model. As can be seen in absorption bands were only Fig. 1, significant observed in the region from 1.500 to 900 cm-‘; also, three bands appeared below 1300 cm-’ that were used to establish the suitable spectral ranges, viz. 1500900, 1500-l 100 and 1500-1200 cm-‘. The polymer and its additives (surfactants, oils, etc.) were also extracted into CCL and absorbed in the region 1500-1400 cm-‘, so the above models were assayed from 1400 cm-‘, as well. The results predicted for TMS and TBQ (as %RSEP) from the different wavenumber ranges studied in the absorbance and first-derivative spectral modes are given in Table 2. As a rule, %RSEP values were smaller for first-derivative spectra than for absorbance spectra. The use of first-derivative spectra led to more simple models (i.e. with fewer PLS components required to construct them) in the determination of TBQ; also, %RSEP values increased as the wavenumber range was shortened. The model obtained by using the first derivative spectra over the range 1500900 cm-’ was chosen as optimal because it gave rise to %RSEP values virtually identical with those of the absorbance model over the range 1400-900 cm-’ and required two PLS components only. The spectral model and wavenumber range were found to influence the determination of TMTS similarly to that of TBQ. Differences in % RSEP among the different wavenumber ranges studied were not too large in the first-derivative spectral mode; also, the lowest % RSEP values were obtained in the region 1500-900 cm-‘, which can be ascribed to better resolution of overlapped bands and a decreased baseline shift by effect of extract turbidity.
355
M. Blanco et al. /Analytica Chimica Acta 353 (1997) 351-358 Table 2 %RSEP values for the calibration Range (cm
‘)
samples as obtained by using the different models tested with vulcanizate
Mode
1500-1100 1500-1200
I400-900 I 400. I 100 1400-1200
TMTS
TBQ
Abs 1st D Abs 1st D Abs 1st D Abs 1st D Abs 1st D Abs 1st D
1500-900
CONCENTRATION
TBP
PLS components
RSEP
PLS components
RSEP
4 2 3 2 3 2 5 2 3 2 3 2
12.5 7.1 21.1 12.7 22.9 13.0 7.3 8.8 11.1 14.8 14.1 16.2
3 2 2 2 2 2 2
8.6 6.9 1.5 7.6 8.7 7.6 10.7
(phr)
. ...
0
3
.
0 0
: -15
L-L-i.,
05
10
-.
15
20
CONCENTRATION
25
30
35
I
t
40
TMTS ,,,hr)
Fig. 2. Plot of scores for the TMTS model, constructed from firstderivative spectra recorded over the wavenumber range 1500900 cm-‘, against the TMTS and TBQ concentrations. (0) First PLS component. (0) Second PLS component.
1 2 1
7.3 9.6 7.6 12.5 8.0
nization was highly correlated with some additive concentrations prior to it. The fact that the best results were obtained in the wider ranges (1500-900 and 1400-900 cm-‘) suggests that all the absorption bands in the spectrum contain relevant information for both additives. Table 3 gives the figures of merit for the straight lines obtained by plotting Gaddedagainst Ground for the calibration and prediction samples for both additives. The parameters for the regression line at a 95% significance level are consistent with a unity slope and zero intercept in all instances. Table 4 gives the individual results obtained for the prediction samples. Quantitation differences were similar for both additives. 3.2. Vulcanizate
The scores for the two PLS components were directly related to the concentration of each additive present in the sample prior to vulcanization (Fig. 2). The black circles in the figure correspond to the values of the scores for the first PLS component with the TMTS concentration and exhibit a positive correlation. The white circles represent the values of the second PLS component with the additive concentration and exhibit a negative correlation. Therefore, the first two PLS components contained virtually all the information required to determine both additives-the two components accounted for 96.0 and 98.2% of the overall variance in each model. Also, the calibration performed from spectra for the extracts after vulca-
1 2
II
Of the 20 samples of vulcanizate II prepared, 13 were used as the calibration set and 7 as the validation set. This was a more complex formulation than vulcanizate I because it contained 6 additives (see Table 1). We studied only four of them. Similarly to the previous vulcanizate, stearic acid was excluded from the model for the same reasons, Also, the aromatic oil exhibited a similar behaviour: it migrated to the vulcanizate surface by exudation and was removed from it. As with vulcanizate I, the optimum spectral range was selected in terms of the spectrum for an extract of
356
M. Blanco et al. /Analytica
Chimica Acta 353 (1997) 351-3.58
Table 3 Figures of merit for the straight lines obtained by plotting the initial additive concentrations the PLSR model for vulcanizate I. The confidence interval is given
prior to vulcanization
Additive
Calibration
Prediction
-0.04fO.23 l.OlZtO.09 0.14
-0.03f0.31 1.OOfO. 13 0.19
O.Olf0.29 0.99Zto. 12 0.13
0.22f0.80 0.89f0.28 0.20
TMTS
Model
C ad&d vs.
1.500-900
Intercept:
1st derivative 2 PLS camp.
Slope: Standard
1500-900 1st derivative 2 PLS camp.
Intercept: Slope: Standard error:
Table 4 Results obtained in the individual vulcanizate I (all in phr)
quantitation
TBQ Sample 1 2 3 4 5 6 7 8 9 10 11
150&900 15@0-1100 1500-1200 1400-900 1400-l 100 1400-1200
of mixtures
of
C Ad&d
C Found
cAdded
C Found
2.0 1.0 4.0 4.0 1.3 1.3 2.7 1.5 2.0 2.0 1.3
2.0 1.0 3.6 4.3 1.1 1.2 2.8 1.6 2.1 1.9 1.3
3.0 2.0 2.8 2.8 3.3 3.3 3.1 1.8 3.0 3.0 3.3
3.1 1.7 2.6 2.6 3.3 3.1 2.8 2.1 3.1 2.8 3.1
Mode
Abs 1st D Abs 1st D Abs 1st D Abs 1st D Abs 1st D Abs 1st D
error:
TMTS
Table 5 % RSEP values for the calibration Range (cm-‘)
CfO”“d
by
the system (Fig. l), using the same criteria as in the previous case. Table 5 shows the predictions obtained in the spectral ranges considered. The lowest %RSEP values were obtained with a model using first-derivative spectra for the range 1400-900 cm, except for CBS, which provided better results with absorbance spectra recorded over the same range. This may be the result of this product contributing little to the spectrum for the extract in this region, and deriving the spectrum might have decreased the sensitivity to this component and hence its predictive capacity for it. Table 6 gives the figures of merit for the straight lines obtained by plotting Gaddedagainst Cfound for the calibration and prediction samples. At a 95% significance level, the lines had a unity slope and a zero intercept; however, the line for CBS (with a far from unity, highly imprecise slope) curved at high concen-
samples as obtained by using the different models tested with vulcanizate CBS
against those calculated
TET
TMTD
II
TBQ
PLS components
RSEP
PLS components
RSEP
PLS components
RSEP
PLS components
RSEP
4 3 3 3 4 4 4 3 5 5 3 6
10.1 10.2 12.9 9.9 18.1 11.1 7.5 10.5 20.2 11.1 11.3 11.6
4 4 3 3 4 5 4 4 3 4 4 4
7.4 7.4 21.6 12.3 6.7 10.8 7.8 6.7 11.4 10.7 8.8 11.0
3 2 4 2 3 3 3 2 3 2 3 2
9.3 3.8 6.7 4.6 111.9 3.9 5.2 3.8 5.8 4.8 6.6 4.2
3 2 3 2 3 2 3 2 3 2 3 3
5.7 5.0 11.1 7.7 14.3 7.7 7.3 4.3 6.5 5.7 8.7 6.1
M. Blanco et al./Analytica
Chimica Acta 353 (1997) 351-358
Table 6 Figures of merit for the straight lines obtained by plotting the initial additive concentrations the PLSR model for vulcanizate II. The confidence interval is given Additive
Model
c ad&d vs.
CBS
1400-900 Absorbance 4 PLS camp.
TMTD
TET
TnQ
Table I Results obtained Sample
351
prior to vulcanization
against those calculated
Calibration
Prediction
Intercept: Slope: Standard error:
0.02ztO.26 0.98-+0.14 0.10
0.44f0.59 0.75f0.32 0.13
14OG900 1st derivative 4 PLS camp.
Intercept: Slope: Standard error:
0.02f0.09 0.98ztO.06 0.06
0.0110.16 1.05f0.13 0.05
1400-900 Absorbance 2 PLS camp.
Intercept: Slope:
0.02+0.13 0.98*0.08 0.09
-0.0310.16 0.07
1400-900
Intercept:
1st derivative 2 PLS camp.
Slope: Standard error:
0.13ztO.32 0.92kO.19 0.18
0.03z!cO.29 0.99fO. 18 0.08
in the individual
quantitation
CBS
Standard
Cfoulld
error:
of mixtures of vulcanizate
by
1.0310.09
II (all in phr)
TMTD
TET
TBQ
CAdded
C Found
C Added
C Found
CAdded
C Found
CAdded
C Found
1.8
1.7
1.0
1.1
1.5
1.5
0.5
-
0.8 I .5
I .9
1.5
1.8 0.5
0.5
1.8 2.5
1.8 2.4
2.2 1.0
2.2 I .6 1.1 2.5
2.2 1.8 1.2 2.2
0.7 1.2 1.6 1.6
0.8 1.2 1.7 1.7
0.7
0.6 1.2 2.1 0.5
0.8 1.6
2.3 1.0 0.8 1.5 2.0 1.4
trations, thus suggesting incomplete extraction of this additive. Table 7 shows the individual results for the different samples of the prediction set. The errors were within +O. 1 phr for all additives except CBS, which gave an error of -0.3 phr in the most concentrated sample; hence the small slope of its Gadded vs. Ground plot. The absence of two values for CBS and TBQ was due to samples with contents below 0.5 phr in both additives, which could not be determined as they lay outside the calibration range. The scores for the first two PLS components in each of the models adopted as optimal were found to be linearly related to the additive concentrations in the samples. In the TBQ and TET models, the first two PLS components contained virtually the whole information; they accounted for 90-98% of the overall
1.2 2.1 0.5
1.9 1.5
0.0 1
2
3
4
5
8
7
8
9
PLs-wmponent5
Fig. 3. MSECV values proposed models.
obtained
in the cross-validation
of the
358
M. Blanco et al./Analytica
variance, depending on the particular additive (Fig. 3). In the TMTD model, the first two PLS components accounted for only 70% of the overall variance; 4 components were required to explain 94% of the variance and ensure correct determination of this additive. Finally, CBS also required 4 components, which gave a sharp minimum in the residual variance obtained in validating the model (see Fig. 3).
Chimica Acta 353 (1997) 351-358
[21 R.G.T. Miller, H.A. Willis, Spectrochim. [31
[41 [51
M [71
4. Conclusions FT-IR spectrometry in combination with multivariate (PLSR) calibration enables the determination of some accelerators and antioxidants added to rubber prior to vulcanizing from the spectra for the CC4 extracts of the vulcanizates, with satisfactory results, when the additive or its products are extractable. As a rule, the use of first-derivative spectra provides the best results and decreases the number of PLS components required to construct the model. However, absorbance spectra are required when there is a low contribution of some additive to the overall spectrum. The wavenumber range must be chosen empirically from the spectra for the Ccl4 extracts since the IR spectra for the individual products produced in the vulcanization process are unknown. Usually, quantitation errors are less than fO.l phr.
[81 [91 UOI 1111 1121 [I31 [I41 [I51 1161 [I71 Df31 [I91 WI
Acknowledgements The authors are grateful to DGCyT for financial support of this work as part of Project PB 93-899, and to Bendix Espafia, S.A. for preparing and processing the samples.
WI 1231
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