Determination of Carboxyl Content in High-Yield Kraft Pulps Using

The PLS regression method was used to develop a correlation between the PAS ... two sets of weights w (X-weights) and c (Y-weights) are computed to cr...
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Anal. Chem. 2006, 78, 6818-6825

Determination of Carboxyl Content in High-Yield Kraft Pulps Using Photoacoustic Rapid-Scan Fourier Transform Infrared Spectroscopy Nishi K. Bhardwaj, Vinh Q. Dang, and Kien L. Nguyen*

Australian Pulp and Paper Institute, Department of Chemical Engineering, Monash University, Clayton, Victoria, Australia

Pinus radiata kraft pulps with varying carboxyl content were studied using Fourier transform infrared photoacoustic spectroscopy (FT-IR-PAS). The examined pulp samples, with Kappa number ranging from 20.8 to 128, originated from pulping experiments conducted in flowthrough reactors utilizing varying effective alkali, temperature, and cooking time. A partial least-squares (PLS) analysis was used to formulate a model that correlates the spectral data with the carboxyl content of pulp. Using three principal components, the resultant PLS model could explain ∼98.5% of the variance in the X-matrix (spectral features) and 96.8% of the variance in the Y-matrix (measured carboxyl content). The FT-IR-PAS technique in combination with PLS analysis predicts the carboxyl content of the pulps with a high degree of accuracy. This method is much faster than the conventional titration methods and also not destructive to the pulp sample. The kraft pulping process is currently used to produce more than 80% of chemical pulps worldwide. High-yield kraft pulps have been commonly selected for the manufacture of high-strength papers for containers. When suspended in water, cellulosic fibers produced from the kraft process acquire a charge due to the ionization of acidic groups in the hemicelluloses and lignin. The ionizable groups on cellulosic fibers, which depend on the origin of the fibers and on the chemical treatment conditions, comprise carboxylic acid, sulfonic acid, alcoholic, and phenolic groups.1 Additional contributions arise from fatty and resin acids and from pectins (polymers of galacturonic acid). The sulfonic acid groups are mainly found in sulfite pulps. Under slightly acidic or neutral conditions, the main ionized groups in wood kraft fibers are carboxyl.2 These ionizable groups in carbohydrates are weakly dissociated with an ionization constant, pKa, 4-5. The carboxyl groups in oxidized lignin have a pKa of ∼5.0 whereas carboxyl groups in fatty acids and resin acids have a pKa within the range 5.0-6.5.3,4 The phenolic groups of lignin are also ionizable but at a higher pH (pKa 7.3-10.5).3 * Corresponding author. Tel: +61 3 9905 3429. Fax: +61 3 9905 3413. E-mail: [email protected]. (1) Lindstro ¨m, T. In Paper Chemistry; Roberts, J. C., Ed.; Blackie: Glasgow, 1991; pp 25-28. (2) Sjo ¨stro ¨m, E. Nord. Pulp Pap. Res. J. 1989, 4, 90-93. (3) Sundberg, A.; Pronovich, A.; Holmbolm, B. J. Wood Chem. Technol. 2000, 20, 71-92.

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The carboxyl content has been a matter of concern during wood pulping and is of great importance for the sorption of various ions onto unbleached kraft fibers. Carboxyl groups situated in or at the surface of fibers and fines can be considered beneficial since, in addition to the swelling effect, these groups can interact with added cationic process chemicals, providing bridging conditions for retaining fillers and fines in the paper sheet. Previous studies indicate that the fiber hydrophilicity and swelling, which are also highly relevant to fiber-fiber bonding, are affected by fiber charge.5,6 Various methods developed for measuring the charge of fibers4 are time-consuming. Fourier transform infrared (FT-IR) spectroscopy has become a versatile research tool for elucidating the structure, physical properties, and interactions of carbohydrates. The use of midinfrared FT-IR spectroscopy for analysis of carbohydrates has been comprehensively reviewed by Kae`ura´kova´ and Wilson.7 Gellerstedt and Gatenholm8 used FT-IR to study the modification of bleached kraft fibers by reacting with succinic anhydride. They observed the change in the absorption intensity of the carbonyl groups, the sum of esters and carboxylic acids, followed the trend of the ion exchange capacity of fibers, as determined by titration. Recently, Fardim et al.9 investigated the anionic groups on birch kraft and aspen chemithermomechanical pulps and assessed by FT-IR-ATR the effect of methylene blue sorption on a proximate surface layer of 1 µm. The intensity of the characteristic broad peak of methylene blue at 1598 cm-1, after the normalization (1800 cm-1 taken as a reference), exhibits the same tendency as observed in the methylene blue isotherms; i.e., the intensity increases with the amount of methylene blue sorbed. Bjarnestad and Dahlman10 summarized the results from a number of investigations in which FT-IR has been used together with partial least-squares (PLS) analyses for rapid identification of lignin and carbohydrates in wood and pulps. Since 1980, the photoacoustic spectroscopy (PAS) has gradually emerged as a valuable analytical tool mainly due to the developments of FT-IR, low-noise electronics, high-sensitivity (4) Scott, W. E. Principles of Wet End Chemistry, 2nd ed.; TAPPI Press: Atlanta, GA, 1996. (5) Laine, J.; Stenius, P. Paperi Ja Puu (Pap. Timber) 1997, 79, 257-266. (6) Zhang, Y.; Sjo¨gren, B.; Engstrand, P.; Htun, M. J. Wood Chem. Technol. 1994, 14, 83-102. (7) Kae`ura´kova´, M.; Wilson, R. H. Carbohydr. Polym. 2001, 44, 291-303. (8) Gellerstedt, F.; Gatenholm, P. Cellulose 1999, 6, 103-121. (9) Fardim, P.; Moreno, T.; Holmbom, B. J. Colloid Interface Sci. 2005, 290, 383-391. (10) Bjarnestad, S.; Dahlman, O. Anal. Chem. 2002, 74, 5851-5858. 10.1021/ac0605952 CCC: $33.50

© 2006 American Chemical Society Published on Web 08/23/2006

microphones, and progress made in computerized data processing. PAS is unique as a sampling technique as it (i) does not require sample to be transparent, (ii) is not very sensitive to the condition of the surface, and (iii) is capable of probing at sample depths ranging from several micrometers to more than 100 µm. Limits of detection of the PAS, which relies on the absorption of radiation energy by a sample and subsequent detection of the acoustic waves, surpass those of conventional absorption-based methods by a factor of typically 10-1000.11 Thermal waves propagating from the region where the absorption has taken place to the sample’s light-irradiated surface decay rapidly. The so-called thermal diffusion length, µt (cm), is given by eq 1, where D is sample’s

µt ) xD/πVv

(1)

thermal diffusivity (cm2/s), V is the moving mirror velocity (cm/s), and ν is the wavenumber (cm-1). FT-IR-PAS allows for the analysis of opaque and highly absorbing samples the intrinsic characteristics of which normally preclude recording of good-quality infrared absorption spectra by means of traditional IR spectroscopy techniques. In the past, the FT-IR-PAS method has been used to analyze wood samples. The experiments comprised studies on the effect that light-induced changes have on the surface properties of acetylated or poly(ethylene glycol)-impregnated wood,12 comparison of spectral differences between red oak and redwood,13 depth profile measurements in puspa, and kapur woods exposed to various weathering environments.14 Recently, Bjarnestad and Dahlman10 use FT-IR-PAS to analyze the composition of hardwood and softwood pulps. They concluded that, by using four principal components, the FT-IR-PAS technique in combination with PLS could accurately predict the contents of carbohydrates, i.e., xylose, glucose, mannose, arabinose, galactose, and hexenuronic acid (hexA) residues, as well as the content of lignin measured in terms of Kappa numbers (κ) of the pulps. The usefulness of PAS has also been demonstrated when assessing thermal and chemical properties of bleached wood pulp and finished papers,15 proving that this technique is useful for comparing, controlling, and evaluating the effects of various processing parameters on the properties of the resulting pulp and paper. Gurnagul et al.16 obtained FT-IR-PAS spectra of bleached kraft papers prepared from a pulp subjected to different degrees of beating. They concluded that the effect of sheet structure should be considered when comparing quantitatively spectra of different sheets. Halttunen et al.17 investigated the applicability of FT-IRPAS depth profiling in the studies of coated papers and presented a modified method for calculating coating thickness from spectral information. (11) Foster, N. S.; Amonette, J. E.; Autrey, T.; Ho, J. T. Sens. Actuators, B: Chem. 2001, 77, 620-624. (12) Ohkoshi, M. J. Wood Sci. 2002, 48, 394-401. (13) Kuo, M. L.; McClelland, J. D.; Luo, S.; Chien, P. L.; Walker, R. D.; Hse, C. Y. Wood Fiber Sci. 1988, 20, 132-145. (14) Yamauchi, S.; Sudiyani, Y.; Imamura, Y.; Doi, S. J. Wood Sci. 2004, 50, 433-438. (15) Lima, C. A. S.; Lima, M. B. S.; Miranda, L. C. M.; Baeza, J.; Freer, J.; Reyes, N.; Ruiz, J.; Silva, M. D. Measure. Sci. Technol. 2000, 11, 504-508. (16) Gurnagul, N.; St-Germain, F. G. T.; Gray, D. G. J. Pulp Pap. Sci. 1986, 12, 156-159. (17) Halttunen, M.; Tenhunen, J.; Saarinen, T.; Stenius, P. Vib. Spectrosc. 1999, 19, 261-269.

In a previous study, we have presented the potential use of FT-IR-ATR in combination with PLS method for predicting fiber charge of unbleached kraft pulps.18 In a separate study, we found that the generation of fiber surface charge during refining of softwood high-yield kraft pulp could be monitored by FT-IR-ATR. The characteristic bands within 1700-1300 cm-1 range were found to be strongly associated with the fiber surface charge, and reliable PLS1 calibration models could be established to correlate the FT-IR spectral data and the surface charge of the refined pulps.19 In another study, based on the transmission FT-IR spectra of highyield pine kraft pulps, a quick and reliable FT-IR method was established using a multivariate analysis to take into account all the characteristic bands of lignin and hexA groups to predict κ and hexA content in the pulps.20 In this study, the predicted values were found to compare closely with the measured data. The main objective of the research study described here is to evaluate the potential use of FT-IR-PAS for quantitative determination of carboxyl content in kraft pulps. This was achieved by considering the characteristic bands of carboxylic acid and carboxylate groups. Two sets of spectral data, which include characteristic bands of related functional groups, were collected. The first set was integrated with a multivariate analysis to formulate a model for correlating the selected spectral information with carboxyl content of kraft pulps. The second set was used to test the accuracy of the model. The results obtained are compared to data acquired from the same samples by means of conductometric titrations. It appears that, based on our comprehensive literature review, the work described here is the first attempt ever made to develop the FT-IR-PAS technique for quantitative analysis of carboxyl content in Pinus radiata kraft pulps. EXPERIMENTAL SECTION Kraft Pulping Conditions. All pulping experiments were conducted in 2-L flow-through reactors. Some 230 g of wood chips (average dimension of 25 × 25 × 3 mm) of P. radiata on an ovendry basis was used in each cook. The wood chip moisture content was 51.4%. Twenty-six kraft pulp samples, with κ ranging from 20.8 to 128, were produced using cooking liquor at 0.5-1.0 M effective alkali as Na2O. The sulfidity (defined as the ratio of the concentrations of Na2S and (Na2S + NaOH)), where the concentrations are expressed as gram per liter Na2O of the cooking liquor, was 25%. The temperature was ramped from a room temperature of 23 to 108 °C at a rate of 3 °C/min in ∼28 min. These chips were then impregnated with the cooking liquor at 108 °C for 30 min before being cooked at 140-155 °C, which was ramped from impregnation temperature at a rate of 3 °C/min. Different cooking times (from 90 to 250 min) were used to produce pulps of different κ. The calculated H factor, defined as the equivalent time needed to achieve the same extent of delignification as at 100 °C, ranged from 208 to 842 based on an estimated activation energy of 134 kJ/mol‚K. To quench the reactions, cold tap water was admitted into the reactors at the end of each cook. Subsequently, the pulps were thoroughly washed in the reactors for ∼120 min before being disintegrated in a laboratory disintegra(18) Bhardwaj, N. K.; Duong, T. D.; Hoang, V.; Nguyen, K. L. J. Colloid Interface Sci. 2004, 274, 543-549. (19) Bhardwaj, N. K.; Hoang, V.; Nguyen, K. L. Bioresource Technol. In press. (20) Hoang, V.; Bhardwaj, N. K.; Nguyen, K. L. Carbohydr. Polym. 2005, 61, 5-9.

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tor. The pulps were then washed again in a basket with a 200mesh screen. The washed pulps were sieved through a screen with 0.15-mm slots for shive removal and then thoroughly washed with deionized water using a vacuum Bu¨chner funnel to form a wet fiber pad of ∼20% dryness content. The washed pulps were crumbed and stored at 4 °C for subsequent tests. Chemicals. Sodium hydroxide, hydrochloric acid, and sodium chloride used for the determination of carboxyl content were of analytical grades. These chemicals were diluted with deionized water having a conductivity of 8 × 10-4 mS/cm to the desired concentration before use. Nitrogen was used to prevent the absorption of carbon dioxide into the test samples during the conductometric titrations for fiber charge determination. Measurement of K. Determination of κ, a measure of the reactivity of the residual lignin in pulp, of thoroughly washed pulp samples was carried out following a standard procedure described in Tappi test method T 236 om-99. In this test, the consumption of potassium permanganate during oxidation of the pulp under standardized conditions is measured and the resulting value used as an indirect measure of the lignin content. The κ was not corrected for the hexA content of pulp. For various pulps, the corresponding κ range between 20.8 and 128. For 12 pulp samples, κ is in the 20-60 range while 9 specimens have κ between 60 and 100. The remaining five pulp samples are characterized by higher κ (100-128). Measurement of Pulp Brightness. To determine the brightness of the paper handsheet, the TAPPI test method T452 om-98 at 457-nm directional reflectance was used. Measurement of Carboxyl Content. Prior to undertaking charge measurements, the pulp samples were converted to their fully protonated form by soaking the pulp at 1% consistency in 0.01 M HCl acid for 16 h as suggested by Lloyd and Horne.21 The pulp pH after 16 h of soaking was close to 2.2. The pulp was then vacuum filtered using a Bu¨chner funnel and washed several times with deionized water until the pH of the water filtrate was close to 6.0. The carboxyl content was analyzed using the conductometric titration method described previously,22 initially outlined by Katz et al.23 Approximately 0.5 g of the protonated pulp was dispersed in 100 mL of 1.0 mM NaCl, and 0.5 mL of 0.05 M HCl added before the start of each titration. The titration was performed with 0.05 M NaOH at 25 °C using a 718 STAT Titrino autotitrator from Metrohm and a LC-81 conductivity meter from TPS Pty. Ltd. The conductivity measurements were performed every 30 s after each addition of 0.05 mL of alkali solution. The conductometric titration was based on changes in conductance of the suspension. The conductance was related to the concentration of the most highly conducting ions, i.e., the hydrogen and hydroxyl ions in the suspension. The addition of HCl was made before the start of each titration. Initially, the conductance decreased due to a neutralization of the added HCl. The additional alkali reacted with the weak acid groups bound to the fibers, causing a buffering effect. After the charge neutralization of these weak acids, further addition of the alkali raised the conductance. The resultant conductance of the suspension was (21) Lloyd, J. A.; Horne, C. W. Nord. Pulp Pap. Res. J. 1993, 8, 48-52, 67. (22) Bhardwaj, N. K.; Duong, T. D.; Nguyen, K. L. Colloids Surf., A 2004, 236, 39-44. (23) Katz, S.; Beatson, R. P.; Scallan, A. M. Svensk Papperstidning 1984, 87, R48-R53.

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plotted against the volume of the alkali added. The carboxyl content was then calculated using the volume of the alkali required to reach the second inflection point from the first inflection point of the plot. After each titration, the amount of pulp in each sample was determined gravimetrically by filtering the pulp on preweighed filter paper and drying the filtered sample in an oven at 105 °C until a constant weight was obtained. FT-IR-PAS Measurements. The FT-IR-PAS measures the absorbance in the infrared by sensing absorption-induced heating of the sample directly. The heat deposited within a certain depth of the sample is transferred to the surrounding layer of inert gas above the sample surface thereby producing a thermal expansion that generates an acoustic effect, which is detected by a sensitive microphone. The PA spectra are associated with the chemical structures at a depth below the sample’s surface from which the signal evolves. Usually, the PA spectrum is obtained by measuring the magnitude of the PA signal while varying the wavelength of the incident radiation. To eliminate the effect of the wavelengthdependent power output of the excitation source on the magnitude of the PA signal, this latter is usually normalized to a PA signal obtained under the same experimental conditions from a strongly absorbing (over the entire wavelength range) reference sample, such as for example carbon black provided by MTEC Photoacoustics Inc. This reference sample has a very low thermal mass and generates a much stronger signal than the typical samples. The carboxyl groups on the fibers were converted to their Na form by a procedure suggested by Wågberg et al.24 The washed wet pulp samples were subsequently used to produce 120 g/m2 paper handsheets using a British handsheet maker. All handsheets were air-dried in a conditioning room (23 °C and 50% relative humidity) before being tested. Paper samples of appropriate size (∼10 mm in diameter) were prepared for use with the macrosampling head of the PA cell using a hand puncher. The IR beam is focused into a 5-mm-diameter area at the center of the cup in MTEC detectors. All PAS spectra were obtained with a PerkinElmer FT-IR (GX model) spectrometer equipped with a MTEC model 300 PA cell with a macrosampling head. Prior to the PA measurement, the sample chamber was purged using clean, pure, and dry helium gas (at ∼20 psi at a flow rate of 10-20 cm3/s) during ∼20 min to provide a CO2- and moisture-free environment and to ensure reproducibility, optimize signal-to-noise ratio, and avoid spectral interferences. Likewise, helium gas was used to purge the PA cell for ∼10 s before each measurement. A successful purge increases the signal level by a factor of ∼2-3. All data was recorded at 8-cm-1 resolution and scan interval of 1 cm-1 in the 4000-750 cm-1 wavenumber range with 8-100 scans coadded. Each sample was scanned 8, 16, 32, 50, and 100 times using moving mirror velocities of 0.05, 0.1, 0.2, 0.5, and 1 cm/s, respectively. Each spectrum was replicated and the average spectrum taken. Spectrum software was used to control the spectrometer, as well as to collect and process the spectral data. RESULTS AND DISCUSSION Overall, 26 kraft pulps were evaluated. The reported test data about carboxyl content are the average from three tests. The carboxyl content declined from 131.7 to 38.4 mmol/kg as the κ (24) Wågberg, L.; O ¨ dberg, L.; Glad-Nordmark, G. Nord. Pulp Pap. Res. J. 1989, 4, 71-76.

for the quantitative determination of the carboxyl content in the pulp samples using the spectral data associated with the characteristic bands of carboxylic groups and carboxylate anions. Multivariate Data Analysis. To enhance the predictive power of multivariate calibration models, spectral data are often preprocessed prior to the analysis. Thus, all FT-IR-PAS spectra were automatically baseline corrected and then normalized to the characteristic band of cellulose (peak at 1317 cm-1) to visualize the relative changes on the spectra. For each given pulp sample, spectral intensity, Yi, was divided by the square root of the sum of the squares of all intensities in the spectrum to give a new YiI as follows: Figure 1. Carboxyl content of different P. radiata kraft pulp samples plotted as a function of κ.

decreased from 128 to 20.8. Because the carboxyl groups are associated with both lignin and hemicelluloses in wood, their content in the pulp decreases as the delignification proceeds, due to the dissolution of both lignin and hemicelluloses. The relationship between measured carboxyl contents in pulps and the corresponding κ is presented in Figure 1, where the carboxyl content is linearly correlated (R2 ) 0.97) with the κ. FT-IR-PAS Spectra. The PA spectra in the mid-infrared range (4000-800 cm-1) of three pulp samples (κ 39.6, 89.4, and 120) recorded at moving mirror velocity (V) of 0.05 cm/s are presented in Figure 2a. Various bands correspond to the major functional groups related to the chemical components of the pulp sample. As the carboxyl content increased for higher κ, the relative absorbances of bands at 1600 and 1426 cm-1 (related to the asymmetric and symmetric stretching vibrations of carboxylate anions) also increased. At higher κ, the characteristic band at 1507 cm-1 of the aromatic skeletal in lignin is clearly present with higher absorption intensity. Figure 2b features the 1800-1200 cm-1 region from Figure 2a with absorbance bands corresponding to the functional groups of the constituents. The wavenumber range 1750-1300 cm-1, selected for the PLS analysis, includes the characteristic bands25 of the carboxylic groups (1725-1700 cm-1), carboxylate (1610-1550/1420-1300 cm-1), and lignin26 (1600-1505 cm-1). The bands at 1739 and 1600 cm-1 represent the vibrations from pectin ester and carboxylate groups, respectively.7 Also, the bands in the range 1725-1710 cm-1 arise from the stretching of carboxyl carbonyl groups.27,28 The asymmetric -COO- vibration17 occurs at 1560 cm-1. The characteristics bands representing the C-H deformations29 are observed at 1466 and 1369 cm-1. The assignment of the bands7,8,17,25,27-34 in spectra of pulp is summarized in Table 1. We attempted to apply the PLS analysis (25) Coates, J. In Encyclopedia of Analytical Chemistry; Meyers, R. A., Ed.; John Wiley & Sons Ltd.: Chichester, 2000; pp 10815-10837. (26) Faix, O. In Methods in lignin chemistry; Lin, S. Y., Dence, C. W., Eds.; Springer: New York, 1992; p 93. (27) Yang, C. Q. J. Appl. Polym. Sci. 1993, 50, 2047-2053. (28) Matuana, L. M.; Balatinecz, J. J.; Sodhi, R. N. S.; Park, C. B. Wood Sci. Technol. 2001, 35, 191-201. (29) Rodrigues, J.; Faix, O.; Pereira, H. Holzforschung 1998, 52, 46-50. (30) Va´zquez, G.; Gonza´lez, J.; Freire, S.; AnTorrena, G. Holz als Roh- Werkstoff 2002, 60, 25-30. (31) Ouajai, S.; Shanks, R. A. Macromol. Biosci. 2005, 5, 124-134. (32) Fardim, P.; Duran, N. J. Braz. Chem. Soc. 2005, 16, 915-921. (33) A° kerholm, M.; Salme´n, L. J. Pulp Pap. Sci. 2002, 28, 245-249.

YiI ) Yi/

x∑

Yi2

i

Calibration is a procedure of modeling that establishes the relationship between the spectral data and sample’s property based on a selected number of experiments. In this calibration, the carboxyl content was treated as a dependent variable (Y) with spectral features from PA measurements being independent variables (X). The PLS analysis can be used to correlate the predictors (X) to the response parameters (Y), the main objective being to predict the latter from the former. The PLS regression method was used to develop a correlation between the PAS spectra and the carboxyl content in the pulp samples. A general form of the PLS model is expressed as

X ) TPT + E Y ) UQT + F where X is the variable predictor matrix (absorbance); Y is the variable response matrix (carboxyl content); T and U are the X-score and Y-score matrixes; P and Q are the X-loading and Y-loading matrixes; E and F are the X-residual and Y-residual matrixes. The coordinates of the sample in a coordinate system defined by the principal components (PCs) are called scores. The loading vectors are the bridge between the variable space and the PC space. The loadings provide the information about how much each variable contributes to each PC. In the case here, T contains information about the samples, and P contains information about the wavelengths. In the PLS analysis, the matrixes X and Y are initially column centered and normalized. The PLS algorithm chooses successive orthogonal factors that maximize the covariance between each X-score and the corresponding Y-score. To specify T and U, two sets of weights w (X-weights) and c (Y-weights) are computed to create a linear combination t ) Xw and u ) Yc with the constraints that wTw ) 1 and tTt ) 1 and the regression weight b ) tTu be maximal. The columns of T are also called the latent vectors. When the first latent vector is found, it is subtracted from both X and Y and the procedure is reiterated until X becomes a null matrix. Once the correlation is established, Y of the new sample is estimated as Y ) TBCT, where B is a diagonal matrix with b as (34) Ja¨a¨skela¨inen, A.-S.; Nuopponen, M.; Axelsson, P.; Tenhunen, M.; Lo ¨ija, M.; Vuorinen, T. J. Pulp Pap. Sci. 2003, 29, 328-331.

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Figure 2. (a) PAS-FT-IR spectra (V ) 0.05 cm/s) of different P. radiata pulp samples with κ 39.6, 89.4, and 120. (b) An enhancement of (a) in 1800-1200 cm-1 region.

diagonal elements. The detailed PLS algorithm is well described by Geladi and Kowalski.35 In this study, the Spectrum Quant+ software was used to perform the PLS analysis. In the Spectrum Quant+, the regression model for the property is refined by selecting only those factors considered to be of statistical significance in determining that property. The aim of the principal component analysis (PCA) is to express the variation in the spectral data in as few terms as possible. In this sense, it is a maximum data compression scheme, which avoids the possibility of falsely relating the spectral features to the response parameter. The factor compression cutoff point indicates the number of factors that will be retained for the multiple linear regression modeling. The coefficient of determination (R2) for the model gives the proportion of variability of the property that is described by the model. It indicates the strength of the relationship between the property values and the scores. The root-mean-square error of estimate (RMSEE) for the regression gives an indication of the quality of fit of the regression. (35) Geladi, P.; Kowalski, B. R. Anal. Chim. Acta 1986, 185, 1-17.

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Two sets of spectral data, which included the characteristic bands of the related functional groups, were collected. The first set, comprising the half of the total number of pulp samples, was integrated with a multivariate analysis to formulate a model for correlating the selected spectral information with carboxyl content of kraft pulps and to determine the appropriate number of principal components to include in our PLS model. The second set, comprising the same number of pulp samples different from those used in the calibration, was used to test the accuracy of the model. The results obtained are compared to data acquired from the same samples by means of conductometric titrations. The PLS analysis was first performed using spectral data at the moving mirror velocity of 0.05 cm/s within the wavenumber region 1750-1300 cm-1 (1700-1610 as blank). Thirteen samples were used for the calibration. In the calibration samples, it was important to include the two extremes of the data (carboxyl contents of 38.4 and 131.7 mmol/kg). The relationship between the first set of spectral data and the carboxyl content was established by the PLS analysis. The calibration equation for V )

Table 1. Assignment of Bands in Infrared Spectra of Pulp Fibers Reported from Previous Studies wavenumber, cm-1 1750-1735 1748-1729 1740 1740 1733 1725-1710 1725-1700 1660 1640 1605 1610-1550/1420-1300 1600-1505 1595, 1550, 1500 1595, 1505 1590 1563 1466, 1369 1464, 1424 1463, 1388 1430 1375 1329 1317 1315

functional group assignment

ref

carbonyl stretch peak ester carbonyl stretching vibrations from pectin ester unconjugated CdO in xylans CdO stretching of methyl ester and carboxylic in pectin stretching of carbonyl (CdO) carboxylic groups carboxylic acid HsOsH deformation vibration of adsorbed water and conjugated CdO stretching vibration antisymmetric sCOO- stretching vibrations from carboxylate groups carboxylate (carboxylic acid salt) lignin CdC of aromatic lignin aromatic skeletal vibrations in lignin carboxylate asymmetric stretching asymmetric sCOO- vibration CsH deformations CsH deformations CsH deformations cellulose CsH deformation in polysaccharides CarylsO vibrations in syringyl derivatives cellulose cellulose

8 28 7 30 31 28, 27 25 30

0.05 cm/s was found to be “estimated parameter ) 0.96 × specified parameter + 3.44”. The spectral region of interest contained a total of 350 data points used for analysis. The PLS decomposition of the X and Y matrixes resulted in three PCs. The X-variance shows the cumulative amount of spectral variance as a percentage of the total, and the Y-variance shows the cumulative amount of property (carboxyl content) variance as a percentage of the total. The method for calculation of X-variance and Y-variance is described in the Spectrum Quant+ user’s reference supplied by Perkin-Elmer. These three principal components can explain ∼98% of the variance in the X-matrix and 96% of the variance in the Y-matrix. The calibration of model was assessed by the RMSEE value for the calibration set, which was 5.6. No outliers were found in our calibration set. The model was then validated by comparing the predicted values of carboxyl content from the resultant model using the spectral data of the second set against the values of carboxyl content determined by the conductometric titrations. The equation of the trendline for the prediction was found to be “predicted value ) 1.01 × measured value”. At V ) 0.05 cm/s, regression coefficient, R2, is 0.96. The predictive ability of the model was assessed in terms of the root-mean-square error of prediction (RMSEP) for the test set, which is defined as

x

N

∑(yˆ - y )

RMSEP )

2

i

i)1

N

where yˆ is the value of the carboxyl content predicted by the model for sample i; yi is the measured carboxyl content, reference value for sample i; and N is the number of samples in the prediction set. The RMSEP values can be viewed as a measure of the standard deviation. For the predicted set, RMSEP was 5.9.

31 7 25 26 32 30 28 17 29 30 32 33 30 30 34 33

Effect of Velocity of the Moving Mirror. The effect of the velocity of the moving mirror on the obtained spectra was also investigated. Figure 3a shows the spectra of the pulp sample (κ 26.4) obtained at 0.05, 0.1, 0.2, and 0.5 cm/s velocities of the moving mirror. It was found that, for increasing velocity of the mirror, thermal diffusion length decreases according to eq 1, yielding lower intensity signals with the spectra shifted downward. The statistical data obtained in connection with the calibration and validations of the PLS models for different velocities of moving mirror are summarized in Tables 2 and 3, respectively. The factor compression cutoff point was 3, the coefficient of determination (R2) for the models was g0.96. It was noted that, at a higher velocity (1.0 cm/s) of moving mirror, R2 of prediction was 0.64. This is likely due to (i) the fact that the depth scanned is not adequate to represent the average carboxyl content in the samples or (ii) lower signal-to-noise ratio. Figure 3b represents the prediction of the carboxyl content at different velocities of the moving mirror. As the velocity of the moving mirror becomes higher, the RMSEP also increases. For V ) 1 cm/s, X-variance reduces and the PLS model can explain ∼90% of the variance in the X-matrix and 96% of the variance in the Y-matrix, but the RMSEP for the predicted set is highest. The prediction is highly accurate for velocity of the moving mirror not exceeding 0.5 cm/s. Thermal Diffusive Length and Carboxyl Content. Thermal diffusivity, R, defined as R ) kF/c (k is the thermal conductivity, F is the mass density, and c is the specific heat at constant pressure of the sample), is the parameter that characterizes the rate of heat diffusion in the sample. Sample depth probed by the PA is determined by the shorter of the thermal diffusion length µS and the optical wave decay length µβ. Equation 1 indicates that thermal diffusion length can be controlled by a proper selection of the velocity of the moving mirror. In a previous study by Lima et al.,15 the thermal diffusivity of kraft pulps was correlated with pulp brightness and their results were presented only in a graphical Analytical Chemistry, Vol. 78, No. 19, October 1, 2006

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Figure 3. (a) Effect of the velocity of the moving mirror on the spectrum of the pulp sample with κ 26.4. (b) Predicted carboxyl content of pulps for different velocities of the moving mirror. Table 2. Statistical Data Obtained in Connection with Calibration of the PLS Model

Table 3. Statistical Data Obtained in Connection with Validation of the PLS Model

V (cm/s)

calibration equation

calibration R2

PC used

RMSEE

V (cm/s)

trendline equation

trendline R2

RMSEP

0.05 0.10 0.20 0.50 1.00

y ) 0.96x + 3.44 y ) 0.96x + 3.45 y ) 0.96x + 3.52 y ) 0.97x + 2.69 y ) 0.96x + 3.62

0.96 0.96 0.96 0.97 0.96

3 3 3 3 3

5.6 5.7 5.7 4.9 5.6

0.05 0.10 0.20 0.50 1.00

y ) 1.01x y ) 1.02x y ) 1.03x y ) 0.98x y ) 1.08x

0.96 0.94 0.92 0.92 0.64

5.9 7.1 8.3 7.9 14.7

sum

y ) 0.97x + 2.88

0.97

3

5.1

sum

y ) 1.01x

0.95

6.4

form. We extracted the data from these graphical results for the estimation of the thermal diffusivity of our pulps. The estimated thermal diffusivity is plotted (Figure 4a) against the κ. It should be noted that the brightness of an unbleached kraft pulp can vary depending on process conditions, e.g., the alkali charge used. Therefore, such estimated thermal diffusivity can only be used to approximate the thermal diffusion length in this study, which was based on the range of wavenumber used in the PLS analysis associated with mainly characteristic bands of carboxylic groups and carboxylate. Reported values for thermal diffusivity of aluminum, steel, paper, and wool are 0.82, 0.037, 0.002-0.004, and 6824 Analytical Chemistry, Vol. 78, No. 19, October 1, 2006

0.000211 cm2/s.17,36 Using 0.00478 cm2/s for the estimated thermal diffusivity of pulp sample with κ 23.7, one has calculated (eq 1) the penetration (see Figure 4b). The PLS models were used to predict the carboxyl content in different layers; this latter is plotted (Figure 4c) against the mean of estimated depths at 1300 and 1750 cm-1 wavenumbers. The results confirm that the depth variation of carboxyl content in the pulp with κ 23.7 is insignificant whenever the estimated depth exceeds 10 µm, suggesting that the method is sufficiently accurate (36) Simula, S. Pap. Puu 1998, 80, 95.

Figure 5. Total carboxyl content: predicted (PLS) versus measured data.

carboxyl content distribution varied with depth, taking the sum of all spectra measured at different mirror velocities is essential for the calibration and prediction of the carboxyl content in the pulps. Using this approach, the PLS model can explain ∼98.5% of the variance in the X-matrix and 96.8% of the variance in the Y-matrix. Also, the RMSEE value is reduced to 5.1 and the RMSEP value for the predicted set is reduced to 6.4. The regression coefficient of the prediction, R2, was 0.95 as shown in Figure 5. The produced PLS model can be used to predict the concentration of the carboxyl groups in the unbleached kraft fibers with small errors, which may be due to the variation of the concentration of non-carboxyl carbonyl groups in these fibers. It is most likely that when the fibers are subjected to different chemical treatments, including bleaching, the concentration of these groups in the treated pulps could vary significantly resulting in larger errors.

Figure 4. (a) Correlation between κ and brightness as well as the estimated thermal diffusivity of the kraft pulps. (b) Thermal diffusion depth calculated from the estimated thermal diffusivity (4.78 × 10-3 cm2/s) of the kraft pulp at varying velocity of the moving mirror. (c) Depth-dependent profile of carboxyl content below the surface of pulp sample (carboxyl content 104 mmol/kg).

only when the velocity of the mirror is e0.5 cm/s. It should be noted that the radiata pine pulp, which was used in this study, had long fibers (2-4 mm) of diameter 0.02-0.03 mm with mean diameter ∼0.025 mm. The ranges of the PAS penetration depth, 0.008-0.010 (∼32-40% of mean diameter of fiber) and 0.0120.014 mm (about 48-56% of mean diameter of fiber), corresponded to the moving mirror velocities of 1 and 0.5 cm/s, respectively. These depths were substantially higher than the typical depth that could be penetrated by the high molecular weight polymers typically used in the measurement of fiber surface charge. As the

CONCLUSIONS The experimental results showed that the carboxyl groups dissolved during kraft pulping and the carboxyl content in the pulp samples correlate linearly with κ. This study describes how to establish the PLS model that correlates the FT-IR-PAS spectral data in the 1750-1300 cm-1 region with the carboxyl content in unbleached kraft pulps. The predicted values compare very well with the measured data. The method can be used to determine the carboxyl content as well as the carboxyl content profile in pulp handsheets. The pronounced advantages of the PA approach above the conventional titration methods are its unique ability to directly predict the carboxyl content using paper handsheets and being nondestructive to the pulp sample. ACKNOWLEDGMENT N.K.B. and V.Q.D. acknowledge Monash University for the award of scholarships. Received for review March 31, 2006. Accepted July 19, 2006. AC0605952

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