Pyrolysis of medium-density fiberboard: optimized search for kinetics scheme and parameters via a genetic algorithm driven by Kissinger's method

The pyrolysis kinetics of charring materials plays an important role in understanding material combustions especially for construction materials with complex degradation chemistry. Thermogravimetric analysis (TGA) is frequently used to study the heterogeneous kinetics of solid fuels; however, there is no agreed method to determine the pyrolysis scheme and kinetic parameters for charring polymers with multiple components and competing reaction pathways. This study develops a new technique to estimate the possible numbers of species and sub-reactions in pyrolysis by analyzing the second derivatives of thermogravimetry (DDTG) curves. The pyrolysis of a medium-density fiberboard (MDF) in nitrogen is studied in detail, and the DDTG curves are used to locate the temperature of the peak mass-loss rate for each sub-reaction. Then, on the basis of the TG data under multiple heating rates, Kissinger’s method is used to quickly find the possible range of values of the kinetic parameters (<i>A</i> and <i>E</i>). These ranges are used to accelerate the optimization of the inverse problem using a genetic algorithm (GA) for the kinetic and stoichiometric parameters. The proposed method and kinetic scheme found are shown to match the experimental data and are able to predict accurately results at different heating rates better than Kissinger’s method. Moreover, the search method (K–K method) is highly efficient, faster than the regular GA search alone. Modeling results show that, as the TG data available increase, the interdependence among kinetic parameters becomes weak and the accuracy of the first-order model declines. Furthermore, conducting TG experiment under multiple heating rates is found to be crucial in obtaining good kinetic parameters

CO2 gasification of chars prepared from wood and forest residue

The CO2 gasification of chars prepared from Norway spruce and its forest residue was investigated in a thermogravimetric analyzer (TGA) at slow heating rates. The volatile content of the samples was negligible; hence the gasification reaction step could be studied alone, without the disturbance of the devolatilization reactions. Six TGA experiments were carried out for each sample with three different temperature programs in 60 and 100% CO2. Linear, modulated, and constant-reaction rate (CRR) temperature programs were employed to increase the information content available for the modeling. The temperatures at half of the mass loss were lower in the CRR experiments than in the other experiments by around 120 degrees C. A relatively simple, well-known reaction kinetic equation described the experiments. The dependence on the reacted fraction as well as the dependence on the CO2, concentration were described by power functions (n-order reactions). The evaluations were also carried out by assuming a function of the reacted fraction that can mimic the various random pore/random capillary models. These attempts, however, did not result in an improved fit quality. Nearly identical activation energy values were obtained for the chars made from wood and forest residues (221 and 218 kJ/mol, respectively). Nevertheless, the forest residue char was more reactive; the temperatures at half of the mass loss showed 20-34 degrees C differences between the two chars at 10 degrees C/min heating rates. The assumption of a common activation energy, E, and a common reaction order, v, on the CO2, concentration for the two chars had only a negligible effect on the fit quality

Thermal Decomposition Kinetics of Woods with an Emphasis on Torrefaction

The pyrolysis kinetics of Norwegian spruce and birch wood was studied to obtain information on the kinetics of torrefaction. Thermogravimetry (TGA) was employed with nine different heating programs, including linear, stepwise, modulated and constant reaction rate (CRR) experiments. The 18 experiments on the 2 feedstocks were evaluated simultaneously via the method of least-squares. Part of the kinetic parameters could be assumed common for both woods without a considerable worsening of the fit quality. This process results in better defined parameters and emphasizes the similarities between the woods. Three pseudo-components were assumed. Two of them were described by distributed activation energy models (DAEMs), while the decomposition of the cellulose pseudo-component was described by a self-accelerating kinetics. In another approach, the three pseudo-components were described by n-order reactions. Both approaches resulted in nearly the same fit quality, but the physical meaning of the model, based on three n-order reactions, was found to be problematic. The reliability of the models was tested by checking how well the experiments with higher heating rates can be described by the kinetic parameters obtained from the evaluation of a narrower subset of 10 experiments with slower heating. A table of data was calculated that may provide guidance about the extent of devolatilization at various temperature residence time values during wood torrefaction

Kinetic Behavior of Torrefied Biomass in an Oxidative Environment

The combustion of four torrefied wood samples and their feedstocks (birch and spruce) was studied at slow heating programs, under well-defined conditions by thermogravimetry (TGA). Particularly low sample masses were employed to avoid the self-heating of the samples due to the huge reaction heat of the combustion. Linear, modulated and constant-reaction rate (CRR) temperature programs were employed in the TGA experiments in gas flows of 5 and 20% O2. In this way the kinetics was based on a wide range of experimental conditions. The ratio of the highest and lowest peak maxima was around 50 in the experiments used for the kinetic evaluation. A recent kinetic model of Várhegyi et al. [Energy & Fuels 2012, 26, 1323-1335] was employed with modifications. This model consists of two devolatilization reactions and a successive char burn-off reaction. The cellulose decomposition in the presence of oxygen has a self-accelerating (autocatalytic) kinetics. The decomposition of the non-cellulosic parts of the biomass was described by a distributed activation model. The char burn-off was approximated by power-law (n-order) kinetics. Each of these reactions has its own dependence on the oxygen concentration that was expressed by power-law kinetics, too. The complexity of the applied model reflects the complexity of the studied materials. The model contained 15 unknown parameters for a given biomass. Part of these parameters could be assumed common for the six samples without a substantial worsening of the fit quality. This approach increased the average experimental information for an unknown parameter by a factor of 2 and revealed the similarities in the behavior of the different samples