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Kinetic analysis of CO2 gasification of biochar and anthracite based on integral isoconversional nonlinear method

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Published/Copyright: October 2, 2020
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High Temperature Materials and Processes
From the journal High Temperature Materials and Processes Volume 39 Issue 1

Abstract

The nonisothermal thermogravimetric analysis was implemented for gasification of sawdust char (SD-char), wheat straw char (WS-char), rice husk char (RH-char), bamboo char (BB-char) and anthracite coal (AC) in the presence of CO2. The dependence of activation energy upon conversion for different biochars and AC was obtained by the integral isoconversional nonlinear (NL-INT) method which is a model-free method. Based on the activation energy values from the NL-INT method, a model-fitting method called random pore model (RPM) was used to estimate the kinetic parameters including the preexponential factor and pore structure parameter from the experimental data. The results are shown that the gasification reactivity of different samples from high to low can be sorted as that of WS-char, SD-char, BB-char, RH-char and AC. In the early stage of gasification, the activation energy values of biochars increase generally with an increase in the conversion degree, whereas the value of AC decreases. Thereafter, the activation energy values remain almost unchanged when the conversion is up to some extent. When the conversion degree varies between about 0.3 and 0.9, these carbon materials can be sorted in the order of average activation energy from low to high as WS-char, SD-char, AC, RH-char and BB-char, respectively, 134.3, 143.8, 168.5, 184.8 and 193.0 kJ/mol. It is shown that a complex multistep mechanism occurs in the initial stage of gasification, while a single-step gasification mechanism exists in the rest of the gasification process. The RPM is suitable for describing the gasification of biomass chars and AC except the initial gasification. Additionally, it is found that the kinetic compensation effect (KCE) still exists in the gasification reactions of biochars and AC. However, the AC deviates markedly from the KCE curve. This may be caused by the similarity of carbonaceous structure of biochars and the difference in reactivity between biochars and AC.

Keywords: biochar; gasification; integral isoconversional nonlinear method; random pore model; kinetic compensation effect

1 Introduction

Biomass energy, as an important renewable and clean energy and the only renewable carbon source, is characterized by wide distribution, rich reserves, renewability, carbon neutrality, fungibility and low pollution. It occupies the fourth place of the total world energy consumption after coal, oil and natural gas [1]. Currently, biomass conversion and utilization technologies can be divided into physical, chemical and biological transformations. The thermal chemical transformation methods, mainly including direct combustion, pyrolysis, gasification and liquefaction technologies, are widely used in the industries of biomass power generation, gas and liquid fuels [2]. Gasification is usually referred to thermal chemical conversion of biomass to gas by using a gasification medium, e.g., air, oxygen, nitrogen, steam, carbon dioxide or a combination of them [3]. Moreover, in the steel industry, renewable biomass-based fuels are considered as a promising opportunity to decrease fossil-based energy consumption and CO2 emissions. Especially, in the processes of iron making such as blast furnace (BF) iron making and direct-reduction iron making (DRI), biomass-derived reducing agents have gained more and more attention [4,5,6]. Generally, the auxiliary reducing agents are injected into the BF from the tuyeres located in the lower part of the BF via injection lances with oxygen-enriched hot blast. The biochars experience rapid heating, devolatilization, gas-phase combustion, char combustion and gasification. In fact, once all the oxygen are consumed at the border of the raceway, the main char consuming reaction is char gasification with CO2 [7]. In addition, for reducing carbon composite agglomerates (CCAs) in DRI process, the carbon gasification reaction with CO2 is an important step that induces the fast self-reduction process of CCAs [8]. It is noteworthy that high gasification reactivity of chars with CO2 is beneficial to decrease the amount of unreacted char, which either blocks the stock column in the lower region of a BF and inhibits the flow of reducing gas or decreases the reduction efficiency of CCAs.

The gasification characteristics of different chars can be evaluated using thermogravimetric methods [9,10,11,12,13]. As a result, the kinetic parameters of gasification can provide a fundamental understanding of the gasification process. At present, the methods of thermogravimetric dynamic analysis mainly include model-fitting method and model-free method (isoconversional method) [14]. In the model-fitting method, the models including volume reaction model (VM) [15,16], unreacted core model (URCM) [17] and random pore model (RPM) [11,12,18,19] are usually used to estimate the kinetic parameters. For a type of carbon material, the activation energy value obtained from the model-fitting methods is constant throughout the gasification process. Whereas the isoconversional method can be used to evaluate the activation energy values without assuming or identifying any particular form of the reaction model [20,21,22]. The activation energy value obtained by the model-free method is not a constant but a function of conversion during the gasification process. Generally, for a multistep kinetic process, it is difficult to find a suitable mechanism function for the model-fitting method. However, the isoconversional (model-free) method is suitable for obtaining reliable kinetic information from at least three sets of experimental data obtained at different heating rates, by which the activation energy obtained varies significantly with the conversion degree. Moreover, the activation energy obtained by the model-free method can be used to verify that gained by the model-fitting method.

In this work, the gasification reactivity and kinetic process of different chars such as sawdust char (SD-char), wheat straw char (WS-char), rice husk char (RH-char), bamboo char (BB-char) and anthracite coal (AC) were studied using the nonisothermal thermogravimetric analysis (TGA). Based on four sets of thermogravimetric (TG) curves under different heating rates, the apparent activation energy values at different conversion degrees were solved by the integral isoconversional nonlinear (NL-INT) method [22]. On the basis of the activation energy values calculated by the NL-INT method, the kinetic parameters of gasification of different carbon materials with CO2 were estimated using the RPM [18,19]. It is expected that this research will be helpful for understanding the mechanism of gasification reaction and improving the co-gasification of biochar and coal in the gasifier.

2 Materials and methods

2.1 Raw materials

The biomass feedstock sawdust (SD), wheat straw (WS), rice husk (RH) and bamboo (BB) were used for producing biochars by slow pyrolysis. Before carbonization, the biomass raw materials were rinsed, dried and smashed to the size of 0.25–5 mm. These pretreated samples were pyrolyzed in a controlled temperature tube-type resistance furnace with a flowing nitrogen atmosphere at a temperature of 973 K for 120 min. The biochars derived from pyrolysis were then grinded and screened for characterization analysis and gasification experiment. The AC raw material was taken from Yangquan city, Shanxi Province in China. The proximate and ultimate analyses of biomass and coal raw materials and biochars were conducted using the Chinese standard GB/T 212-2001 and GB/T 476-2001, respectively (Table 1). As shown in Table 1, after pyrolysis, the volatile matter content of the biochars is lower than that of AC, and the main contents are fixed carbon and ash. The ash content of WS-char and RH-char is as high as 32.52% and 42.44%, respectively.

Table 1

Proximate and ultimate analyses of carbonaceous materials (wt%)

SampleProximate analysisUltimate analysis
H2OFCdAdVdCdHdOdNdSd
SD8.6716.832.4580.7248.896.7541.390.440.08
SD-char90.543.895.5792.241.231.630.950.06
WS6.9518.417.2874.3141.514.0246.540.430.22
WS-char62.1632.525.3263.730.911.410.920.51
RH7.0215.1317.6667.2142.234.4135.220.410.07
RH-char52.8542.444.7154.590.831.090.840.21
BB9.0113.813.3382.8645.045.3745.540.650.07
BB-char79.7716.214.0279.521.012.370.780.11
AC7.5075.7611.2512.9978.253.535.191.050.73

Note: FCd, Ad and Vd are fixed carbon, ash and volatile matter with regard to dry basis, respectively; d, dry basis.

The SEM images of biochars and anthracite are shown in Figure 1. The alveolate structure and rough surface of the biochars can be clearly seen from Figure 1a–d. At the same magnification, the pore sizes of different biochars vary significantly. The pore diameter of WS-char is large and the pore wall is thin, whereas the pore size of RH-char is small. Some biochar particles maintain a larger particle size, while others are crushed. The regular pore structure of large char particles is clearly visible, while that of the small particles is not easily observed. When the large char particle is crushed, the pore walls are broken and the small particles are mostly flaky and rough with cracks. By contrast, as shown in Figure 1e, the surface of AC granule is smooth with dense structure. According to the research [23], the porosity of biochars is about 3 times more than that of coal and the specific surface of biochars is high compared to coke and coal.

Figure 1 SEM images of samples: (a) SD-char; (b) WS-char; (c) RH-char; (d) BB-char and (e) AC.
Figure 1

SEM images of samples: (a) SD-char; (b) WS-char; (c) RH-char; (d) BB-char and (e) AC.

2.2 Experimental procedure

The CO2 gasification experiments of biochars and anthracite were conducted by means of thermal gravimetric analyzer (TGA, METTLER TOLEDO STARe 9.20). Each sample weighing about 25 ± 2 mg was put into a crucible, which was moved to the hot zone of the reaction furnace. For the biochars, each experiment was conducted under nonisothermal condition from room temperature to the final temperature of 1,473 K at different heating rates of 5, 10, 15 and 20 K/min; whereas for the anthracite, the final temperature is 1,553 K. The flow rate of the gasifying agent (CO2, with purity of 99.9%) for the reaction zone is 50 mL/min. The experimental data were continuously recorded in real time by a computer.

2.3 Characteristic parameters of gasification

2.3.1 Gasification conversion

The gasification conversion degree (α) can be calculated by the following equation:

(1)α=W0−WtW0−W∞

where W0, Wt and W∞ (mg) are the initial sample weight, sample weight at the time of t and final sample weight during the gasification process, respectively. In this study, the temperature of 600 K is regarded as the starting temperature at which the sample mass is the initial one. In this way, the effect of nonreactive weightlessness on the extent of conversion can be avoided by eliminating the volatilization of moisture.

2.3.2 Conversion rate

The conversion rate γ(1/min) can be described by the following equation based on the first derivative of α:

(2)γ=dαdt

where t (min) is the reaction time during the gasification process.

2.4 Kinetic equation

Generally, the rate of solid-state reactions can be given by the equation:

(3)dαdt=Aexp−ERTf(α)

For the nonisothermal process, when the temperature rises at a constant rate (β=dT/dt), Equation (3) can be written as

(4)dαdT=Aβexp−ERTf(α)

where A and E are the kinetic parameters, the preexponential factor (1/min) and the activation energy (kJ/mol), respectively, and R is the universal gas constant (8.314 J/mol K), T is the thermodynamic temperature (K) and β is the heating rate (K/min), β=dT/dt.

2.5 The NL-INT method

The NL-INT method was proposed by Vyazovkin [20,21,22], and it can be used to calculate the credible activation energy without choosing the model functions by means of multistrip curves from different heating rates.

The integral formula of the abovementioned nonisothermal dynamic equation (Equation (4)) can be presented as follows:

(5)G(α)=∫0αdαf(α)=Aβ∫T0Texp−ERTdT≈Aβ∫0Texp−ERTdT=AβI(E,T)

where f(α) and G(α) are, respectively, the differential and integral forms of kinetic model functions and T0 is the initial reaction temperature (K).

Therefore, for a given conversion degree α and a series of experiments performed at different heating rates βi (i=1,…,n), it follows from Equation (6) that:

(6)Aβ1I(Eα,Tα,1)=Aβ2I(Eα,Tα,2)=⋯=AβnI(Eα,Tα,n)

Thereby, the Eα values can be determined by the minimizing evaluation function [20] as follows:

(7)Φ(Eα)=MIN∑i=1n∑j≠inI(Eα,Tα,i)βjI(Eα,Tα,j)βi−n(n−1)

where the temperature integral

(8)I(Eα,Tα)=∫0Tαexp−EαRTdT

is solved numerically by the fourth-order Senum–Yang approximation equation:

(9)ISY-4(E,T)=Texp(−u)⋅u3+18u2+86u+96u4+20u3+120u2+240u+120

where u=E/RT. The experimental data βi and Tα,i(i=1,2,3,…,n), based on the same conversion from a series of nonisothermal TG curves at different heating rates, can be substituted into Equation (7) to obtain the Eα values. The golden section method which is one-dimensional search optimization algorithm was employed for the solution of Equation (7). For the NL-INT method, since at least three curves are needed from three different heating rates, the Eα values are determined from four different heating rates for each type of the material in this study.

3 Results and discussion

3.1 Gasification characteristics of biochars and AC

To quantitatively describe the gasification characteristics of different samples, the parameters including the initial gasification temperature (Ti), the peak conversion temperature corresponding to the maximum conversion rate (Tp) and the final gasification temperature (Tf) were defined according to the previous research [24]. As shown in Figure 2, the initial gasification temperature (Ti), the peak conversion temperature (Tp) and the final gasification temperature (Tf) from the conversion curves and conversion rate curves were defined and evaluated using the graphic method as described in the literature [25]. First, through the conversion rate peak point A, a vertical line is made upward to intersect the conversion curve at point B, which corresponds to the peak conversion temperature (Tp). Second, a tangential line to conversion curve is made at point B, which meets the extended final-level line of conversion curve at point C and meets the initial-level line at point D. Third, another vertical line is made downward through point C, which corresponds to the final gasification temperature (Tf). The corresponding temperature of point D is defined as the initial gasification temperature (Ti).

Figure 2 Initial gasification temperature (Ti), the peak conversion temperature (Tp) and the final gasificition temperature (Tf).
Figure 2

Initial gasification temperature (Ti), the peak conversion temperature (Tp) and the final gasificition temperature (Tf).

Conversion degree and reaction rate curves of gasification of different biochars and anthracite at different heating rates are shown in Figure 3. It can be seen that with an increase in heating rate from 5 to 20 K/min, the curves of conversion ratio and reaction rate move toward the high temperature. By increasing the heating rate, the temperature corresponding to the same conversion ratio increases, whereas the conversion ratio corresponding to the same temperature decreases. The main reason is that the residence time in each temperature is shortened and the heat transfer hysteresis is strengthened with an increase in the heating rate. It can also be seen that the peak of the reaction rate curve increases by increasing the heating rate. The reason is that the total reaction time shortens when the heating rate increases.

Figure 3 Gasification curves of different carbonaceous materials with CO2: (a) SD-char; (b) WS-char; (c) RH-char; (d) BB-char and (e) AC.
Figure 3

Gasification curves of different carbonaceous materials with CO2: (a) SD-char; (b) WS-char; (c) RH-char; (d) BB-char and (e) AC.

Overall, for different samples (biochars and AC), the shape of these reaction curves is similar except the differences in the initial gasification temperature, final gasification temperature, peak conversion temperature and conversion rate during the gasification process. As can be seen in Figure 3, the gasification process of the different carbonaceous materials can be divided into three stages, using the conversion and reaction rate curves as shown in examples in Figure 3a, at the heating rate of 5 K/min. For the first stage, below the temperature of Ti, the conversion degree changes slowly and the conversion rate is low. The removal of volatiles is dominant and it almost ends at this stage. In the second stage, carbon gasification mainly occurs with CO2 and weight loss occurs rapidly, and a peak can be observed in the reaction rate curve. For the third stage, above the temperature of Tf, the carbon gasification is almost over and the mass of residue tends to be constant. Gasification and weight loss mainly occur in the second stage. The gasification characteristic parameters of the different carbonaceous materials are shown in Table 2. It can be seen that the order of Ti and Tp for the samples is, from high to low, AC, BB-char, RH-char, SD-char and WS-char. Whereas Tf of the samples has a different order which is AC, RH-char, BB-char, WS-char and SD-char. At the same time, the order of maximum reaction rate for these samples is, from high to low, WS-char, SD-char, BB-char, RH-char and AC. Therefore, the gasification reactivity cannot be described only by means of Ti and Tf. In order to describe the gasification reactivity of the different carbonaceous materials, the comprehensive gasification characteristic index S is used for this work. The equation of index S can be written as follows [11,26,27]:

(10)S=(dα/dt)max⋅(dα/dt)meanTi2⋅Tf

where (dα/dt)max and (dα/dt)mean are the maximum and average gasification reaction rates, respectively. As shown in Table 2, the index S of different samples from high to low can be sorted as that of WS-char, SD-char, BB-char, RH-char and AC. Thus, from high to low, the gasification reactivity of five samples can be ranked as that of WS-char, SD-char, BB-char, RH-char and AC. Meanwhile, the maximum and average reaction rates of five carbon samples have almost the same sequence. Therefore, the index S is mainly determined by the reaction rate. According to the literature [11], the carbon crystalline structure of carbonaceous materials plays an important role in carbon gasification reactivity. The carbon structure of biochars is mostly amorphous carbon structure and the structure of anthracite is graphitic carbon. The gasification reactivity of carbonaceous materials decreases with an increase in the graphitization degree of its carbon structure.

Table 2

Gasification characteristic parameters of different samples

SamplesHeating rate (K/min)Ti (K)Tp (K)Tf (K)dα/dtmax (1/min)dα/dtmean (1/min)S×1012
SD-char51043.81140.81159.10.073780.008720.52
101103.91194.41222.80.119530.015891.30
151123.41221.91247.90.172000.022972.56
201135.41244.61284.20.175010.029013.16
WS-char51008.01089.81182.30.092070.008450.70
101086.41136.31232.60.175000.015702.05
151105.61161.21289.40.218710.021643.33
201117.21176.91297.30.248640.028584.84
RH-char51122.81212.31257.20.039850.007560.20
101164.81266.51313.80.071600.013930.58
151180.01280.21332.20.106220.020381.21
201200.41319.11377.90.122010.025601.64
BB-char51135.01223.81239.80.073900.007810.37
101173.51271.11292.20.116000.014450.96
151193.11289.11316.20.157600.020911.80
201218.91340.51373.80.151340.025731.96
AC51215.91313.81384.80.031510.006110.10
101260.01378.21444.90.057940.011210.30
151280.21410.31465.70.076870.015510.52
201296.11423.51492.40.098890.020470.85

3.2 Kinetic analysis

According to a series of conversion curves at the heating rates of 5, 10, 15 and 20 K/min, the Eα values corresponding to each conversion degree of gasification for different carbonaceous materials were obtained by means of the NL-INT method. By plotting the numerical Eα values against the corresponding conversion degree, α, a dependence of activation energy upon conversion has been manifested in Figure 4. It can be seen that the Eα values of biochars increase generally with an increase in the conversion degree, whereas the value of AC decreases from 314 to 180 kJ/mol in the early stage of gasification. Except for AC, the activation energy sequence of the four biochars is basically unchanged and the order from low to high is WS-char, SD-char, RH-char and BB-char. However, as the conversion degree increases to more than 0.3, the activation energy value of AC becomes lower than that of RH-char and BB-char. It can be explained that the pyrolysis of volatiles in AC induces the significant increase in the specific surface area and active points at the early stages of gasification. By contrast, due to the pre-pyrolysis, the volatile matter content of the biochars is lower than that of AC, and the pore structure of the biochars has been well developed. The volatile matter content should not be the main factor affecting the gasification of biochars. On the other hand, when the conversion degree is lower than 0.3, the gasification reaction of carbon with CO2 does not take place appreciably and the residual volatile matter in the chars is pyrolyzed slowly. Structural ordering, carbonization, existing pore collapse and micropore coalescence led to a decrease in the surface area and thermal deactivation of the chars [28]. When the conversion degree is up to some extent, the removal of volatile matter comes to an end and carbon gasification develops, resulting in the immutability of Eα value for different materials. For AC, RH-char and BB-char, the values of Eα remain nearly unchanged when the conversion degree is in the range of 0.25–0.95. While for SD-char and WS-char, the corresponding range of conversion is 0.30<α<0.90. Therefore, at a certain range of conversion degree, the activation energy is nearly independent of the conversion degree, and a single reaction mechanism function can be used for describing the gasification of each biochar or AC. It can also be obtained that, at the range of 0.30<α<0.90, the mean values of Eα from low to high can be sorted as that of WS-char, SD-char, AC, RH-char and BB-char, respectively, 134.3, 143.8, 168.5, 184.8 and 193.0 kJ/mol.

Figure 4 Relation between activation energy and conversion for different biochars and anthracite.
Figure 4

Relation between activation energy and conversion for different biochars and anthracite.

It is well-known that combustion and gasification of char involve a gas–solid reaction. In general, the kinetic models include the VM, URCM and RPM, which are used to describe the gas–solid reaction [12,29]. The governing equations of RPM have been developed for the first-order reaction by Bhatia and Perlmutter [18,19]. In the RPM model, the pore size distribution and the pore structure and its evolution were taken into account during the reaction process. It was confirmed that the RPM is suitable for describing the gasification of biochars. In this work, based on the activation energy values from the NL-INT method, the RPM was used to evaluate the kinetic parameters of gasification. The mechanism functions of the RPM can be written as follows:

(11)f(α)=(1−α)1−ψln(1−α)

where ψ is the pore structure parameter. Thus, the differential and integral expressions of nonisothermal kinetic equations can be given as follows:

(12)dαdT=Aβexp−ERTf(α)
(13)∫0αdαf(α)=Aβ∫T0Texp−ERTdT

With regard to Equation (13), the integral on the right-hand side of the equation is an unconventional integral which was written as an approximate expression by Coats and Redfern [30] and Marini et al. [31] as follows:

(14)Aβ∫T0Texp−ERTdT=ARβET21−2RTEexp−ERT−T021−2RT0Eexp−ERT0

where T0 is the starting temperature of reaction, K. Combining Equations (11)–(14) followed by integrating, the dependence of conversion α on temperature T can be given as Equation (15):

(15)α=1−exp1−1+ψARPMR2βET21−2RTEexp−ERT−T021−2RT0Eexp−ERT02ψ

where ARPM denotes the preexponential factor (1/min) in kinetic equation of RPM.

In the previous studies, the parameters Eα and A were simultaneously obtained by using the model-fitting methods. However, in this study, based on the mean Eα values from the NL-INT method, Equation (15) is used to solve the kinetic parameters including A and ψ from experimental data by means of nonlinear least squares fitting methods. Table 3 shows the mean Eα values calculated by using the NL-INT method and the fitted parameters (A and ψ) determined from the data obtained at different heating rates for each sample. Figure 5 shows a comparison of experimental and fitted conversion degree as a function of reaction temperature for (a) SD-char, (b) WS-char, (c) RH-char, (d) BB-char and (e) AC. Overall, the RPM fits the experimental data well for the different samples due to the high R2 values. However, the RPM cannot describe very well the gasification of the samples in the initial stage (α<0.3). Especially for WS-char, the R2 for the fitted and experimental conversion curves at heating rate of 5 K/min gets the minimum value of 0.9768. This is related to the variation in activation energy value in the initial stage of gasification. This indicates that a complex multistep mechanism occurs in the initial stage of gasification. On the contrary, thereafter, it seems to be true that there is a single-step gasification mechanism for the rest of the gasification process.

Table 3

Kinetic parameters fitted to Equation (15) for the gasification reaction of different samples

Sampleβ (K/min)E (kJ/mol)RPM
A(1/min)ψR2lnA
SD-char5143.83.6705 × 1050.96050.989212.8133
102.3519 × 1054.62810.996712.3681
152.6708 × 1054.10160.996412.4953
203.2428 × 1051.83200.996212.6894
WS-char5134.32.3803 × 1050.41570.976812.3802
106.2551 × 10439.52790.996411.0437
158.4914 × 10421.91380.996211.3494
209.7843 × 10420.30930.996011.4911
RH-char5184.81.0778 × 1070.30130.993816.1930
109.6694 × 1060.23390.993916.0845
151.1121 × 1070.39990.994216.2243
209.1348 × 1060.21370.995516.0276
BB-char5193.01.9663 × 1071.39520.995016.7942
101.9145 × 1071.12090.994916.7676
151.9810 × 1071.40220.995016.8017
201.7234 × 1070.23060.991416.6624
AC5168.52.9166 × 1050.81980.994712.5833
103.0077 × 1050.55140.990712.6141
153.3362 × 1050.19630.987012.7178
203.6102 × 1050.21720.984212.7967
Figure 5 Experimental and fitted conversions for different biochars and anthracite during gasification with CO2: (a) SD-char; (b) WS-char; (c) RH-char; (d) BB-char and (e) AC.
Figure 5

Experimental and fitted conversions for different biochars and anthracite during gasification with CO2: (a) SD-char; (b) WS-char; (c) RH-char; (d) BB-char and (e) AC.

Comparing the mean activation energy with the reactivity of char gasification, it can be seen that the order is different. The main reason is that the gasification reaction rate is determined by both activation energy (E) and preexponential factor (A) as shown in Equation (3). Even so, it is quite clear that by increasing the preexponential factor and decreasing the activation energy, the gasification reaction rate increases. Thus, although the activation energy of AC decreases to be lower than that of RH and BB, its lower preexponential factor leads to a lower reaction rate. Furthermore, the relation of the mean value of logarithmic preexponential factor and the activation energy value Eα for the gasification of different chars under different heating rates is shown in Figure 6. The clear linear relationship between ln A and E is the well-known kinetic compensation effect (KCE), which is caused by fitting a conversion curve at a single-heating rate by using single kinetic function model-fitting method based on the Arrhenius equation [32]. Thus, the expression of KCE in this study can be given as:

(16)lnA=0.085E−0.07054

From Figure 6, it can also be observed that the biomass chars maintain strong correlation and the AC deviates from the KCE curve. This could be due to the similarity of carbonaceous structure of biochars and the difference in reactivity between biochars and AC. This also means that the KCE exists in the same or similar types of reactions under the same experimental conditions for the same type of materials, i.e., they have the same or similar reaction mechanisms.

Figure 6 Relation between the values of apparent activation energy and preexponential factor for different biochars and AC.
Figure 6

Relation between the values of apparent activation energy and preexponential factor for different biochars and AC.

4 Conclusions

In this work, the gasification behavior of different biomass chars and AC with CO2 was investigated by nonisothermal TGA. The dependence of activation energy upon the conversion of gasification for different biochars and AC was achieved by using the NL-INT method which is a model-free method. Based on the activation energy values from the NL-INT method, the kinetic parameters of gasification of different chars with CO2 were obtained using the RPM. The results obtained can be summarized as follows:

  1. The comprehensive gasification characteristic index S can well represent the gasification characteristics of different carbon materials. The CO2 gasification reactivity of different biomass chars and anthracite from high to low can be sorted as that of WS-char, SD-char, BB-char, RH-char and AC. The gasification reactivity of biochars is stronger than that of anthracite.

  2. In the initial stage of gasification, the activation energy values of biochars increase generally with increasing conversion degree, whereas the value of AC decreases. However, the values remain almost unchanged when the conversion degree is up to some extent. At the range of 0.30<α<0.90, the mean values of Eα from low to high can be sorted as that of WS-char, SD-char, AC, RH-char and BB-char, respectively, 134.3, 143.8, 168.5, 184.8 and 193.0 kJ/mol. It is shown that a complex multistep mechanism occurs in the initial stage of gasification, while a single-step gasification mechanism exists in the rest of the gasification process.

  3. The RPM as a model-fitting method is suitable for describing the gasification of biomass chars and AC except the initial gasification. It is found that the KCE exists in the gasification reactions of biochars and AC. However, the AC deviates markedly from the KCE curve. This could be due to the similarity of carbonaceous structure of biochars and the difference in reactivity between biochars and AC.

Acknowledgments

This research was supported by the Open Project of Anhui Province Key Laboratory of Metallurgical Engineering & Resources Recycling (Anhui University of Technology) (SKF18-03) and the PhD start-up fund of Jiangsu University of Science and Technology (120140004) in China.

References

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Received: 2020-05-06
Revised: 2020-07-25
Accepted: 2020-08-07
Published Online: 2020-10-02

© 2020 Bing Dai et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Research Article
  2. Electrochemical reduction mechanism of several oxides of refractory metals in FClNaKmelts
  3. Study on the Appropriate Production Parameters of a Gas-injection Blast Furnace
  4. Microstructure, phase composition and oxidation behavior of porous Ti-Si-Mo intermetallic compounds fabricated by reactive synthesis
  5. Significant Influence of Welding Heat Input on the Microstructural Characteristics and Mechanical Properties of the Simulated CGHAZ in High Nitrogen V-Alloyed Steel
  6. Preparation of WC-TiC-Ni3Al-CaF2 functionally graded self-lubricating tool material by microwave sintering and its cutting performance
  7. Research on Electromagnetic Sensitivity Properties of Sodium Chloride during Microwave Heating
  8. Effect of deformation temperature on mechanical properties and microstructure of TWIP steel for expansion tube
  9. Effect of Cooling Rate on Crystallization Behavior of CaO-SiO2-MgO-Cr2O3 Based Slag
  10. Effects of metallurgical factors on reticular crack formations in Nb-bearing pipeline steel
  11. Investigation on microstructure and its transformation mechanisms of B2O3-SiO2-Al2O3-CaO brazing flux system
  12. Energy Conservation and CO2 Abatement Potential of a Gas-injection Blast Furnace
  13. Experimental validation of the reaction mechanism models of dechlorination and [Zn] reclaiming in the roasting steelmaking zinc-rich dust process
  14. Effect of substituting fine rutile of the flux with nano TiO2 on the improvement of mass transfer efficiency and the reduction of welding fumes in the stainless steel SMAW electrode
  15. Microstructure evolution and mechanical properties of Hastelloy X alloy produced by Selective Laser Melting
  16. Study on the structure activity relationship of the crystal MOF-5 synthesis, thermal stability and N2 adsorption property
  17. Laser pressure welding of Al-Li alloy 2198: effect of welding parameters on fusion zone characteristics associated with mechanical properties
  18. Microstructural evolution during high-temperature tensile creep at 1,500°C of a MoSiBTiC alloy
  19. Effects of different deoxidization methods on high-temperature physical properties of high-strength low-alloy steels
  20. Solidification pathways and phase equilibria in the Mo–Ti–C ternary system
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  23. Improving mechanical properties of ZK60 magnesium alloy by cryogenic treatment before hot extrusion
  24. Temperature-dependent proportional limit stress of SiC/SiC fiber-reinforced ceramic-matrix composites
  25. Effect of 2CaO·SiO2 particles addition on dephosphorization behavior
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  29. Sulphur and vanadium-induced high-temperature corrosion behaviour of different regions of SMAW weldment in ASTM SA 210 GrA1 boiler tube steel
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  33. Influence mechanism of pulse frequency on the corrosion resistance of Cu–Zn binary alloy
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  48. Development and experimental research of a low-thermal asphalt material for grouting leakage blocking
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  50. Microstructure evolution of TC4 powder by spark plasma sintering after hot deformation
  51. The effect of M (M = Ce, Zr, Ce–Zr) on rolling microstructure and mechanical properties of FH40
  52. Phase evolution and oxidation characteristics of the Nd–Fe–B and Ce–Fe–B magnet scrap powder during the roasting process
  53. Assessment of impact mechanical behaviors of rock-like materials heated at 1,000°C
  54. Effects of solution and aging treatment parameters on the microstructure evolution of Ti–10V–2Fe–3Al alloy
  55. Effect of adding yttrium on precipitation behaviors of inclusions in E690 ultra high strength offshore platform steel
  56. Dephosphorization of hot metal using rare earth oxide-containing slags
  57. Kinetic analysis of CO2 gasification of biochar and anthracite based on integral isoconversional nonlinear method
  58. Optimization of heat treatment of glass-ceramics made from blast furnace slag
  59. Study on microstructure and mechanical properties of P92 steel after high-temperature long-term aging at 650°C
  60. Effects of rotational speed on the Al0.3CoCrCu0.3FeNi high-entropy alloy by friction stir welding
  61. The investigation on the middle period dephosphorization in 70t converter
  62. Effect of cerium on the initiation of pitting corrosion of 444-type heat-resistant ferritic stainless steel
  63. Effects of quenching and partitioning (Q&P) technology on microstructure and mechanical properties of VC particulate reinforced wear-resistant alloy
  64. Study on the erosion of Mo/ZrO2 alloys in glass melting process
  65. Effect of Nb addition on the solidification structure of Fe–Mn–C–Al twin-induced plasticity steel
  66. Damage accumulation and lifetime prediction of fiber-reinforced ceramic-matrix composites under thermomechanical fatigue loading
  67. Morphology evolution and quantitative analysis of β-MoO3 and α-MoO3
  68. Microstructure of metatitanic acid and its transformation to rutile titanium dioxide
  69. Numerical simulation of nickel-based alloys’ welding transient stress using various cooling techniques
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  72. Review Article
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https://doi.org/10.1515/htmp-2020-0086
Keywords for this article
biochar; gasification; integral isoconversional nonlinear method; random pore model; kinetic compensation effect
Creative Commons
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Articles in the same Issue

  1. Research Article
  2. Electrochemical reduction mechanism of several oxides of refractory metals in FClNaKmelts
  3. Study on the Appropriate Production Parameters of a Gas-injection Blast Furnace
  4. Microstructure, phase composition and oxidation behavior of porous Ti-Si-Mo intermetallic compounds fabricated by reactive synthesis
  5. Significant Influence of Welding Heat Input on the Microstructural Characteristics and Mechanical Properties of the Simulated CGHAZ in High Nitrogen V-Alloyed Steel
  6. Preparation of WC-TiC-Ni3Al-CaF2 functionally graded self-lubricating tool material by microwave sintering and its cutting performance
  7. Research on Electromagnetic Sensitivity Properties of Sodium Chloride during Microwave Heating
  8. Effect of deformation temperature on mechanical properties and microstructure of TWIP steel for expansion tube
  9. Effect of Cooling Rate on Crystallization Behavior of CaO-SiO2-MgO-Cr2O3 Based Slag
  10. Effects of metallurgical factors on reticular crack formations in Nb-bearing pipeline steel
  11. Investigation on microstructure and its transformation mechanisms of B2O3-SiO2-Al2O3-CaO brazing flux system
  12. Energy Conservation and CO2 Abatement Potential of a Gas-injection Blast Furnace
  13. Experimental validation of the reaction mechanism models of dechlorination and [Zn] reclaiming in the roasting steelmaking zinc-rich dust process
  14. Effect of substituting fine rutile of the flux with nano TiO2 on the improvement of mass transfer efficiency and the reduction of welding fumes in the stainless steel SMAW electrode
  15. Microstructure evolution and mechanical properties of Hastelloy X alloy produced by Selective Laser Melting
  16. Study on the structure activity relationship of the crystal MOF-5 synthesis, thermal stability and N2 adsorption property
  17. Laser pressure welding of Al-Li alloy 2198: effect of welding parameters on fusion zone characteristics associated with mechanical properties
  18. Microstructural evolution during high-temperature tensile creep at 1,500°C of a MoSiBTiC alloy
  19. Effects of different deoxidization methods on high-temperature physical properties of high-strength low-alloy steels
  20. Solidification pathways and phase equilibria in the Mo–Ti–C ternary system
  21. Influence of normalizing and tempering temperatures on the creep properties of P92 steel
  22. Effect of temperature on matrix multicracking evolution of C/SiC fiber-reinforced ceramic-matrix composites
  23. Improving mechanical properties of ZK60 magnesium alloy by cryogenic treatment before hot extrusion
  24. Temperature-dependent proportional limit stress of SiC/SiC fiber-reinforced ceramic-matrix composites
  25. Effect of 2CaO·SiO2 particles addition on dephosphorization behavior
  26. Influence of processing parameters on slab stickers during continuous casting
  27. Influence of Al deoxidation on the formation of acicular ferrite in steel containing La
  28. The effects of β-Si3N4 on the formation and oxidation of β-SiAlON
  29. Sulphur and vanadium-induced high-temperature corrosion behaviour of different regions of SMAW weldment in ASTM SA 210 GrA1 boiler tube steel
  30. Structural evidence of complex formation in liquid Pb–Te alloys
  31. Microstructure evolution of roll core during the preparation of composite roll by electroslag remelting cladding technology
  32. Improvement of toughness and hardness in BR1500HS steel by ultrafine martensite
  33. Influence mechanism of pulse frequency on the corrosion resistance of Cu–Zn binary alloy
  34. An interpretation on the thermodynamic properties of liquid Pb–Te alloys
  35. Dynamic continuous cooling transformation, microstructure and mechanical properties of medium-carbon carbide-free bainitic steel
  36. Influence of electrode tip diameter on metallurgical and mechanical aspects of spot welded duplex stainless steel
  37. Effect of multi-pass deformation on microstructure evolution of spark plasma sintered TC4 titanium alloy
  38. Corrosion behaviors of 316 stainless steel and Inconel 625 alloy in chloride molten salts for solar energy storage
  39. Determination of chromium valence state in the CaO–SiO2–FeO–MgO–CrOx system by X-ray photoelectron spectroscopy
  40. Electric discharge method of synthesis of carbon and metal–carbon nanomaterials
  41. Effect of high-frequency electromagnetic field on microstructure of mold flux
  42. Effect of hydrothermal coupling on energy evolution, damage, and microscopic characteristics of sandstone
  43. Effect of radiative heat loss on thermal diffusivity evaluated using normalized logarithmic method in laser flash technique
  44. Kinetics of iron removal from quartz under ultrasound-assisted leaching
  45. Oxidizability characterization of slag system on the thermodynamic model of superalloy desulfurization
  46. Influence of polyvinyl alcohol–glutaraldehyde on properties of thermal insulation pipe from blast furnace slag fiber
  47. Evolution of nonmetallic inclusions in pipeline steel during LF and VD refining process
  48. Development and experimental research of a low-thermal asphalt material for grouting leakage blocking
  49. A downscaling cold model for solid flow behaviour in a top gas recycling-oxygen blast furnace
  50. Microstructure evolution of TC4 powder by spark plasma sintering after hot deformation
  51. The effect of M (M = Ce, Zr, Ce–Zr) on rolling microstructure and mechanical properties of FH40
  52. Phase evolution and oxidation characteristics of the Nd–Fe–B and Ce–Fe–B magnet scrap powder during the roasting process
  53. Assessment of impact mechanical behaviors of rock-like materials heated at 1,000°C
  54. Effects of solution and aging treatment parameters on the microstructure evolution of Ti–10V–2Fe–3Al alloy
  55. Effect of adding yttrium on precipitation behaviors of inclusions in E690 ultra high strength offshore platform steel
  56. Dephosphorization of hot metal using rare earth oxide-containing slags
  57. Kinetic analysis of CO2 gasification of biochar and anthracite based on integral isoconversional nonlinear method
  58. Optimization of heat treatment of glass-ceramics made from blast furnace slag
  59. Study on microstructure and mechanical properties of P92 steel after high-temperature long-term aging at 650°C
  60. Effects of rotational speed on the Al0.3CoCrCu0.3FeNi high-entropy alloy by friction stir welding
  61. The investigation on the middle period dephosphorization in 70t converter
  62. Effect of cerium on the initiation of pitting corrosion of 444-type heat-resistant ferritic stainless steel
  63. Effects of quenching and partitioning (Q&P) technology on microstructure and mechanical properties of VC particulate reinforced wear-resistant alloy
  64. Study on the erosion of Mo/ZrO2 alloys in glass melting process
  65. Effect of Nb addition on the solidification structure of Fe–Mn–C–Al twin-induced plasticity steel
  66. Damage accumulation and lifetime prediction of fiber-reinforced ceramic-matrix composites under thermomechanical fatigue loading
  67. Morphology evolution and quantitative analysis of β-MoO3 and α-MoO3
  68. Microstructure of metatitanic acid and its transformation to rutile titanium dioxide
  69. Numerical simulation of nickel-based alloys’ welding transient stress using various cooling techniques
  70. The local structure around Ge atoms in Ge-doped magnetite thin films
  71. Friction stir lap welding thin aluminum alloy sheets
  72. Review Article
  73. A review of end-point carbon prediction for BOF steelmaking process
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