Search

Acid-catalyzed aqueous-phase hydrolysis of cellulose was investigated over zeolite HY nanocrystals grafted on anantase titania nanofibres (HY-TiO2). H-exchanged NaY zeolite nanocrystals of controlled size (40–60 nm) were synthesized and deposited over TiO2 nanofibres prepared by hydrothermal treatment of anatase nanoparticles. The resulting materials were characterized by XRD, SEM, TEM, NH3-TPD and FT-IR, and evidenced a homogeneous distribution of HY nanocrystals across the TiO2 nanofibres. HY-TiO2 catalysts exhibited higher turnover numbers and selectivity to glucose than large (500 nm to 2 μm) unsupported HY nanoparticles; this performance enhancement is attributed to the greater accessibility of Bronsted acid sites in HY nanocrystals to cellulose particles. The importance of active site accessibility to β-1,4-glycosidic bond cleavage was highlighted by a significant increase in the rates of glucose and cellobiose hydrolysis (versus cellulose) over HY-TiO2-100. Engineering of zeolite particle size is a critical design parameter for the valorization of sterically-challenging cellulosic feedstocks.

The pyrolysis processes of the selected combustible solid wastes (CSWs) including poplar wood, polyethylene (PE), paper, rubber, rice and polyethylene terephthalate (PET) were investigated by thermogravimetric (TG) analysis. The pseudocomponents of the six kinds of selected CSWs were determined based on Weibull mixture model. The DAEM reaction model was used to study the pyrolysis kinetics of the samples. The results showed that the pyrolysis temperature of selected CSWs was ranged from 413.15 to 979.14 K and the Weibull mixture model can reproduce the TG and DTG curves accurately. The TG curve can be understood as a sum of two or three parallel reactions, where each single reaction was represented by one Weibull model component. It was observed that there were three pseudocomponents for the poplar and paper samples. There was one pseudocomponent for the PE sample. However, the rubber, rice and PET samples had two pseudocomponents. The activation energy (E α ) changed from 120 to 225 kJ mol−1 in the range of the conversion rate from 0.15 to 0.85 for the six kinds of selected CSWs.

This work studied the drying kinetics of the organic fractions of municipal solid waste (MSW) samples with different initial moisture contents and presented a new method for determination of drying kinetic parameters. A series of drying experiments at different temperatures were performed by using a thermogravimetric technique. Based on the modified Page drying model and the general pattern search method, a new drying kinetic method was developed using multiple isothermal drying curves simultaneously. The new method fitted the experimental data more accurately than the traditional method. Drying kinetic behaviors under extrapolated conditions were also predicted and validated. The new method indicated that the drying activation energies for the samples with initial moisture contents of 31.1 and 17.2 % on wet basis were 25.97 and 24.73 kJ mol−1. These results are useful for drying process simulation and industrial dryer design. This new method can be also applied to determine the drying parameters of other materials with high reliability.

The combustion kinetics of biochar derived from fast pyrolysis of pine sawdust was investigated by using nonisothermal thermogravimetric analysis under air atmosphere at different heating rates. The experimental conversion (α–T) curves contain some experimental errors, and the corresponding derivative conversion (dα/dT–T) curves have many fluctuations. Two strategies of obtaining the smooth dα/dT–T curves were used based on the robust locally weighted scatterplot smoothing method coupled with the corrected AIC smoothing parameter selection method. In the strategy of firstly smoothing α–T data and then differentiating smoothed α–T data, although the smoothed α–T data are relatively smooth, the dα/dT–T curves obtained from the differentiation of the smoothed α–T data have fluctuations. In the strategy of firstly differentiating α–T data and then smoothing dα/dT–T data, the obtained dα/dT–T curves with the optimal smoothing parameters are smooth enough, which indicates that the second strategy is effective. The isoconversional kinetic analysis of the smoothed dα/dT–T curves was performed by using the Friedman differential isoconversional method. The effective activation energies of biochar combustion were obtained and found to significantly vary with the conversion degree (from about 150 to 250 kJ mol−1 in the range of conversion degree from 0.05 to 0.95).

This work involved the prediction of the concentration profiles and theoretical yields in lignocellulosic biomass pyrolysis under real pyrolysis conditions. The competing reaction model was used and verified by the experimental data of the pyrolysis of oilseed rape straw and sesame stalk. The pyrolysis kinetic behaviors of the pyrolysis of peach branch, cotton stalk, and corn stalk under various conditions were simulated based on the model and their chemical compositions. The influences of the heating rate and final temperature on the theoretical yields of pyrolysis products and the pyrolysis time were obtained. Under the same conditions, the pyrolysis of peach branch gave the highest yield of volatile products, while the pyrolysis of cotton stalk gave the highest yield of char. The method presented in this work enables us to predict the concentration profiles and theoretical yields of different lignocellulosic materials under various pyrolysis conditions.

In this work, a new method for fitting the conversion rate curves of the distributed activation energy model (DAEM) and lignocellulosic biomass pyrolysis process was introduced. The method was based on the curve fitting technique using the Fraser–Suzuki function. Various simulated DAEM processes were analyzed. The results showed that the conversion rate curve of one DAEM process could be described well by a Fraser–Suzuki function. According to the obtained parameters of the fitted Fraser–Suzuki functions, the influences of the DAEM parameters on the conversion rate curves of the corresponding DAEM processes can be quantitatively obtained. The experimental data of the pyrolysis of cotton stalk, oilseed rape straw, and rice straw were fitted by the Fraser–Suzuki mixture model which involves three individual Fraser–Suzuki functions. It has been found that the Fraser–Suzuki mixture model can reproduce accurately the conversion rate curves of the pyrolysis of three lignocellulosic biomass samples. The Fraser–Suzuki mixture model provides an approach to separate lignocellulosic biomass pyrolysis into three parallel reactions which link to the decomposition of hemicellulose, cellulose, and lignin, respectively.

The pyrolysis of wheat straw has been carried out by means of thermogravimetric analysis in inert atmosphere. The samples were heated over a range of temperatures that includes the entire range of pyrolysis with three different heating rates of 5, 10 and 20 K min−1. The activation energy values as a function of the extent of conversion for the pyrolysis process of wheat straw have been calculated by means of the Flynn–Wall–Ozawa isoconversional method, the Vyazovkin–Sbirrazzuoli isoconversional method and an iterative isoconversional method presented in this article. The results have showed that there are small differences between the activation energy values obtained from the three methods, and the pyrolysis process reveals a dependence of the activation energy on conversion and have indicated the validity of the iterative integral isoconversional method. The effective activation energy for the pyrolysis of wheat straw is 130–175 kJ mol−1 in the conversion range of 0.15–0.85. Furthermore, the prediction of the pyrolysis process under isothermal conditions from the dependence of the activation energy on the extent of conversion has been presented.

The integral methods, which are obtained from the various approximations for the temperature integral, have been extensively used in the non-isothermal kinetic analysis. In order to obtain the precision of the integral methods for the determination of the activation energy, several authors have calculated the relative errors of the activation energy obtained from the integral methods. However, in their calculations, the temperature integral at the starting temperature was neglected. In this work, we have performed a systematic analysis of the precision of the activation energy calculated by the integral methods without doing any simplifications. The results have shown that the relative error involved in the activation energy determined from the integral methods depends on two dimensionless quantities: the normalized temperature θ=T/T 0, and the dimensionless activation energy x 0=E/RT 0 (where E is the activation energy, T is the temperature, T 0 is the starting temperature, R is the gas constant).

A nonlinear regression method has been proposed for a simultaneous calculation of the activation energy, frequency factor, and reaction order from a single TG curve. This method was based on the new temperature integral approximation proposed in this paper and the Levenberg–Marquardt method. The newly proposed nonlinear regression method was applied for determining the kinetic parameters from two simulated TG curves. The results of the calculations were compared with values obtained by the traditional method. It can be concluded from this comparison that the new nonlinear regression method is more accurate than the traditional method for the determination of the kinetic parameters of solid-state heterogeneous reactions.

In this paper, a systematic analysis of the errors involved in the determination of the kinetic parameters (including the activation energy and frequency factor) from five integral methods has been carried out. The integral methods analyzed here are Coats-Redfern, Gorbachev, Wanjun-Yuwen-Hen-Zhiyong-Cunxin, Junmeng-Fusheng-Weiming-Fang, Junmeng-Fang and Junmeng-Fang-Weiming-Fusheng method. The results have shown that the precision of the kinetic parameters calculated by the different integral methods is dependent on u (E/RT), that is, on the activation energy and the average temperature of the process.

This paper describes the influences of some parameters relevant to biomass pyrolysis on the numerical solutions of the nonisothermal n th-order distributed activation energy model (DAEM) involved the Weibull distribution. Investigated parameters are the integral upper limit, the frequency factor, heating rate, the reaction order and the shape, scale and location parameters of the Weibull distribution. Those influences can be used for the determination of the kinetic parameters of the nonisothermal n th-order Weibull DAEM from thermoanalytical data of biomass pyrolysis.

The integral methods are extensively used for performing the kinetic analysis of solid-state reactions. As the Arrhenius integral function p(u) does not have an exact analytical solution, many approximations have been proposed. One popular type of approximations is called the exponent approximation which can be put in the form $$p(u) = e^{a+b\,ln\,u+cu}$$ . In this study, a systematic analysis of the errors involved in the determination of the kinetic parameters calculated by the integral methods based on the exponent approximations for p(u) has been carried out. The results have shown that the precision of the kinetic parameters computed from the integral methods analyzed in this paper depends on u and the errors of the kinetic parameters determined from Doyle approach are the largest.

An improved version of Junmeng–Fang–Weiming–Fusheng approximation for the temperature integral has been developed. The accuracy of the improved approximation for the temperature integral has been tested by some numerical analyses. The systematic analysis of the relative errors involved in the kinetic parameters obtained from Junmeng–Fang–Weiming–Fusheng integral method and its improved version has been also carried out. The results have shown that the improved approximation is more accurate than Junmeng–Fang–Weiming–Fusheng approximation as the solution of the temperature integral, and that more accurate kinetic parameters can be determined from the integral method based on the improved temperature integral approximation.

An improved version of Doyle integral method for the determination of the kinetic parameters from nonisothermal thermoanalytical data has been presented. The relative errors involved in the activation energy and frequency factor determined from Doyle integral method and its improved integral method have been estimated. The results have shown that the precision of the improved version of Doyle integral method for the determination the kinetic parameters (including the activation energy and frequency factor) is much higher than that of Doyle integral method.

A new approximation has been proposed for calculation of the general temperature integral \( \int\limits_0^T {T^m } e^{ - E/RT} dT \), which frequently occurs in the nonisothermal kinetic analysis with the dependence of the frequency factor on the temperature (A=A0Tm). It is in the following form: $$ \int\limits_0^T {T^m } e^{ - E/RT} dT = \frac{{RT^{m + 2} }} {E}e^{ - E/RT} \frac{{0.99954E + (0.044967m + 0.58058)RT}} {{E + (0.94057m + 2.5400)RT}} $$

The dependence of the frequency factor on the temperature (A=A0Tm) has been examined and the errors involved in the activation energy calculated from some integral methods without considering such dependence have been estimated. Investigated integral methods are the Coats-Redfern method, the Gorbachev-Lee-Beck method, the Wanjun-Yuwen method and the Junmeng-Fusheng method. The results have shown that the error in the determination of the activation energy calculated ignoring the dependence of the frequency factor on the temperature can be rather large and it is dependent on x=E/RT and the exponent m.

A new integral method of nonisothermal kinetic analysis has been developed with the dependence of the frequency factor on the temperature (A = A 0 T m ). The new integral method is obtained from the newly proposed approximation for the general temperature integral, which is more accurate than the other existed approximations. For applications, nonisothermal thermoanalytical data obtained by theoretical simulation have been processed. The results have shown that the newly proposed integral method is an ideal solution for the evaluation of kinetic parameters from nonisothermal thermoanalytical data with the frequency factor dependent the temperature.

Nonisothermal nth-order distributed activation energy model (DAEM) was derived. Numerical solutions of the nonisothermal nth-order DAEM equation were performed. The influences of various parameters relevant to biomass pyrolysis on numerical results of the nonisothermal nth-order DAEM equation were also studied. Investigated parameters are heating rate, the mean of activation energy distribution, standard deviation of activation energy distribution, frequency factor and reaction order. The study results can be further responsible for determination of nth-order DAEM kinetic parameters from thermogravimetric analysis data of biomass.

The most accurate and up-to-date approach to modeling biomass pyrolysis is to adopt the distributed activation energy model (DAEM). In this study, a pattern search method to be used for the determination of DAEM kinetic parameters from the nonisothermal thermogravimetric analysis (TGA) data of biomass has been introduced. The method has been applied to the nonisothermal TGA data of peanut shell sample, and DAEM kinetic parameters of biomass samples have been determined. Calculated model results from determined kinetic parameters have been compared with nonisothermal TGA data of biomass.

Recently, Orfao obtained two simple equations for the estimation of the relative error in the activation energy calculated by the integral methods [2]. In this short communication, the validity of the equations has been evaluated by comparing the results calculated by the equations with the results calculated by the equation from theoretical derivation without introducing any assumption.