Thermokinetic investigation of cellulose pyrolysis impact of initial and final mass on kinetic results

Journal of Analytical and Applied Pyrolysis 62 (2002) 165 177 www.elsevier.com/locate/jaap Thermokinetic investigation of cellulose pyrolysis impact of initial and final mass on kinetic results S. Völker a, *, Th. Rieckmann b a 42 Engineering, on-behring-str. 9, D-34260 Kaufungen, Germany b Department of Chemical Engineering and Plant Design, Uni ersity of Applied Sciences Cologne, Betzdorfer Str. 2, D-50679 Cologne, Germany Received 14 April 2000; accepted 27 December 2000 Abstract Cellulose pyrolysis has been investigated by combined TGA/DTA applying constant heating rates between 0.14 and 105 K min 1. The experiments entailed variation of initial mass and initial bulk density of the cellulose samples. The final mass depended on the heating rate as well as on the initial mass and bulk density and was reproducible when these parameters were carefully controlled. Mass transport resistance is a dominating factor increasing the char yield even in samples of 1 mg significantly at all heating rates. At higher initial sample masses, the char yield is determined by meshed heat and mass transport phenomena. Exothermic secondary reactions form additional char and change the overall heat of reaction. The heat released by secondary reactions promotes the volatilization of primary tars which in turn reduces the char yield. Fitting global reaction models to the experimental TGA results assuming a single first-order reaction yielded apparent kinetic parameters which were strongly correlated, but varied in a broad range depending in a complicated manner on heating rate and initial sample mass. This, together with the inherent impossibility to predict changes in product distribution, results in the restricted applicability of a single first-order reaction as predictive model for reactor analysis and design. Multi-step models with a modified Broido-Shafizadeh mechanism are more successful in describing experimental results for small sample masses. Nevertheless, they can not be extended to conditions under which secondary char is formed due to the lack of kinetic data in the literature. 2002 Elsevier Science B.V. All rights reserved. Keywords: Pyrolysis; Cellulose; TGA/DTA; Char yield; Kinetics; Heat and mass transport; Modelling * Corresponding author. Tel.: +49-5605-925114; fax: +49-5605-925112. E-mail address: susanne.voelker@42engineering.de (S. Völker). 0165-2370/02/$ - see front matter 2002 Elsevier Science B.V. All rights reserved. PII: S0165-2370(01)00113-9

166 S. Völker, Th. Rieckmann / J. Anal. Appl. Pyrolysis 62 (2002) 165 177 1. Introduction The growing interest in renewable energies is accompanied by intensified research and development of technical processes for the thermal conversion of biomass. Plant design and scale-up bases on process simulation which needs reliable reaction models for the desired operation conditions. Cellulose is a main constituent of biomass and as a model compound its pyrolysis behaviour has gained attention for many years. Despite the numerous investigations, the biomass community is still debating the best global reaction model and kinetic parameters for the primary thermal decomposition of cellulose. Experiments were performed using thermogravimetric analysis with low to moderate heating rates (0.5 100 K min 1 )as well as devices for very rapid heating (up to several 1000 K min 1 ), resulting in considerable differences in final char yields and calculated kinetic parameters. Cellulose pyrolysis was described by one-step first order models postulating or rejecting a change of the rate limiting reaction step going from low to high heating rates, as well as by multi-step models of the Broido-Shafizadeh type with competitive reactions leading to volatiles and primary char [1 7]. Recently, Grønli et al. published the results of a round-robin study of cellulose pyrolysis kinetics by thermogravimetry [8]. Regarding experiments at a heating rate of5kmin 1, the authors state in this paper: Note that the values of m last /m 0 span a range of 4.0 10.9%. Obviously, the measurement of the very small Avicel char residue by thermogravimetry lacks precision. This inspired us to take a deeper look into the influence of experimental conditions on final char yields in thermogravimetric analysis. We wanted to check whether thermogravimetry is able to give reliable char yields and to which extent these are determined by heat and mass transport. As the char yield is an important parameter for process optimization, we intended to investigate the influence of the final mass on modelling results and to evaluate the applicability of established kinetic models for engineering purposes. 2. Experimental 2.1. Thermogra imetric analysis Combined TGA/DTA experiments have been performed using an STA 503 (Bähr GmbH, Altendorfer Str. 12, D-32609 Hüllhorst). The maximum load of the STA is 1000 mg, and mass variations of 200 mg can be detected. The mass resolution is 1 g. The STA apparatus has a horizontal weighing beam which generates an unusually low drag in the weighing direction, and the effect of drag was further reduced by using high purity helium (99.999%, Linde) as a low viscosity purge gas with a gas flow rate of 1.7 l h 1. Open crucibles made from Al 2 O 3 have been used in all experiments. The thermocouples measuring the sample temperature and the reference temperature, respectively are integrated in the sample holder and are

S. Völker, Th. Rieckmann / J. Anal. Appl. Pyrolysis 62 (2002) 165 177 167 located directly beneath the platinum plates under the crucibles. This configuration provides an intense and reproducible thermal coupling to the sample. A temperature calibration has been performed for all heating rates by analyzing the DTA signal from the melting peak of the pure substances Indium (T m =429.8 K); KClO 4 (T m =572.6 K); and Ag 2 SO 4 (T m =699.6 K), using the same crucibles and conditions as in the experimental runs. The corrected sample temperatures T from the thermogravimetric analyses are the most accurate representation of the sample temperature (low sample mass) or the sample surface temperature (high sample mass), respectively. The linearity of the T(t) curves was excellent for all heating rates. Linear regression of the T(t) curves to estimate the individual heating rate for each experiment resulted in correlation coefficients between 0.999998 for =0.14 K min 1 and m 0 =3.3 mg and 0.999294 for =105 K min 1 and m 0 =54 mg. The experiments have been performed with microcrystalline cellulose (Avicel, Merck) and entailed variation of the heating rate, the initial sample mass m 0, and the initial bulk density 0 of the cellulose sample. Initial sample masses of 1, 3, 20, 37 and 54 mg have been investigated at constant heating rates of 0.14, 3, 41 and 105 K min 1. The cellulose samples were filled in the sample pan which was slightly tapped afterwards, resulting in an approximate initial bulk density of the cellulose of 400 kg m 3. Additionally, the experiments were repeated with cellulose samples which had been compressed to an initial bulk density of approximately 550 kg m 3 using a piston onto which a weight of 1 kg had been placed. All samples were dried 1.5 h at 381 K in a helium stream at the beginning of the experiments. 2.2. Calculation of kinetic parameters Formal kinetic models have been calculated to describe the experimental mass loss of the cellulose samples. The material balance of the crucible contents was described as a dynamic system with concentrated parameters which resulted in a single or a set of ordinary differential equations (ODE), respectively. The corrected sample temperature T was used for the time/temperature integration at a constant heating rate which was calculated from the experimental data. The simultaneous numerical solution of the ODE system and the estimation of the kinetic parameters by the least squares (LSQ) method were performed using Thermokinetics (Netzsch GmbH). Netzsch Thermokinetics is a software module for the evaluation of thermokinetic experiments and allows the calculation of kinetic parameters by analyzing single experiments as well as by applying the multivariate regression technique [9]. Model predictions for the comparison of different kinetic models were calculated using Matlab (The MathWorks, Inc.). 3. Results and discussion Our investigations confirmed a very good reproducibility of the final mass, provided that the initial sample mass and bulk density were carefully controlled.

168 S. Völker, Th. Rieckmann / J. Anal. Appl. Pyrolysis 62 (2002) 165 177 Fig. 1. TGA results at =3 Kmin 1 for m 0 =1, 3, 20 and 54 mg with 0 =400 kg m 3 ( ) and 0 =550 kg m 3 (- - -), respectively. Included is an experiment at =0.14 K min 1 with m 0 =3 mg and 0 =400 kg m 3 (- - - -). The experimental TGA results for heating rates of 0.14, 3, 41 and 105 K min 1 are displayed in Figs. 1 3. The corresponding DTG curves are shown in Figs. 4 6. At a heating rate of 3 K min 1, all cellulose samples decompose in a narrow temperature range. The DTG curves show temperatures between 593 and 595 K for the maximum decomposition rate without dependency on m 0 and almost no variation of the curve form for different initial sample masses. A clear trend can be seen within the TGA curves with final masses varying between 2 and 18% of m 0 at 800 K. As expected, the final mass increases with the initial sample mass due to mass transport effects which can also be enhanced by increasing the initial bulk density of the sample. Therefore, experiments with a higher initial bulk density always yielded a higher final mass. The influence of bulk density is most pronounced for small initial sample masses (1 and 3 mg), doubling the char yield at 800 Fig. 2. TGA results at =41 K min 1 for m 0 =1, 3, 20 and 54 mg with 0 =400 kg m 3 ( ) and 0 =550 kg m 3 (- - -), respectively.

S. Völker, Th. Rieckmann / J. Anal. Appl. Pyrolysis 62 (2002) 165 177 169 Fig. 3. TGA results at =105 K min 1 for m 0 =1, 3, 20 and 54 mg with 0 =400 kg m 3 ( ) and 0 =550 kg m 3 (- - -), respectively. K. This is of special interest as experimental conditions comprising low sample masses and low heating rates are usually assumed to minimize the influence of heat and mass transport [6]. Lowering the heating rate for a sample with m 0 =3 mg and 0 =400 kg m 3 from 3 to 0.14 K min 1 resulted in a doubled char yield at 700 K. This confirms the general assumption that more char is formed at lower heating rates. The experiments at a heating rate of 41 K min 1 show the presence of heat transport limitations through shifting temperatures for the maximum decomposition rate from 634 to 651 K with increasing initial sample mass. The experimental results can be divided into two groups. The first group contains initial sample masses of 1 and 3 mg. The behaviour of these samples is similar to that at a heating rate of 3 K min 1 with final masses increasing with m 0 and 0. Interestingly, char Fig. 4. DTG results at =3 Kmin 1 for m 0 = 1, 3, 20 and 54 mg with 0 =400 kg m 3 ( ) and 0 =550 kg m 3 (- - -), respectively. The original DTG values have been multiplied by 10 for m 0 =1mg, by 8 for m 0 =3mg and by 2 for m 0 =20 mg.

170 S. Völker, Th. Rieckmann / J. Anal. Appl. Pyrolysis 62 (2002) 165 177 Fig. 5. DTG results at =41 K min 1 for m 0 =1, 3, 20 and 54 mg with 0 =400 kg m 3 ( ) and 0 =550 kg m 3 (- - -), respectively. The original DTG values have been multiplied by 5 for m 0 =1 and 3 mg and by 1.5 for m 0 =20 mg. yields for samples with identical m 0 and 0 are higher at =41Kmin 1 than at =3 Kmin 1. This contradicts the assumption of decreasing char yields with increasing heating rates. The second group contains initial sample masses of 20 and 54 mg. For this group, the onset of decomposition is delayed due to heat transport limitations. This delay is slightly reduced by compressing the sample which leads to a higher heat conductivity. Conversely to the first group, a higher initial bulk density leads to equal or lower char yields. The char yields of samples with m 0 =20 and 54 mg are nearly the same at =41 K min 1 as at =3 Kmin 1. Another interesting feature can be seen within the DTG results. Whereas the curves for the samples with m 0 up to 20 mg display the usual form, the curve for m 0 =54 mg and 0 =400 kg m 3 has a shoulder and the curve for m 0 =54 mg and 0 =550 kg m 3 splits into several peaks and shoulders. Fig. 6. DTG results at =105 K min 1 for m 0 =1, 3, 20 and 54 mg with 0 =400 kg m 3 ( ) and 0 =550 kg m 3 (- - -), respectively. The original DTG values have been multiplied by 5 for m 0 =1mg, by 4 for m 0 =3 mg and by 1.3 for m 0 =20 mg.

S. Völker, Th. Rieckmann / J. Anal. Appl. Pyrolysis 62 (2002) 165 177 171 Fig. 7. DTG (- - -) and DTA ( ) results at =105 K min 1 for m 0 =3, 37 and 54 mg with 0 =550 kg m 3. The experimental results at a heating rate of 105 K min 1 show the same characteristics as those at a heating rate of 41 K min 1. Again the curves for m 0 =1 and 3 mg lie very close together and the same trend of char yields is observed as at the lower heating rates. The char yields for m 0 =1and3mgand =105 K min 1 are comparable to those at =3 K min 1. The curves for m 0 =20 and 54 mg are shifted to higher decomposition temperatures and the effects of heat and mass transport are further pronounced. In Fig. 7, DTA results together with DTG curves are shown for =105 K min 1 and m 0 =3, 37 and 54 mg with 0 =550 kg m 3. In this figure, the influence of secondary cracking on the total reaction enthalpy can be studied. For an initial sample mass of 3 mg, the DTA signal follows the form of the DTG curve and the whole reaction is strongly endothermic. The DTG curve for 37 mg splits into two peaks. The DTA signal reveals that the first peak is accompanied by exothermic reactions whereas the second peak is dominated by endothermic reactions. For an initial sample mass of 54 mg, the DTG curve splits into three distinguishable peaks. The contribution of the individual reactions changed with the right and left peaks being the same as those in the 37 mg signal and the central peak evolving from a shoulder seen at 37 mg. Only the peak at the highest temperature is dominated by endothermic reactions. It seems that mass transport resistance leads to the domination of exothermic secondary reactions until the sample layer is sufficiently thin or the void fraction is sufficiently large to allow the escape of primary vapours before pronounced secondary cracking occurs. Therefore, the overall reaction enthalpy decreases significantly with enhanced mass transport resistance. This, as well as the earlier onset of reaction is in accordance with findings of Mok et al. [10] who investigated the formation of charcoal in a

172 S. Völker, Th. Rieckmann / J. Anal. Appl. Pyrolysis 62 (2002) 165 177 sealed reactor. The decreasing char yield with the onset of exothermic reactions in our experiments might result from the fact that we worked with an open system and the heat provided by these reactions compensated the heat demands of volatizing tars. At high heating rates, large samples will not have a homogeneous temperature due to heat transport limitations and a part of the exothermic heat of reaction may not be seen in the DTA signal. A quantitative estimation of the total heat of reaction would therefore require a comprehensive mathematical model including reaction, heat transport, and mass transport. Since the thermogravimetrically determined final mass exhibited a systematic behaviour with experimental conditions, we wanted to check how this influences the results of kinetic analyses. Kinetic analysis of our TGA results has been performed by a least squares analysis assuming a single irreversible first-order reaction with the rate equation d dt =k(1 ), where =1 (m(t) m f )/(m 0 m f ), k=k 0 exp( E a /(RT)), m(t) is the time-dependent sample mass, m f is the final sample mass, m 0 is the initial dry sample mass, k 0 is the pre-exponential factor, E a is the apparent activation energy, R is the ideal gas constant, and T is the corrected sample temperature. For every single experiment, apparent kinetic parameters E a and log(k/s 1 ) have been calculated. Due to the slow carbonization of the primary char, m f varies not only with the experimental conditions but also with the final temperature up to which the data are considered for the kinetic analysis. Therefore, each experiment has been evaluated twice. The first evaluation ( narrow temperature interval ) was performed using the data up to the temperature at which the primary pyrolysis was finished. The definition of this temperature is somewhat ambiguous, we used a final temperature shortly after the last bending of the TGA curve (i.e. 630 K for the experiments at =3 K min 1 ). The second evaluation ( wide temperature interval ) was performed using the data up to a final temperature which was 100 K higher than the final temperature in the first evaluation of the experiment. The results of the kinetic analyses are displayed in Fig. 8. The apparent kinetic parameters spread over a wide range. Activation energies between 132 and 241 kj mol 1 were calculated for 0 =400 kg m 3 and between 104 and 245 kj mol 1 for 0 =550 kg m 3. The resulting kinetic parameters are always lower when the kinetic analysis is performed with data comprising a higher final temperature. This might be due to a change in the dominating reaction mechanism at higher temperatures. Despite their great variance, the kinetic parameters are strongly coupled due to the well known compensation effect [11]. For engineering purposes, models often have to be chosen a priori. To check, whether the choice of an appropriate pair of E a and log(k/s 1 ) for the desired operation conditions can be facilitated, the dependencies of E a on experimental conditions have been investigated. Fig. 9 displays E a as function of for all performed experiments.

S. Völker, Th. Rieckmann / J. Anal. Appl. Pyrolysis 62 (2002) 165 177 173 Fig. 8. Kinetic parameters E a and log(k/s 1 ) for best representations of all performed experiments by single first-order reactions. For each experiment, two temperature intervals with lower ( narrow, filled symbols) and higher final temperature ( wide, open symbols) have been analyzed. Although some trend can be seen, the scatter of data is too large to allow the a priori choice of an appropriate parameter combination, especially at higher heating rates. As E a decreases with increasing heating rate and increasing initial sample mass, the dependency of E a on a parameter m 0 has been investigated. This parameter can be interpreted as a pseudo-parameter for increasing heat and/or mass transport restrictions. The results are shown in Fig. 10. Fig. 9. Dependency of the activation energy E a for best representations of all performed experiments by single first-order reactions on heating rate. For each experiment, two temperature intervals with lower ( narrow, filled symbols) and higher final temperature ( wide, open symbols) have been analyzed. Data for different initial bulk densities are displayed with the same symbol but different shading.

174 S. Völker, Th. Rieckmann / J. Anal. Appl. Pyrolysis 62 (2002) 165 177 Fig. 10. Dependency of the activation energy E a for best representations of all performed experiments by single first-order reactions on the parameter m 0. For each experiment, two temperature intervals with lower ( narrow, filled symbols) and higher final temperature ( wide, open symbols) have been analyzed. The scatter of data is somewhat reduced and a clear trend becomes visible. The values for E a converge for conditions with reduced influence of heat and mass transport effects and under these conditions a valid reaction model could be chosen. The situation is worse for higher mass loads and heating rates and it seems to be impossible to choose a model without deeper knowledge of heat and mass transport characteristics of the reaction system. The uncertainty regarding the best pair of kinetic parameters might be overcome by the approach of fixing E a to a high value and varying log(k/s 1 ) to account for heat transfer limitations [8]. This approach has been tested with our experimental results for the lowest initial sample masses with 0 =400 kg m 3 measured at the respective heating rates. The results are shown in Fig. 11. The value of E a was chosen according to [8] and log(k/s 1 ) values were determined from the regression of the experiments with the lowest and the highest heating rate, respectively. The resulting difference in log(k/s 1 ) values was 1.0, equivalent to a 10-fold difference in reaction rates at a given temperature. Additionally, it should be noted that the model optimized for =0.14 K min 1 does not fit the experiment at =3 Kmin 1, meaning that the experimental data at =3 K min 1 would already be affected by some kind of transport limitation. The major drawback for the application of this model type for process optimization is its inherent inability to predict shifts in product yields with differing heating rates. To account for this observation, different models with competing reactions leading to either tar or to char+gas have been developed [6]. Two of these models have been tested for our experimental results and are displayed in Fig. 12.

S. Völker, Th. Rieckmann / J. Anal. Appl. Pyrolysis 62 (2002) 165 177 175 The first model contains the well-known Broido Shafizadeh mechanism with an activation step and two competing following reactions. The kinetic parameters were taken from Bradbury et al. [12]. The second model contains a modified Broido Shafizadeh mechanism in which the activation step had been omitted. The kinetic parameters were taken from Várhegyi et al. [2]. Although the predicted decomposition temperatures are mostly too high, the pyrolysis behaviour of small cellulose samples can be described with more accuracy by multi-step models than by single-step models using one set of kinetic parameters for all heating rates. The modified Broido Shafizadeh mechanism yields better results, especially regarding the onset of reaction. The lower final char yields of this model are probably due to the fact that it was developed using very small sample masses. Interestingly, a modified Broido-Shafizadeh mechanism is also suitable for the description of cellulose pyrolysis at high heating rates with careful minimization of heat and mass transport [13]. 4. Conclusions Our investigations confirmed that the final mass of cellulose samples after pyrolysis is reproducible, provided that the initial sample mass and the initial bulk density are carefully controlled. The variance in final mass induced by altering Fig. 11. Comparison of established single-step models for cellulose pyrolysis with our experimental TGA results for small samples with 0 =400 kg m 3 at different heating rates. Kinetic model parameters are E a =244 kj mol 1 with log(k/s 1 )=19.2 ( ), and E a =244 kj mol 1 with log(k/s 1 )=18.2 (---). The final mass was fixed to the mean of the experimental results.

176 S. Völker, Th. Rieckmann / J. Anal. Appl. Pyrolysis 62 (2002) 165 177 Fig. 12. Comparison of established multi-step models for cellulose pyrolysis with our experimental TGA results for small samples with 0 =400 kg m 3 at different heating rates. Kinetic model parameters for the Broido Shafizadeh mechanism ( ) were taken from [12] and for the modified Broido-Shafizadeh mechanism (- - -) from [2]. the initial bulk density is sufficiently large to be responsible for the different char yields found in the round-robin study by Grønli et al. [8]. Besides heat transport, mass transport is a very important parameter in the thermal decomposition of cellulose and has to be considered even for very low initial sample masses. Mass transport restrictions alter not only the char yield due to char forming secondary reactions but also the overall heat of reaction due to the exothermic nature of the secondary reactions. In case of heat transport limitations, the heat released by secondary reactions promotes the volatilization of primary tars which in turn reduces the char yield. Therefore, the dependency of char yield on mass transport is strongly non-linear. The rate of thermal decomposition of cellulose can be predicted for small initial sample masses at all heating rates and for higher initial sample masses at low heating rates with sufficient accuracy using a modified Broido-Shafizadeh mechanism. The prediction of product yields remains a problem due to mass transport effects which seemingly have to be considered in all technically relevant systems. Established models of cellulose pyrolysis can only calculate constant char yields for a given temperature time history because no parameters are available in the literature for char forming secondary reactions. This implies a special need of research on mass transfer and diffusion parameters of volatiles from biomass pyrolysis as well as on primary and secondary char forming processes.

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