Energy & Fuels 1989,3, 329-335 2216-69-5;a-tetralone, 529-34-0;1,2,3,4,5,6,7,8-octahydronaphthalen-1-one,18631-96-4;decahydronaphthalene,91-17-8; 1-hydroxynaphthalene,90-15-3; 9H-xanthene,92-83-1;methyl1,l'-bicyclohexyl, 3178-23-2; dibenzofuran, 132-64-9; 1,2,3,4,6,7,8,9-dydrodibenzofuran,1010.77-1;1,l'-bicyclohexyl, tetradecahydroanthracene,6596-35-6; 92-51-3;anthrone,90-44-8; 9-hydroxy-1,2,3,4,5,6,7,8-octahydroanthracene, 110836-01-6; 1,2,3,4,4a,5,6,7,8,9a-decahydroanthracen-9-one, 119529-50-9;anthraquinone, 84-65-1;carbazole, 86-74-8;1,2,3,4-tetrahydrocarbazole,942-01-8;1,2,3,4,5,6,7,&dydrdahydrocarbazole,26727-32-2; 1,2,3,4,4a,9a-hexahydrocarbazole, 1775-86-6;quinoline,91-22-5;
329
1,2,3,4-tetrahydroquhohe, 635-46-1;5,6,7,&tetrahydroquholine, 10500-57-9; 2-aminonaphthalene,91-59-8;1,2,3,4-tetrahydro-6aminonaphthalene,2217-43-8;benzene, 71-43-2;cyclohexane, 110-82-7; naphthalene,91-20-3;1-methylnaphthalene,90-12-0; decahydro-1-methylnaphthalene,2958-75-0;1,2,3,4-tetrahydro5-methylnaphthalene,2809-64-5;2-methylnaphthalene,91-57-6; 1,2,3,4-tetrahydrc-6-methylnaphthalene, 1680-51-9;phenanthrene, 85-01-8;1,2,3,4,5,6,7,8-octahydrophenanthrene, 5325-97-3;anthracene, 120-12-7; 9,10-dihydroanthracene, 613-31-0; 1,2,3,4,5,6,7,8-octahydroanthracene, 1079-71-6; 1,2,3,4,4a,9,9a,lO-octahydroanthracene, 7389-11-9.
Kinetics of the Thermal Decomposition of Cellulose, Hemicellulose, and Sugar Cane Bagasse Gabor Varhegyif and Michael J. Antal, Jr.* Department of Mechanical Engineering and the Hawaii Natural Energy Institute, University of Hawaii, Honolulu, Hawaii 96822
Tamas Szekely and Piroska Szabo Research Laboratory for Inorganic Chemistry, Hungarian Academy of Sciences, P. 0. Box 132, Budapest 1502, Hungary Received September 19, 1988. Revised Manuscript Received February 10, 1989
Nonisothermal thermogravimetric experiments using Avicel cellulose, 4-methyl-Pglucurono-D-xylan, and sugar cane bagasse in the presence and absence of catalysts (inorganicsalts) were subject to kinetic evaluation by the method of least squares. Five different mathematical models were employed. These were based on the assumption of (1)a single first-order reaction, (2) a chain of successive reactions, (3) competitive reactions, (4)independent parallel reactions, and (5) a combination of two successive reactions and a separate independent reaction. The choice between which of these models offered the best fit was based partly on chemical considerations and partly on the quality of the fit. The resulting activation energies and preexponential factors had chemically meaningful magnitudes and helped to confirm or reject various hypotheses on the catalyzed and uncatalyzed reaction mechanisms of lignocellulose decomposition.
Introduction In previous papers, we dealt with the thermal decomposition of Avicel cellulose' and sugar cane bagasse2in the presence and absence of catalysts. A separate papeI-3 dealt with the thermal decomposition of a hemicellulose (4methyl-D-glucurono-D-xylan).Here a kinetic analysis of the same experiments will be given. The aim of the present work was to gain further insight into the factors governing the thermal behavior of lignocellulose materials. Numerous papers have dealt with these questions. For recent detailed reviews, see the reviews of Anta14 and Agra~al.~ Here only a brief overview will be given. Cellulose decomposition takes place through a reaction network consisting of parallel and competitive reactions.&' Nevertheless, the common experience is that the overall reaction can be well described by a single first-order reaction. AgrawaP lists 16 papers that describe cellulose decomposition by using a first-order reaction. This fact may be due to the rate-controlling role of one of the reactions in the reaction network.
* To whom correspondence should be addressed. Visiting Scientist from the Hungarian Academy of Sciences.
Considerably fewer papers deal with the decomposition of the various hemicellulose materials. Hemicellulose decomposition is usually described by a first-order react i ~ n . ~Ward ? ~ and Braslaw"' assumed a chain of consecutive reactions, while Bar-Gadda'l chose a model composed from nucleation, growth of nuclei, and a diffusion-controlled decay. (1)Varhegyi, G.; Antal, M. J., Jr.; Szekely, T.; Till, F.; Jakab, E. Energy Fuels 1988,2,267-272.
(2)Vafhegyi, G.;Antal, M. J., Jr.; Szekely, T.; Till, F.; Jakab, E.; Szabo, P. Energy Fuels 1988,2,273-277. (3)Simkovic, I.; Varhegyi, G.; Antal, M. J., Jr.; Ebringerova, A.; Szekely, T.; Szabo, P. J. Appl. Polym. Sci. 1988,36, 721-728. (4)Antal, M. J., Jr. In Advances in Solar Energy; Boer, K. W.; Duffer, J. A., Eds.; Plenum: New York, 1985,uol. 2,pp 175-255. (5)Apawal, R. K. Kinetics of Biomass and Coal Pyrolysis. Ph.D. Thesis, Clarkson University, Potadam, NY, 1984. (6)Shafizadeh, F.In Cellulose Chemistry and its Applications; Nevell, T. P., Zeronian, S. H., Eds.; Wilew: New York, 1985;pp 266-290. (7)Broido, A. In Thermal Uses and Properties of Carbohydrates and Lignins; Shafizadeh, F., Sarkanen, K., Tillman, D. A., Eds.; Academic: New York, 1976;pp 19-36. (8)Ramiah, M. J. Appl. Polym. Sci. 1970,14,1323-1337. (9)Min, K. Combust. Flame 1977,30, 285-294. (10)Ward, S. M.; Braslaw, J. Combust. Flame 1985,61,261-269. (11)Bar-Gadda, R. Thermochim. Acta 1980,42,153-163.
0887-0624/89/2503-0329$01.50/00 1989 American Chemical Society
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330 Energy & Fuels, Vol. 3, No. 3, 1989
For the decomposition of whole lignocellulose materials (usually various woods), two type of models have been applied. The first approach is a formal description in which separate competitive reactions are assumed to describe the product distribution, but the chemical inhomogeneity of the wood is not taken into a ~ c o u n t . ' ~ ~In' ~ the second approach, the decomposition of a lignocellulose material is assumed to be the sum of the decomposition of its comp~nents.~*'~ This latter approach is the mathematical expression of the hypothesis of Shafizadeh and McGinnis14 concerning the independence of the decomposition of major components in a lignocellulose material.
Experimental Section The instrumentation, samples, and sample preparation were described in detail in the preceding papers.'-3 The thermogravimetric signal was provided by a Perkin-Elmer TGS-2 thermobalance. The DTG curves were numerically calculated from the TG data obtained in a computerized data acquisition process. Low sample masaes (1-2 mg) and an open platinum plate were applied. When it is not stated otherwise in the discussion, the kinetic evaluations belong to experiments that employ a 10 OC/min heating rate. The simultaneously measured mass spectrometric c u ~ v e s l -were ~ not considered sufficiently exact for kinetic calculations since the product tar changed the effective diameter of the capillary during the measurements and added some extra "background" to the mass spectrometric data at higher temperatures. Though these effects were relatively low, the DTG curves appeared to be more suitable for least-squares calculations. The reliability of the DTG data was carefully tested.' The kinetic calculations were carried out by an IBM AT personal computer equipped with a mathematical coprocessor. The programs were written in Fortran. The algorithms applied will be described in a separate section. Pure microcrystalline Avicel cellulose,' bagasse obtained in pelletized form from the Hamauka Sugar Co., Honolulu, HI: and 4methyl-~-glucurono-~-xyh prepared from beech sawdust3were studied. Prior to the experiments, the bagasse pellets were ground in a ball mill and dried in a desiccator at room temperature. Part of the experiments was carried out with inorganic catalysts (NaCl, FeSO,, and ZnC12)added from dilute solution to the cellulose and bagasse The concentrations were chosen so that one cation was added per 100 monomer units of cellulose in the Avicel experiments. The resulting weight percentages of NaCl, FeSO,, and ZnC12 in the dry Avicel and bagasse samples were 0.36,0.94, and 0.84%, respectively.
Kinetic Models In this section, the fundamental considerations we applied in the kinetic evaluation of the thermogravimetric data will be briefly outlined. From a theoretical point of view, an endless variety and complexity of reactions forming a network can be assumed in biomass pyrolysis. In practice, however, the DTG curves we observed were simple and could be described by relatively simple models. Reverse reactions were excluded from the models since experiments with closed sample holders did not show their presence. In this way the following simple reaction kinetic models were applied. Single Reaction Model. The most frequently applied model in the field of nonisothermal reaction kinetics is the equation d a / d t = A exp(-E/RT) (1- a)" where a is the conversion (reacted fraction) of the original (12) Shafkadeh, F.;Chin, P. P. S. ACS Symp. Ser. 1977, No. 43 57-71. (13) Thurner, F.;Mann, U. Ind. Eng. Chem. Process Des. Deu. 1981, 20,4a2-4aa. (14) Shafizadeh, F.; McGinnis, G. D. Carbohydr. Res. 1971, 16, 273-211.
substance. If the quotient of the actual sample mass and the initial sample mass is denoted by m and mch stands for the relative char yield, then a is defined as a = (1- m)/(l - mCh)
(2)
The physical meaning of eq 1has been discussed in detail in a recent review.15 For a solid-state organic decomposition, the most plausible approach seems to be the assumption of a kinetic model built of first-order elementary reactions. Second-order reactions are obviously hindered in the solid phase. The assumption of a surface reaction requires some special physical or chemical reasons to explain why the reaction should have a considerably higher rate on surfaces than in the other parts of the sample. Note that the presence of the volatile decomposition products does not decrease the decomposition rate of the lignocellulosic materials,'P2 hence, the decomposition products cannot suppress the decomposition in the bulk of the sample. Independent Parallel Reactions. If the sample consists of more than one chemical component and each component decomposes independently from the others, then we can define a separate conversion (reacted fraction) ai for each component and write dai/dt = Aiexp(-Ei/RT) (1 - ai)"i
i = 1, 2,
...
(3)
If the contribution of component i to the mass loss is ci, we have -dm/dt =
Cci dai/dt
(4)
Here ci is the relative amount of component i in the sample multiplied by the amount of volatiles formed from a unit mass of that component. The primary use of this model is the (approximate) description of the thermal decomposition of mixtures. However, this model may describe the catalytic decomposition of a one-component sample, too, if we assume that the catalyst has direct contact only with a part of the sample or only with selected parts of the molecules composing the sample and the rest of the sample remains unchanged. If this assumption is valid, we have separate equations for the pure part of the sample and the part that is in contact with the catlayst. Competitive Reactions. If a given molecule can react in more than one way, we may attempt to describe the process by da/dt = E A i exp(-Ei/RT) (1 - a)"i
(5)
where a is the reacted fraction of the original substance and Ai, Ei, and ni are the kinetic constants of the ith partial reaction. Note that the char yields of the individual partial reactions may be different; hence, the relationship between a and m is more complicated here than in the case of a single reaction: -dm/dt = CciAi exp(-Ei/RT) (1- a)"i
(6)
From a theoretical point of view, an organic macromolecule can always be decomposed through more than one reaction. However, relatively small differences in the activation energy of the partial reactions can lead to the dominance of one of the reactions. Successive Reactions. In case of successive (consecutive) reactions we cannot describe the amount of the intermediate species by reacted fractions (ai). Hence, we shall introduce the variables mi, which are the masses of (15) Pokol, G.; Varhegyi, G. CRC Crit. Rev. Anal. Chem. 1988, 19, 65-93.
Kinetics of Thermal Decomposition
Energy & Fuels, Vol. 3, No. 3, 1989 331
-dm/dt
-dm/dt
1
A
250
300
350
250
400°C
Figure 1. Avicel + NaCl evaluation by the model of competitive reactions. In all figures, dots, the bold solid line, and thin solid lines represent the experimental data (-dm*/dt), the calculated data (-dm&/dt) and the contributions of the partial reactions to -dm*c/dt, respectively
300
350
40OOC
Figure 2. Avicel + FeSO, evaluation by the model of successive reactions. The second partial curve belongs to the intermediate product. Its formation (rate of muss gain) is shown below the dashed line dmldt = 0. -dm/dt
the reacting species divided by the initial mass of the decomposing sample. If ci denotes the amount of volatiles formed from a unit mass of species i, then we have for the rate of the overall mass loss dm/dt = Cci dmi/dt
(7)
For the decomposition of the individual species we have dml/dt = -Al exp(-E1/RT) mlnl
(8)
dmi/dt = -(1 - ci-J dmi-l/dt - Ai exp(-Ei/RT) mini i = 2, 3, ... (9)
Combined Models. Any combination of the above models may arise in the thermal decomposition of the various biomass materials. During the kinetic evaluation of the present work, however, only the combination of the independent and successive reactions was necessary.
Figure 3. Avicel + ZnClz evaluation by the model of successive reactions. (The rate of mass gain of the intermediate product is shown below the dashed line dmldt = 0.) -dm/dt
Techniques of the Kinetic Evaluation The data were evaluated by the method of least squares. The sum
S = C[(dmob*/dt)j- (dmCB'C/dt)j]2
(10)
was minimized by searching for the optimal set of parameters for the model tested. Here dmokf dt and dmdc f dt stand for the observed DTG curve (normalized by the initial sample mass) and its counterpart obtained by the numerical solution of the kinetic differential equation(s) at the given set of parameters. Subscript j indicates the discrete values of a given dm f dt curve. The deviation between the observed and the calculated curves at the optimal set of parameters was given in percentage of the highest measured dm f dt value: deviation ('3%) = 100@N/max(-dmobs/dt)
Figure 4. Thermal decomposition of 4-methyl-D-glucorono-Dxylan. Evaluation was by the model of successive reactions. (The rate of mass gain of the intermediateproduct is shown below the dashed line dmldt = 0.) -dm/dt
I
h
(11)
(Here N is the number of the data of the given dmobef dt curve.) The flat tailing sections of the DTG curves corresponding to the slow charring prwess of the solid residue at higher temperatures were excluded from the kinetic evaluation. The domains of the kinetic evaluation are shown in Figures 1-7. From a mathematical point of view, the evaluation of the DTG data is approximately equivalent to the evaluation of the TG data. In practice, however, it is easier to make a distinction between well-fitting and poorly fitting models when the DTG curves are evaluated. In addition, the plot of the resulting dmcdc/dt curves unambiguously
250
300
350
400'C
Figure 5. Thermal decomposition of untreated bagasse (curve fitting by independent parallel reactions). shows whether or not the given model is able to describe multiple peaks and other fine details of the experiment.
Varhegyi et al.
332 Energy & Fuels, Vol. 3, No. 3, 1989
experiment standard 80 OC/min preheated + NaCl + NaCl + NaCl + FeSOl + ZnCll + ZnClz
model single single single compet indep succ succ indep succ
Table I. Kinetic Evaluation of the Avicel Experiments" first peak second peak E, kJ/mol log A c, % E , kJ/mol log A 234 17.6 205 15.1 222 16.8 75 3.5 75 240 17.7 87 5.1 25 224 16.5 101 6.5 43 198 14.4 209 17.3 44 na na 125 9.6 23 146 10.4 127 9.7 39 145 10.4
c, 73
93 94 91 76 51 52 39 41 37
dev, % 1.9 2.1 2.1
0.9 0.8 1.1
2.4 1.1 1.1
"The subheading Experiment lists the alterations from the standard 10 OC/min experiment of pure Avicel cellulose. The terms single, compet, indep, and succ in the column titled model stand for the models of a single reaction, competitive reactions, and successive reactions, respectively. Parameters c have different meanings in the different models (see text). Hyphens indicate the lack of the corresponding peak. The term na (not available) refers to the kinetic parameters of an ill-defined flat peak. The units of A are 5-l. -dm/d t
For the case of successive reactions, a simple transformation of the mj(t) variables into a set of qj(t) variables reduces eq 7-9 into the simpler form dm/dt =
Cc: dqi/dt
dq,/dt = -A'' exp(-El/RT) qlnl dqi/dt = -dqj-l/dt - A : exp(-Ej/RT) qini i = 2, 3, ...
(12)
(13) (14)
In case of two reactions, this transformation is 250
300,
350
400°C
Figure 6. Thermal decomposition of FeS04-treated bagasse (curve fitting by independent parallel reactions).
-d"dt
I
5
Figure 7. Thermal decomposition of ZnClTtreated bagfitting by independent parallel reactions).
(curve
In nonisothermal reaction kinetics, special care is needed to properly choose the initial values of the unknown parameters and to ensure convergence. The calculations are based on an algorithm developed by G.V. for nonisothermal reactions.16 Here we briefly summarize its main features and the modifications needed for the other kinetic models. Linear and Nonlinear Parameters. In the case of independent parallel reactions, dmldt is a linear function of the unknown ci parameters. Hence it is sufficient to vary only the remaining parameters by a general minimization subroutine. The ci parameters are calculated by a simple linear least-squares calculation at each set of values of the nonlinear parameters. In this way, the dimension of the problem is reduced and convergence is more assured. A similar simplification also can be applied to the other mechanisms. (16) Varhegyi, G. Thermochim. Acta 1979, 28, 367-376.
qlW = (1 - cl)ml(t)
q2 = m2W
(15)
Equation 12 has the same form as eq 4, and eq 13 and 14 do not differ too much from eq 3. This similarity allowed us to use the same program for the evaluation of the parallel independent reaction model, the successive reaction model, and their combination. Parameter Transformations. For the case of independent parallel reactions, a simple parameter transformation speeded up the convergence and allowed an easy and safe way to choose the initial parameter values.16 The same parameter transformation proved to be useful for the model of successive reactions, too. For competitive reactions, another parameter transformation was developed, which will be published elsewhere. Nonlinear Minimization. In the present calculations, we checked the algorithms of the IMSL library" and obtained the best performance for a simple direct search technique: the simplex (or polytope) algorithm.'* For safety, strict convergence criteria were given and all floating point variables were declared "double precision" in the programs. The overall time of the calculations varied between 3 and 30 min, depending on the number of the unknown parameters. Results and Discussion Reliability of the Kinetic Parameters. The experimental errors of a TG curve obtained by a state of the art, microprocessor-controlled thermobalance are neither random nor independent quantities. The averaging used in the computerized data a~quistion'~ filters out the random errors of the digitization process. The numerical techniques used in the computation of the DTG values do (17) ZMSL MATHILBRARY For Numerical Fortran Programming; IMSL,Inc.: Houston, TX, 1987.
(18) Nelder, J. A.; Mead, R. Comput. J. 1966, 7, 308-313. (19) Varhegyi, G.; Till, F.; Szekely, T. Thermochim. Acta 1986,102, 115-124.
Kinetics of Thermal Decomposition
heatine rate, OC/min model 10 succ 80 succ 10 indep 80 indep
Energy & Fuels, Val. 3, No. 3, 1989 333
Table 11. Kinetic Evaluation of the Xylan Experiments’ first reaction second reaction E, kJ/mol loa A c, % E, kJ/mol loa A 43 95 6.7 193 16.9 44 96 7.1 195 16.9 9.0 199 17.3 18 121 26 131 10.1 194 16.6
c, %
56 55 58 54
dev. % 1.3 1.7 3.0 2.8
’See the comments in footnote a in Table I. ~~
Table 111. Kinetic Evaluation of the Bagasse ExDeriments by the Model of IndeDendent Parallel Reactions’ 1st peak of hemicellulose 2nd peak of hemicellulose cellulose exoeriment E. kJ/mol lonA c, % E. kJ/mol logA c. % E, kJ/mol loaA c, % dev, % 31 213 15.3 43 1.1 standard (187) (17) (2) 111 7.7 13.7 40 1.3 7.5 32 195 (3) 105 80 “C/min (148) (13) (7) 209 14.8 42 1.6 preheated (14) (191) (3) 104 7.3 20 141 9.5 47 1.3 + NaCl (133) (12) 101 6.8 33 159 10.9 38 1.9 FeSO, + ZnClz 115 9.1 14 (123) (9) (12) 140 9.4 37 3.0 ~~~
~
~
+
‘Hyphens refer to the lack of the corresponding peaks. Parentheses indicate the parameters of ill-defined small peaks. The peaks of the ZnClz-treated sample were preceeded by a small peak around 190 “C with parameters E = 97 kJ/mol, log A = 9,and c = 1.5%. The units of A are s-l.
with a fixed value of n = 1, we still obtained an acceptable not add significant random errors to the data (see Figure fit: about 2% deviation at both heating rates. A t 10 1 in ref 1). Consequently, the elegant methods of the OC/min the kinetic parameters were A = 3.9 X 1017s-l and mathematical statistics cannot be used for the estimation E = 234 kJ/mol. The value of the activation energy is of the reliability of the kinetic parameters calculated from reasonable for this type of reaction. The preexponential this type of data. This reasoning is outlined in more detail factor is higher than that of an elementary unimolecular in ref 15 under the subtitle “The Use and Misuse of reaction.21 However, the assumption of a reaction network Statistics”. The greatest experimental errors are systemwith a rate-determining reaction means that the overall atic and seem to be connected with heat transfer probreaction rate is approximately the product of the rate of l e m ~hence, ; ~ the most suitable way to judge the reliability the rate-determining reaction and several other factors. of the parameters appears to be a comparison of the paAt the higher heating rate (80 OC/min) E and A slightly rameters obtained from measurements at different heating decreased (see Table I). The decrease can be due to heat rates. Experiments with heating rates of 10 and 80 OC/min transfer problems at the higher heating rate4 The actiwere compared for this reason. Note that the latter heating vation energies are close to the values reported in some rate is usually considered high in thermogravimetry. In former studies. (However, the opinion of the various authe case of Avicel, the difference between the log A and thors differed concerning the rate-controlling process.) E values at the two heating rates were about 12%. A Thus Anta14 reported 242 kJ/mol for the cellulose difference of 8% was observed from an evaluation of log “active cellulose” reaction step. Broido7 gave 229 f 8 A and E for the two main peaks of the bagasse (see Table kJ/mol for the activation energy of the “depolymerization” 111). The best agreement was observed in the case of xylan process. (4-methyl-D-glucurono-D-xylan). For the successive reacPreheated Avicel. A preheat of 1h at 260 “C before tion model, the differences between the activation energy the usual 10 OC/min heating program did not change values of the higher and lower heating rate experiments significantly the kinetics of the decomposition. With were only 1%. The differences listed above indicate that varying reaction order, we obtained n = 1.2 again, while the obtained kinetic parameters may contain errors on the the first-order model led to A = 6 X 10l6s-l and E = 222 order of 10%. kJ/mol with an acceptable fit (see Table I). Thermal Decomposition of P u r e Avicel. The single Avicel + NaCl. The sodium chloride catalyzed dereaction model gave a formal reaction order of 1.2 at composition proved to be equally well fit by each of the heating rates of 10 and 80 “C. The deviations between the models for successive, competitive, and independent calculated and the observed DTG curves were 0.9% and parallel reactions. The deviations between the observed 1.5%, respectively. Since the formal reaction order is and the calculated curves were between 0.8 and 1.1%. The strongly connected with the degree of asymmetry of the DTG curve shows that the majority of the sample decomDTG curves,2oa value of n = 1.2 indicates that the deposed in the temperature domain of the untreated sample scending part of the DTG curve is less steep than in the while a smaller part decomposed at lower temperatures. case of a pure first-order reaction. The most plausible This observation is reflected by the kinetic parameters of interpretation is that a rate-determining first-order reacthe competitive and the independent parallel reaction tion was followed by further reaction steps, in accordance models. In these cases, the kinetic parameters of the with the generally accepted hypotheses concerning the chemical mechanism of the cellulose decomp~sition.~,’ second peak were close to the corresponding values of the untreated sample (see Table I). The easiest explanation These further reactions, however, only slightly affected the is to assume that part of the sample decomposed via a low DTC curve; hence, there weas no possibility to determine activation energy pathway opened by the catalyst while their kinetic parameters. (In other words, the information the decomposition of the remainder remained unchanged. content of a single regularly shaped DTG peak is not sufficient for the determination of the parameters of a multistep kinetic model.Is) Carrying out the evaluation
-
(20) Kissinger, H. E. Anal. Chem. 1957,29,1702-1706.
(21)Benson, S.W.;Golden, D. M. In Physical Chemistry, An Aduanced Treatise, Vol. V I I Reactions in Condensed Phase; Eying, H., Ed.; Academic Press: New York, 1975;pp 58-124.
334 Energy & Fuels, Vol. 3, No. 3, 1989
The model for competitive reactions corresponds to the case when the whole sample has the same probability to decompose through the catalyzed path. The model of the independent parallel reactions describes the situation where only those parts of the sample that had some contact with the catalyst decomposed through the low activation energy pathway. The ratio of the weight loss due to the catlayzed and noncatalyzed pathways proved to be about 1:2 in both models. Because the distinction between the competitive and the independent parallel reaction models requires experiments with extremely different heating rates, further experiments are necessary before a firm conclusion can be reached. Figure 1shows the fit and the partial reactions in the case of the competitive reaction model. Avicel FeS04. The addition of about 1 mol % FeS04 to the cellulose shifted almost the entire DTG to considerably lower temperatures. The main peak was followed by a low, flat DTG signal, which may be due to a slow step-by-step decomposition (charring) of the residue. This interpretation corresponds to a consecutive reaction model. The resulting curves are shown in Figure 2. The kinetic parameters of the main peak are listed in Table I. The parameters of the second process had extremely low values (0.6 s-l and 23 kJ/mol, respectively) indicating that the flat tailing part of the DTG curve can only-formally be described by a single reaction. When independent parallel reactions were used, three reactions had to be assumed to achieve the same fit. The kinetic parameters of the main peak were close to the values given by the successive reaction model. The model of the competitive reactions did not give an acceptable fit. A closer examination of the problem revealed that the competitive reaction model is unable to describe this type of curve. With a linear temperature program, competitive reactions exhibit first the relatively flat peak(s) of the lower activation energy step(s). In the higher part of the temperature domain, the rate of the reaction with the highest activation energy starts to increase sharply. In this way, the overall DTG curve will contain a flat section at lower temperatures and a sharp peak at the end of the domain, while the DTG curve of the FeS04-catalyzed decomposition proved to be just the opposite of that picture. Avicel ZnClo. This experiment is equally well described by the models of successive and independent parallel reactions. Figure 3 shows the former case. Both models gave the same kinetic parameters (see Table I). The kinetic parameters were lower than in the case of pure Avicel, but still in the ranges of chemically meaningful A and E values. (Here the term "ranges of chemically meaningful A and E values" stands for the usual ranges of A and E values of elementary decomposition processes.21 The kinetic evaluation of thermoanalytical curves frequently leads to parameters out of these ranges.) The competitive reactions model did not give an acceptable fit. From a chemical point of view, only the successive reactions model seems to be plausible. Note that the presence of the ZnClp shifted the second DTG peak (as well as the first) to a slightly lower temperature (to 330 O C from 360 "C.) Hence, we can exclude the existence of a noncatalyzed phase in the sample. On the other hand, we may assume that ZnClz catalyzed the dehydration reactions at the temperature of the first DTG peak, and the solid residue of this reaction decomposed further in the temperature domain of the second peak. Thermal Decomposition of 4-Methyl-~-glucuronoD-xylan. The xylan sample exhibited a characteristic double peak (see Figure 4). Experiments were carried out
+
+
Varhegyi et al.
at heating rates of 10 and 80 OC/min. The model of successive reactions gave a good fit to the experimental data and a very good agreement between the A , E , and c values obtained from the 10 and 80 OC/min experiments (see Table 11.) In the case of the independent parallel reaction model, the fit was worse (about 3%) and the difference between the parameters associated with the 10 and 80 "C/min experiments was higher. The model of competitive reactions was unable to describe the DTG curves for the reasons outlined in the paragraph titled "Avicel + FeS04" above. An interpretation of the corresponding mass spectrometric curves also led to the assumption of successive reaction^.^ Earlier, Ward and Braslawlo described the thermal decomposition of hemicellulose by a chain of three successive reactions. Obviously we cannot exclude the existence of three or more successive reactions. Our experiments, however, reflect only the effect of two reactions, so if there are more reactions, only two of them are rate determining. When we formally approximated the double peak of the xylan decomposition by a single first-order reaction, we obtained a bad fit (10% deviation). In this case the activation energy (104kJ/mol) was close to the values reported by those investigators who described the degradation of hemicellulose samples by a single first-order reacti~n.~ It ,may ~ be interesting to note that the approximation of the TG curve of the same experiment by a single first-order reaction resulted in a fit of abaut 1.2%. This smaller deviation reflects the fact that decompositions having clear and characteristic double peaks on the differential type of thermoanalytical curves exhibit only small "shouldersnon the TG curve. We should like to underline, however, that we observed the same double peak on the mass spectrometric curves of the xylan decomposition, too.3 Thermal Decomposition of Sugar Cane Bagasse. The bagasse experiments evidenced three DTG peaks between 200 and 400 "C (see Figure 5), of which the first two were due to hemicellulose(s) and the third peak was due to cellulose.2 (The lignin component did not give a DTG peak in this temperature domain. Its slow, stepwise decomposition gave a flat DTG section, which became dominant only at higher temperatures.) The two hemicellulose peaks probably belong to different hemicellulose materials. Keeping in mind the results of the xylan experiments, however, we cannot exclude the possibility that a single chain of consecutive reactions gave a double peak here. Hence the kinetic evaluations were carried out by two different models: the independent parallel reaction model and a "combined model" assuming successive reactions for the first peak. The two models gave practically identical fits and parameter sets at both heating rates (10 and 80 OC/min); hence, no distinction could be made between these models. Table I11 shows the parameters belonging to the case of the independent parallel reactions. The results at 10 and 80 OC/min were close to each other; only the parameters of the small, ill-defined first peak differed by about 20%. Note that the parameters of the cellulose peak agree well with the parameters of the Avicel cellulose (cf. Tables I and 111). This agreement may be due to the fact that the water-soluble part of the mineral matter was removed from the bagasse during the hotwater-leaching process of the cane sugar fabrication. The parameters of the hemicellulose peaks were also close to the parameters of the pure 4-methyl-D-glucurono-D-xylan, especially at the lower heating rate (see the results of the independent parallel reaction model at 10 OC/min in Table 11). However, we cannot exclude the possibility of a ran-
Kinetics of Thermal Decomposition
dom coincidence of the corresponding E and log A values. Concerning the ci parameters of the independent parallel reaction model: they give the contributions of each component to the overall weight loss. As Table I11 shows, the kinetic evaluation resulted in weight losses of 33-35% and 40-43% for the decomposition of the hemicellulose and the cellulose components, respectively. Note that the bagasse composition is reported to be about 32% hemicellulose, 40% cellulose, 20% lignin, 6% extractives, and 2% ash.22 The small difference between the reported composition and the values given by the kinetic evaluation may be due to various errors inherent in the different experimental techniques, as well as to some contribution of the lignin and the extractives to the weight loss within the temperature range of the evaluation. However, the good agreement between the kinetic parameters of the bagasse and the corresponding values of the pure avicel and xylan samples indicates that the contributions of the lignin and the extractives are either neglibible or consist of broad, very low DTG signals that do not influence the kinetic evaluation. A preheating of 1h at 260 "C eliminated the majority of the hemicellulose components, leaving only a small, ill-defined DTG signal in this temperature domain. The kinetic parameters of the cellulose component were close to those of the pure Avicel again. Effects of Catalysts on the Thermal Decomposition of Bagasse. The catalysts used in this work opened lower activation energy pathways for a fraction of the sample. As a result, the DTG peaks become broader, ranging from the temperature of the noncatalyzed decomposition to the that of the catalyzed decomposition. Since the DTG peaks of the components overlapped each other, there was no possibility of determining the partial reactions. Hence, a kinetic analysis could only describe formally the broader peaks, giving lower E and A values. (See Figures 6 and 7 and the data in Table 111. Note that lower E and A values give wider DTG peaks.) It is interesting to note that the ZnC12 catalyst experiment could be described only by the assumption of four DTG peaks. (See Figure 7.) The small flat peak at 190 "C was not identified. (Its kinetic parameters were A = lo9 s-l, E = 97 kJ/mol and c = 1.5%.) The ratios of the areas of the remaining three peaks (at TpeaL = 260,290, and 355 "C) indicated that a considerable amount of the hemicellulose decomposed around 260 "C while the decomposition of the cellulose component was (22) Lipinsky, E. S. In Hydrolysis of Cellulose: Mechanisms of Enzymotic and Acid Catalysis; Brown, R. D., Jr., Jarasek, L.; as. Advances ; in Chemistry 181; American Chemical Society: Washington DC, 1979; pp 1-23.
Energy & Fuels, Vol. 3, No. 3, 1989 335
effected only on a smaller extent.
Conclusions A least-squares evaluation of the DTG curves led to an acceptable mathematical description for the catalytic and noncatalytic thermal decomposition reactions of cellulose, hemicellulose and bagasse. The resulting activation energies and preexponential factors fell into the range of chemically meaningful E and A values. The decomposition of pure Avicel cellulose is well described by a single first-order reaction, indicating that one of the reactions of the reaction network is rate controlling. The other experiments required evaluations by multireaction models. The assumption of competitive reactions gave an adequate fit only for the DTG curve of the NaC1-treated cellulose (Figure 1). The assumption of independent parallel reactions and the assumption of successive reactions gave roughIy identical fits and kinetic parameters at the majority of the experiments; hence, the distinction between these models could only be based on chemical considerations. The kinetic evaluation affirmed the hypotheses that were drawn from the interpretation of the mass spectrometric curves of the same e~periments-l-~Thus the thermal decomposition of 4-methy~-D-glucurono-D-xy~an was well simulated by the successive reaction model with practically identical parameters at 10 and 80 "C/min. The evaluation of the NaC1-catalyzed cellulose decomposition led to the conclusion that roughly two-thirds of the sample decomposed with the kinetic parameters of the untreated cellulose; while the other third went through a lower activation energy pathway. The treatment of cellulose with FeS04 and ZnClz changed the decomposition of the whole sample. The corresponding DTG curves were well described by assuming a low-temperature catalytic reaction followed by the successive decomposition of the residue. The kinetic parameters obtained from the DTG curves of bagasse affirmed the hypothesis of Shafizadeh and McGinnis14concerning the independence of the decomposition of the major components in a lignocellulose material. A preheating of l h at 260 "C eliminated the majority of the hemicellulose components without influencing the kinetics of the cellulose decomposition. Altogether, kinetic evaluation of the DTG curves proved to be useful to affirm chemical considerations and to supplement them with quantitative data. It is not possible, however, to choose between kinetic models only on the magnitude of the deviation between the experimental and the theoretical data. Registry No. NaCI, 7647-14-5;FeS04, 7720-78-7;ZnCl2, 7646-85-7;cellulose, 9004-34-6; 4-methyl-D-g~ucurono-D-xylan, 9062-57-1.
