Influence of Model Free Methods on Pyrolysis Kinetics and Thermodynamic Parameters of Soybean Straw

doi:10.21203/rs.3.rs-933372/v1

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Influence of Model Free Methods on Pyrolysis Kinetics and Thermodynamic Parameters of Soybean Straw

https://doi.org/10.21203/rs.3.rs-933372/v1

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Thermochemical conversion of surplus agro-residue for energy generation has gained renewed attention, due to its abundant availability throughout the world. Although, it still needs the thermodynamic and pyrolysis kinetic background, that play important role for the effectual design of thermo-chemical conversion reactors such as pyrolyzers, gasifiers, etc. In the present study, thermal profile (mass loss vs. temp) for soybean straw was examined at 20, 30, 40 ^oC/min heating rates under a non-isothermal condition in an oxygen limiting environment through a thermogravimetric analyzer (TGA). The pyrolysis kinetic parameters (activation energy and pre-exponential factor) were evaluated by applying iso-conversional model-free methods such as Flynn–Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), and Starink. The average values of activation energy for KAS, FWO and Starink models were recorded to be around 150, 155 and 147 kJ/mol, respectively. Thermodynamic variables (change of enthalpy, entropy, and Gibbs free energy) for soybean straw were also computed. The average value of enthalpy for FWO, KAS, Starink were recorded to be 151, 147, and 142 kJ/mol, respectively. The obtained simulation findings of pyrolysis kinetic and thermodynamic variables are in good agreement.

Molecular Biology

General Biochemistry

Soybean straw

Thermal analysis

Pyrolysis

Model free methods

Kinetic analysis

Enthalpy

Entropy

Gibbs free energy

Reaction mechanism

The proper utilization of surplus agro-residue has gained significant attention owing to its potential for energy generation. The most common agro-residue disposal processes such as incineration, landfill, and other agricultural applications are becoming intolerable because of stringent rules and regulations. Therefore, the conversion of biomass into energy fuels via thermochemical conversion process is recognised as an economically feasible and environmentally friendly option with many sustainable benefits. The agro-residue is recognized as organic renewable raw material for green fuel generation because of its salient features such as abundant availability, easy process, clean, with a lower sulfur and nitrogen compositions as compared to fossil resources. Among the thermochemical conversion techniques, pyrolysis process is regarded as one of the important biomass conversion processes where precursor material is heated in an oxygen-free condition at a moderate temperature of 400–600 ^oC for getting energetic bio-fuels such as char, bio-oil, and syngases (Amenaghawon et al. 2021). Biochar is refereed as organic carbon rich material and therefore it is widely used as a soil conditioner or as a catalyst for biofuel generation, while liquid oil and syngases can be used as an alternate fuel or for power generation because of their higher heating value. Biomass pyrolysis is a heterogeneous complex thermochemical conversion process where some physicochemical changes are occurred due to the occurrence of simultaneous competing reactions. Thus, investigation on pyrolysis kinetic of biomass is becoming very crucial to understand the reaction chemistry, thermal behaviour, and for obtaining the desired products by optimizing different parameters.

Soybean (Glycine max (L.) Merr) straw is a lignocellulosic fibrous residue of agricultural crop soybean which is taken worldwide. The annual production of soybean is about 315 million tons and an equivalent amount of by-products especially straw is produced throughout the world (Toro-Trochez et al. 2019). Husk indicates 10% of the weight of the soybean crop and is mainly referred to as waste. A large quantity of surplus straw is not being managed properly but is mostly burnt in an open field by some peasants, which causes a serious environmental problem. Revalorization of soybean straw using thermochemical conversion route i.e., pyrolysis is projected to be an alternative promising option, at the time of minimizing the adverse effects of the current waste management problem.

However, pyrolysis of soybean straw on an extensive platform is becoming very crucial to understand its pyrolysis kinetics. In addition, thermal analysis of biomass (mass loss Vs. temp) and knowledge of thermodynamic parameters are very imperative for CFD modeling, design of reactors, process optimization, and energy balance. Kinetic analysis of biomass is comprising of a two-stage process, first contains decomposition of biomass through pyrolysis process for getting the reaction progression data, and second involves obtaining kinetic triplet (pre-exponential factor, activation energy, and reaction model) by performing computational mathematics. As lignocellulosic biomass used in the present study i.e., soybean straw which is subjected for pyrolysis to know its decomposition pattern relative to its operating temperature. Each constituent of soybean straw degrades at a different range of temperatures with a distinct range of complex reactions. The lignin constituent is considered as more refractory as compare to cellulose and hemicellulose, due to the availability of functional groups it possesses wide dispersed thermal stability, and therefore it needs higher pyrolysis temperature (433–1173 K) for its thermal decomposition (Zhang et al. 2018). As a result, apparent kinetic parameters are varying in the reacting system during the whole reaction process. For this a model-free or iso-conversional methods are regarded as well suited for performing the kinetic analysis. Non-isothermal condition for TG-DTG analysis is referred to as significant condition for computing the pyrolysis kinetics and thermodynamic variables. The International Confederation of Thermal Analysis and Calorimetry (ICTAC) recommended in 2011 (Vyazovkin et al. 2011) and 2014 (Vyazovkin et al. 2014), are the main causes for getting an improved attention on iso-conversional methods.

In the present work, pyrolysis kinetics of soybean straw was performed at 20, 30, and 40 ^oC/min heating rates under a nitrogen atmosphere using TGA technique. The kinetic parameters were estimated using iso-conversional models like Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), and Starink. The obtained values of activation energy were also used for calculating the thermodynamic parameters such as enthalpy, entropy, and Gibbs free energy. In addition, the proximate, ultimate analysis, higher heating value, and thermal degradation analysis were also performed for soybean straw biomass using the different analytical techniques.

2.1 Raw Material

Soybean straws were collected from the oil seed research station of Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola. It was ground using a hammer mill to obtain a particle size of 200–400 µm and afterwards oven drying at 110 ^oC for 24 h. Then the dried sample was placed in an airtight container to restrict the absorption of atmospheric moisture. Figure 1 indicates the images of raw soybean straw and its dried powder.

<< Fig. 1 >>

2.2 Methods

2.2.1 Proximate, ultimate analysis, and higher heating value

Proximate analysis of soybean straw was conducted by determining the moisture content, volatile matter, fixed carbon, and ash content as per procedure suggested by Cai et al (2017). The ultimate analysis of precursor viz., total carbon, nitrogen, oxygen, hydrogen and sulfur composition were estimated by using an elemental analyzer. The calorific value of soybean straw was calculated using a microprocessor digital bomb calorimeter.

2.2.2 Thermo and differential thermogravimetric analysis

TG-DTG analysis of soybean straw was performed in a TG-DTG unit (Model: STA 7300, make: Hitachi) for obtaining the thermal degradation curves or patterns. The weighed quantity of soybean powder was heated from 30 to 800^oC at 20, 30, and 40 ^oC/min heating rates under a nitrogen atmosphere by keeping a flow rate of 95 ml/min, nitrogen as an inert gas was used to move the air present into pyrolysis chamber, thus averting the combustion of the sample. The obtained thermal degradation data was further used to estimate the kinetic parameters of biomass pyrolysis.

2.3 Kinetic analysis

Pyrolysis of lignocellulosic biomass is referred to as a complex method where multiple reactions are involved. A complete kinetic analysis is usually not practicable for a complex system, but some types of regular or efficient kinetic analysis are still needed. The pyrolysis kinetics of soybean straw was executed using the iso-conversional method. A widely preferred global reaction is used to understand the kinetic description of biomass pyrolysis process as represented in (Eq. 1):

\(\text{B}\text{i}\text{o}\text{m}\text{a}\text{s}\text{s}\to \text{C}\text{h}\text{a}\text{r} + \text{V}\text{o}\text{l}\text{a}\text{t}\text{i}\text{l}\text{e}\text{s}\) ...... (Eq. 1)

From Arrhenius equation, the rate of biomass conversion can be expressed as;

\(\frac{\text{d}{\alpha }}{\text{d}\text{t}} =\text{A}{\text{e}}^{-\frac{\text{E}}{\text{R}\text{T}}} \text{f}\left({\alpha }\right)\) .... (Eq. 2)

Where the main components in Eq. (2) are activation energy (E), reaction model [F (\({\alpha }\))], and pre-exponential factor (A), while the remaining elements are the degree of conversion (\({\alpha }\)), reaction temperature (t), and universal gas constant (R), respectively. The activation energy of biomass is the amount of energy required to stimulate the biomass to an energetic state, where the reaction occurs. Activate energy is generally used for breaking the bonds within the structure, and making a transition state complex, where further reactions occur on their own. Pre-exponential factor is also referred to as ‘frequency factor’, where a number of collisions took place with respect to time for maintaining a proper orientation during the reaction. The reaction model is a model-based function [f(α) = (1- α) ⁿ], which shows the quantitative relationship between the extent of conversion and the degree of conversion. The mass loss data for soybean straw was converted into a degree of conversion (α) as,

\({\alpha }= \frac{{\text{m}}_{\text{o}}-{\text{m}}_{\text{t}}}{{\text{m}}_{\text{o}}-{\text{m}}_{\text{f}}}\) ...... (Eq. 3)

Where,

α = Degree of conversion,

m_o = Initial weight of biomass sample,

m_t = Weight of sample after pyrolysis at a time t,

m_f = Weight of char after biomass pyrolysis

Generally, during thermal analysis the reaction temperature (T) raises with time (t) at a constant heating rate under anaerobic atmosphere and this heating rate i.e. β (^oC/ min), can be described as in Eq. 4;

\({\beta }= \frac{\text{d}\text{T}}{\text{d}\text{t}}\) ....... (Eq. 4)

Merging Eqs. (2) & (4) offers an Eq. (5),

\({\beta } \frac{\text{d}{\alpha }}{\text{d}\text{t}}=\text{A}{e}^{-\left(\frac{\text{E}}{\text{R}\text{T}}\right)} {\text{f}(1-{\alpha })}^{n}\) ....... (Eq. 5)

Equation (5) integrated with respect to temperature from T = T₀ and T = T gives,

\(\text{g}\left({\alpha }\right)= \underset{0}{\overset{{\alpha }}{\int }}\frac{\text{d}{\alpha }}{{(1-\alpha )}^{n}}= \frac{\text{A}}{{\beta }} \underset{\text{T}}{\overset{{T}_{0}}{\int }}{e}^{-\left(\frac{\text{E}}{\text{R}\text{T}}\right)} \text{d}\text{T}\) ........ (Eq. 6)

The Eq. (6) is very useful while carrying out the kinetic calculations, whereas the difference between reference temperature and biomass pyrolysis temperature should be insignificant.

2.4 Iso-conversional models

The obtained TG-DTG data at 20, 30, 40 ^oC/min of heating rate was further used for the estimation of activation energy values by adopting the iso-conversional or model-free methods such as Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), and Starink method. As per ICTAC report, FWO and KAS are the most effective and precise methods for the calculations of kinetic parameters (Vyazovkin et al., 2011). These models can determine the activation energy value on a model-free basis. The obtained activate energy values were used further for the evaluation of the pre-exponential factor, and estimating the reaction model. Iso-conversional methods are mainly categorized into an integral and differential methods. Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), and Starink are mainly regarded as integral methods while the Friedman model is coming under a differential method (Cai et al. 2018).

2.4.1 Flynn-Wall-Ozawa (FWO) method

FWO integral model is considered as a extensively accepted method among the scientific community for calculating the thermal kinetic parameters. It undergoes a correlation of the activation energy, heating rate of the biomass, and inverse temperature, that was initially adopted by Doyle’s (Doyle 1965). The FWO model is represented by following Eq. (7) (Ozawa 1965)

\(\text{ln}\left({\beta }\right)=\text{ln}\left(\frac{\text{A}{\text{E}}_{\alpha }}{\text{R}\text{G}\left({\alpha }\right)}\right)-5.331-1.052 \left(\frac{\text{E}{\alpha }}{\text{R}\text{T}}\right)\) ..... (Eq. 7)

Here, activation energy is calculated corresponding to each degree of conversion by putting an inverse plot between log (β) and 1/T. At each degree of conversion, the values of activation energy are computed from the slope\(-1.052 \left(\frac{\text{E}{\alpha }}{\text{R}}\right)\)

2.4.2 Kissinger-Akahira-Sunose (KAS) method

The pyrolysis kinetics can be determined by the most widely assessed model-free method i.e. KAS, which is represented by following expression, Eq. (8) (Kissinger 1957, Akahira 1971)

\(\text{ln}\left(\frac{\beta }{{T}^{2}}\right)=\text{ln}\left[\frac{\text{A}\text{R}}{\text{E}{\alpha }\text{G}\left({\alpha }\right)}\right]-\frac{\text{E}{\alpha }}{\text{R}\text{T}}\) ...... (Eq. 8)

Where,

β = heating rate (K/min),

A = Pre-exponential factor (s^− 1)

a = conversion rate (computed by diving the loss mass by total mass of soybean straw),

G(a) = Decomposition mechanism

R = Gas constant (8.314 J/K.mol)

Here, the activation energy for each degree of conversion is calculated from the plot of the slope of an equation \(\text{ln}\left(\frac{{\beta }}{{\text{T}}^{2}}\right)\) VS. \(\frac{1}{\text{T}}\) .

2.4.3 Starink method

Activation energy can be computed in a Starink model by adopting the below expression Eq. (9) (Starink, 2003);

\(\text{ln}\left(\frac{\beta }{{T}^{1.92}}\right)=\text{c}\text{o}\text{n}\text{s}\text{t}.-1.0008 \frac{{\text{E}}_{{\alpha }}}{\text{R}\text{T}}\) ....... (Eq. 9)

Here, for each degree of conversion, a straight line is obtained due to the plotting of \(\text{ln}\left(\frac{\beta }{{T}^{1.92}}\right)\) VS 1/T. In addition, activation energy can be assessed from the slope − 1.0008 Ea/R for each degree of conversion.

2.5 Thermodynamic parameters

The FWO, KAS, and Starink models are adopted for obtaining the activation energy values for each degree of conversion and these methods can be further implemented for calculating the different thermodynamic parameters such as change of enthalpy (ΔH), pre-exponential factor (A), entropy change (ΔS), and Gibbs free energy change (ΔG), etc. with the aid of mentioned expressions like Eq. (10), (11), (12), and (13) respectively (Kumar 2020).

\(\varDelta \text{H}= {\text{E}}_{{\alpha } }– \text{R}\text{T}\) ...... (Eq. 10)

\(\text{A}= {\beta } {\text{E}}_{{\alpha }}\text{exp}\frac{\left(\frac{\text{E}{\alpha }}{{\text{R}\text{T}}_{\text{m}}}\right)}{\text{R}{\text{T}}_{\text{m}}^{2}}\) ....... (Eq. 11)

\(\varDelta \text{S}= \frac{\varDelta \text{H}-\varDelta \text{G}}{{\text{T}}_{\text{m}}}\) ....... (Eq. 12)

\(\varDelta \text{G}= {\text{E}}_{{\alpha }}+ \text{R}{\text{T}}_{\text{m} }\text{ln}\left(\frac{{{\text{T}}_{\text{m}}\text{k}}_{\text{B}}}{\text{h}\text{A}}\right)\) ....... (Eq. 13)

Here, Tm is addressed as a peak temperature in the DTG curve, while k_B and h are referred to as Boltzmann and plank constant, respectively.

3.1 Characteristics of soybean straw biomass

The proximate, ultimate analysis, lignocellulosic composition, and higher heating value of soybean straw were investigated using different analytical methods are listed in Table 1. The proximate analysis of soybean straw indicated that the agro residue has a more volatile matter of 74.05 ± 1.5 % while lower moisture, ash, and fixed carbon content to be around 9.0 ± 1.1, 6.54 ± 0.8, and 10.41 ± 1.3 %, respectively. Here, higher volatile content in agro residue showed its excellent thermal reactivity during the thermal decomposition process, easily devolatilize and leads increase in bio-oil production. Lower moisture content in soybean straw facilitates uniform heat distribution during the pyrolysis process. If the available moisture percentage in the feedstock is ≥ 10, more amount of auxiliary energy is needed to complete the pyrolysis process. Interestingly, a lower percentage of fixed carbon is showing a lower lignin composition in the agro residue. Soybean straw contains a low amount of ash, the proximate analysis of soybean straw well matches with another soybean straw feedstock as previously reported by Huang et al. (2016). The calorific value of soybean straw was observed to be about 14.00 MJ/kg, which found very closer to the other agricultural residues (Dos Santos et al. 2018; Leng et al. 2020)

Table 1

Characteristics of soybean straw biomass (% wt.)
Proximate analysis (% wt.) Present study		Huang et al. (2016)
Moisture content	9.0 ± 1.1	1.8
Volatile matter	74.05 ± 1.5	75.5
Ash content	6.54 ± 0.8	4.7
Fixed carbon content	10.41 ± 1.3,	19.8
Calorific value (MJ/kg)	17	19.71
Ultimate analysis (% wt.)
C	44.64 ± 0.02	47.8
H	6.79 ± 0.12	6.9
O (by difference)	47.53 ± 0.02	44.3
N	0.94 ± 0.01	1.0
S	0.10 ± 0.32	0.1
H:C ratio	1.34 ± 0.01	1.73
O:C ratio	0.83 ± 0.01	--
C: N ratio	52.98 ± 1.22	--
Lignocellulosic composition (% wt.)
Cellulose	37.21	--
Hemicelluloses	18.40	--
Lignin	2.12	--

Ultimate analysis results of soybean straw revealed that a percentage of oxygen to be around (47.53 ± 0.02%), carbon (44.64 ± 0.02%), hydrogen (6.79 ± 0.12%), and a negligible percentage of nitrogen (0.94 ± 0.01%), and sulfur content (0.10 ± 0.32%). While, hydrogen to carbon, oxygen to carbon, and nitrogen to carbon ratios were obtained using empirical formula are 1.34 ± 0.01, 0.83 ± 0.01, 52.98 ± 1.22. respectively. Higher oxygen to carbon ratio reduces the calorific value of the feedstock. However, a negligible percentage of sulfur and nitrogen in soybean straw results in lower emission of harmful gases (NOx, SOx) (Dhaundiyal et al. 2018). As it can be observed from Table 1, biochemical analysis of soybean straw including cellulose, hemicellulose, and lignin composition were found to be 37.21, 18.40, and 2.12 % respectively. The lignocellulosic composition of soybean straw was found comparable with some other soybean straw biomass previously studied by Huang et al. (2016).

<< Table 1 >>

3.2 Thermal decomposition behaviour of soybean straw

Soybean straw was thermally decomposed from ambient to 800^oC at 20, 30, and 40 ^oC/min heating rates in a TG furnace. The obtained TG and DTG curves for pyrolysis of soybean straw are shown in Fig. 2.

<< Fig. 2 >>

It can be seen that the thermal degradation (mass loss Vs. temp) of soybean straw took place or might be categorised into three different stages, the first stage is attributed to the drying zone, the second stage indicates the devolatilization zone, and the third stage corresponded to the char formation zone. The first zone ranging from 30 to 200 ^oC, which is mainly referred to as the dehydration stage also known as the passive zone, where very light volatiles were present and that showed the hygroscopic nature of feedstock (Said et al. 2013). From 30 to 110^oC, some unbound moisture was liberated, whereas from 110 to 200^oC bounded moisture as well as small amount extractives were released. The main decomposition of soybean straw took place between 200 to 400^oC, this zone is primarily known as the active pyrolysis zone where maximum mass loss (60–64%) was observed. The first peak in an active zone from 210 to 310^oC where hemicelluloses decompose while the second peak from 310 to 400^oC revealed the decomposition of cellulose. However, a strong peak between 200 to 400^oC was obtained at 320^oC, which may be regarded for pyrolysis of hemicellulose and cellulose (Yang et al. 2007). Taking after the second stage, a small shoulder between 400 to 550^oC was noticed, that should be corresponded to the degradation of lignin (Barneto et al. 2010). This stage is representing the passive zone of pyrolysis where minimum mass loss (1–4%) was observed. After 600^oC, the devolatilization curve was found almost constant, which was mainly considered as an end of pyrolysis process i. e. char formation zone. A similar thermal decomposition behaviour was also observed in a previous investigation on soybean straw by Huang et al. (2016).

3.3 Kinetic analysis

The pyrolysis kinetics of soybean straw was performed to evaluate the relation between the activation energy and degree of conversion using model-free methods such as FWO, KAS, and Starink at 20, 30, and 40 ^oC/min heating rates, where a conversion ranged from 0.1 to 0.9, respectively. The obtained data were further used for calculating the thermodynamic variables viz., change of enthalpy, entropy, and Gibbs free energy, respectively. The derivation of obtained activation energy values for three different models were found below 5%, justifying that the obtained activation energy values were reliable and might be supported by each other.

3.3.1 Evaluation of activation energy and pre-exponential factor

Here, linear Eq. (7) was used for the KAS model to calculate the activation energy values with the help of slope (− Eα/R) at a different conversion. Likewise, the activation energy values for FWO and Starink model were obtained using Eqs. (8) and (9), respectively. The calculated activation energy values relative to the degree of conversion using FWO, KAS, Starink models are listed in Table 2. The activate energy values for soybean straw were found in between 55–170 kJ/mol for a degree of conversion from 0.1 to 0.9 by adopting FWO, KAS, and Starink models. The average values of active energies derived from FWO, KAS, and Starink models were recorded to be around 155.34, 150.11, 147.17 kJ/mol respectively. The deviation was found below 5% for all three models, indicating that obtained activation energy values are more reliable. A nearly similar results was also obtained by Islam et al. (2015) for the pyrolysis of fruit hulls using FWO and KAS models.

Table 2

Apparent activation energy and pre-exponential factor of soybean straw relevant to the degree of conversion (α) at 20 ⁰C/min.
Conversion. Factor	FWO			KAS			STARINK
α	E_α (kJ/mol)	R²	A(s^− 1)	E_α(kJ/mol)	R²	A ( s^− 1)	E_α(kJ/mol)	R²	A (s^− 1)
0.10	158.31	0.9423	1.45 x 10¹⁷	153.66	0.9521	1.45 x 10¹⁵	150.32	0.9423	2.26 x 10¹⁰
0.20	169.32	0.9698	2.14x 10¹⁵	165.21	0.9569	2.47 x 10¹⁷	156.32	0.9565	2.05 x 10¹¹
0.30	172.32	0.9654	3.66 x 10¹⁷	168.23	0.9674	1.54 x 10¹⁵	163.23	0.9614	2.15 x 10¹¹
0.40	175.63	0.9785	1.76 x 10¹⁵	171.66	0.9632	2.26 x 10¹²	169.36	0.9696	1.45 x 10¹²
0.50	178.63	0.9865	1.21 x 10¹⁶	175.36	0.9698	2.68 x 10¹⁰	172.32	0.9785	1.41 x 10¹¹
0.60	160.32	0.9845	1.41 x 10¹⁴	168.23	0.9879	3.11 x 10¹⁵	170.33	0.9899	3.22 x 10⁰⁸
0.70	155.36	0.9941	1.41 x 10¹⁵	154.36	0.9785	2.12 x 10¹⁷	165.36	0.9841	2.64 x 10¹⁰
0.80	140.23	0.9952	1.41 x 10¹⁷	126.32	0.9894	2.09 x 10¹⁶	123.33	0.9914	1.44 x 10⁰⁹
0.90	88	0.9896	1.54 x 10¹⁶	68	0.9925	2.71 x 10¹⁴	54	0.9921	1.21 x 10⁰⁸
Average	155.3467			150.1144			147.1744

The obtained values of activating energies from three different methods were found highly dependent on the degree of conversion which signifies that pyrolysis of soybean straw is a complex process including multiple reactions. From Table 2, it was noticed that for all methods, the activation energy values were found to be increases from the conversion of 0.1 to 0.5, which means that endothermicity raises relative to the degree of conversion. Then after the conversion of 0.5 to 0.9 the values of Eα were found to drop, which justifies that the occurrence of exothermic reaction. For FWO conversion, activation energy values were increased from 158.31 to 178.63 kJ/mol for the conversion from 0.1 to 0.5, which might be because of degradation of hemicellulose and cellulose present in the feedstock. While as the degree of conversion increased from 0.5 to 0.9, then activate energy values were significantly reduced from 160 to 88 kJ/mol, respectively. A similar trend was also noticed in Eα values derived from KAS and Starink model. For the KAS model, the values of activate energies increased from 153.66 to 175.36 kJ/mol for the conversion of 0.1 to 0.5, as pyrolysis process proceeds, the activation energy found decreased from 168.23 to 68 kJ/mol with a conversion range of 0.6 to 0.9. Similarly, the values of Eα were observed to raise from 150.32 to 172.32 kJ/mol corresponding to the conversion from 0.1 to 0.5 and then activate energy values significantly reduced from 170.33 to 54 kJ/mol for a degree of conversion ranging from 0.6 to 0.9, respectively. Here, an increase in active energy values for a conversion range of 0.1 to 0.5 shows the presence of endothermicity reactions, while decreased values of Eα for a conversion from 0.6 to 0.9 were mainly attributed to the occurrence of exothermic reactions during soybean straw pyrolysis. The degree of conversion from 0.6 to 0.9, where pyrolysis temperature varied from 500 to 800^oC, corresponded to the degradation of lignin, and a small percentage of cellulose. As Vamvuka et al. (2003) noticed that maximum activation energy (145–285 kJ/mol) was needed for thermal decomposition of cellulose and hemicellulose, whereas the lowest activation energy was needed for lignin (30–139 kJ/mol), which may be the main reason for decreasing the Eα values for degree of conversion from 0.6 to 0.9. Based on the findings, it was observed that soybean straw required lower activation energy means a faster reaction rate because activation energy is simply defined as the smallest amount of energy needed to begin the reaction. Secondly, the soybean straw is considered as an agricultural by-product, which was mainly composed of lignocellulosic constituents that indicates less aromaticity, easily react and because of this, it shows minimum Eα value. Similar observations for activation energy were also reported in previous literature for pyrolysis of agricultural residues such as soybean straw, peanut shell, wheat straw, etc. (Huang et al. 2016; Varma et al. 2020; Rathore et al. 2021) In addition, for all three models the values of R² were found maximum for all degree of conversion signifies that obtained activate energy values are more accurate and reliable.

<< Table 2 >>

The Eα values obtained from FWO, KAS, and Starink methods were further adopted to evaluate the pre-exponential factor, as the pre-exponential factor is considered as one of the significant kinetic parameters to carry out a detailed kinetic study (White et al. 2011). Here, the pre-exponential factor was evaluated using Coats-Redfern method as represented in Eq. (6). Since, FWO, KAS, and Starink methods are referred to as reliable and therefore activate energy derived from these methods were well fitted to obtain the pre-exponential factor and reaction order. Calculated values of pre-exponential factors obtained from FWO, KAS, and Starink methods at 20, 30, and 40 ^oC/min heating rates using Eq. (6) are recorded in Table 2. From Table 2 it was observed that as pyrolysis temperature increased for all three models, the values of pre-exponential factor were also found to increase, which means that more complex reactions took place in a very short duration. Here, the values of pre-exponential factors obtained from FWO, KAS, and Starink were recorded between of 10⁹-10¹⁷ which signifies that thermal degradation of soybean straw becomes spontaneous at maximum temperature. The pre-exponential factor was estimated from intercept by using heating rate, activation energy, and gas constant. Pawar et al (2021) reported that discrepancy in values of a pre-exponential factor for all model’s links with the composition of biomass and due to more complex reaction undergoes during biomass pyrolysis. Whereas pre-exponential factor values as Aα is ≤ 10^{9 S−1}, the reactor indicates less reactivity, that means a low value of Aα links with a closed complex, whereas more the Aα (Aα ≥ 10^{9 S−1}) specify that a system possesses a simple complex with a extremely reactive system. Similar observations are also conveyed in a previous study by Havilah et al. (2021).

3.3.2 Analysis of Thermodynamic parameters

Thermodynamic variables have received great importance because of their application in small- and large-scale pyrolysis reactor optimization. Here, thermodynamic parameters such as change of enthalpy: ΔH; Gibbs free energy: ΔG; Change of entropy: ΔS with conversions were estimated from Eqs. (10), (12), and (13) corresponding to the values of Eα calculated from FWO, KAS, and Starink models are shown in Table 3.

Table 3

Thermodynamic parameters of soybean straw relevant to the degree of conversion (α) at 20 ⁰C/min.
FWO
α	ΔH*(kJ/mol)	ΔG* (kJ/mol)	ΔS* (J/mol.K)	ΔH*(kJ/mol)	ΔG*(kJ/mol)	ΔS*(J/mol.K)	ΔH*(kJ/mol)	ΔG*(kJ/mol)	ΔS*(J/mol.K)
0.10	150.23	166.98	-226.71	140.23	172.95	-207.44	140.21	168.95	-233.71
0.20	160.22	166.52	-84.99	154.36	172.54	-66.98	145.18	168.21	-98.84
0.30	163.21	165.91	84.90	163.23	172.1	72.31	153.63	167.89	66.26
0.40	174.36	165.65	114.93	175.89	171.95	103.13	160.25	167.89	93.33
0.50	178.63	165.23	130.14	170.23	171.65	116.58	165.69	167.59	112.27
0.60	160.23	165.21	82.77	164.89	171.23	69.45	158.36	167.36	65.27
0.70	148.96	164.91	78.21	153.21	171.2	64.52	145.63	167.12	61.83
0.80	135.23	164.21	69.23	132.23	170.96	55.08	136.36	166.58	56.35
0.90	91	164	63.67	70	170.21	50.52	80	166.12	46.35
Averages	151.34	165.40		147.14	171.64		142.81	167.52

<< Table 3 >>

<< Fig. 3 (a, b, c) >>

The change of enthalpy (ΔH) signifies the energy variance among the end products and reagents in a thermochemical reaction (Xu and Chen, 2013). For the FWO model, the value of ΔH increased from 150.23 to 178.63 kJ/mol with a degree of conversion from 0.1 to 0.5 and then reduced after conversion of 0.5. A similar leaning was noticed for the KAS, and Starink model, where enthalpy value hiked significantly, i.e., 140.23-170.23 kJ/mol and 140.21-165.69 kJ/mol with the function of conversion from 0.1 to 0.5 and then after 0.5 decreased. The average value of ΔH was recorded to be around 151, 147, and 143 kJ/mol for FWO, KAS, and Starink methods, respectively. Figure 3 (a) indicates progress of the ΔH relative to degree of conversions. The rise in enthalpy value for all models corresponding to its degree of conversion up to 0.5, mainly due to the starting of an endothermic reaction. After 0.5 conversions, a significant drop in enthalpy values for all models indicates the moving of the reaction from endothermic to exothermic (Varma et al. 2020). In the present study from Tables 2 and 3, it was observed that there is a very small energy barrier among the average value of change in enthalpy and Eα value (< 5 kJ/mol) for all FWO, KAS, and Starink methods. The same variation between activation energy and enthalpy was found in a previous study conveyed by Sahoo et al. 2021. In addition, Pawar et al. (2021) also noticed a small variation between enthalpy and activation energy for coconut husk waste are 224 and 229 kJ/mol. A smaller alteration among the ΔH and Eα is mainly attributed to the creation of activated complex, which is linked with the requirement of minimum additional energy for effective pyrolysis of soybean straw for energy fuel generation (Kaur et al. 2018).

The Gibbs free energy (ΔG) indicates that the total energy raised in the reactor perspectives of the reactant and the original state of the activated product (Wen et al. 2019). In the present work, the average value of Gibbs free energy obtained for FWO, KAS, and Starink methods was found to be 165.40, 171.64, and 167.52 kJ/mol, respectively. The variation in Gibbs free energy values obtained for all three models showed that the formation of the activated complex and might be further used to solve the heat flow-related problems and disorders. For the FWO model, the values of Gibbs free energy were found to slightly decreased from 166.98 to 164 kJ/mol for a conversion from 0.1 to 0.9. Similar observation was also noticed for KAS and Starink methods, where Gibb's free energy slightly reduced from 172.95 to 170.21 kJ/mol and 168.95 to 166.12 kJ/mol, respectively. Figure 3 (b) indicates the ΔG relative to degree of conversions. Here, the increased value of Gibbs free energy corresponding to the degree of conversion discloses that overall energy supplied to the reactor at high pyrolysis temperature didn’t release rapidly from the system. In addition, from Table 2, it was observed that a higher value of ΔG was recorded at the beginning of conversion for all models, which means that auxiliary heat supplied to the reactor was found to be surplus. The positive value of ΔG obtained for all models justifies that the whole process is non-spontaneous and may be accomplished with the addition of some external energy.

Change in entropy represents the disorder in the degree of the reactant when it is exhibited for the reaction in any system. It means that the production of different end products and degree of randomness because of the thermal decomposition of soybean straw. From Table 2, it was observed that lower entropy was recorded at 0.1 conversions and it raised to conversion 0.5. For the FWO model, the entropy value at 0.1 conversions was found to be -226.71 kJ/mol and it increased up to 0.5 conversions to be around 130.14 kJ/mol, respectively. Likewise, for KAS and Starink model, the value of entropy changed from − 207.44 to 116.58 kJ/mol and − 233.71 to 112.27 kJ/mol, respectively. Figure 3 (c) indicates the ΔS relative to degree of conversions. A smaller value of ΔS implies that selected biomass i.e., soybean straw inclines toward the thermodynamic equilibrium, which means during the reaction process it undergoes a small physicochemical change relevant to its operating conditions. The negative value of change in entropy at conversion 0.1 and 0.2 for all three models signifying that produced devolatilization products possess a lower degree of disorder as compare to raw biomass, i.e., soybean straw. Whereas, the positive value of ΔS at different degrees of conversion, indicating a higher degree of randomness for soybean straw than those end products (Singh et al. 2020). The increase in value of entropy, in the beginning, justifies the improvement in the reactivity during the process of thermo-chemical conversion. This matches very well with the previous study conveyed by Dhyani et al. (2017) that enhancement in the reactivity at a specific degree of conversion and further dropped.

Similar results for change in enthalpy, entropy, and Gibbs free energy were also obtained in pyrolysis of agricultural residues such as wheat straw (Rathore et al. 2021), black gram (Gajera and Panwar, 2019), rice bran, and rice straw (Singh et al. 2020), Peanut shell, (Varma et al. 2020) etc. In addition, Table 4 compares the thermodynamic parameters and activation energy values obtained in the present experiment with other agricultural waste. From Table 4, it was noticed that soybean straw found a lower activation energy value than other agro-waste materials. As low activate energy for soybean straw means a requirement of minimum energy for efficient chemical reaction and because of this, it opens a new window to the researcher for appropriate utilization of soybean straw for bio-energy generation. In addition, knowledge of thermodynamic variables can play a significant role in designing the different thermochemical conversion systems with a proper mass and energy balance.

Table 4

Activate energies and thermodynamic parameters of soybean straw and other agro-residue.
Agro-waste	Method	Activation energy, Ea (kJ/mol)	Thermodynamic vairables			References
Agro-waste	Method	Activation energy, Ea (kJ/mol)	ΔH (kJ/mol)	ΔG (kJ/mol)	ΔS (J/mol. k)	References
Soybean straw	FWO, KAS, and Starink	155.34, 150.11, and 147.17	151.34, 147.14, and 142.81	165.40, 171.64, and 167.52	-233 to 130	Present study
Soybean straw	FWO, KAS	156.22, 154.15	--	--	--	Huang et al. (2016)
Maize cob	FWO, KAS, and Friedman	186.06. 185.39, and 197.63	192.83, 180.58	176.49, 176.66	-37 to 190	Gupta and Mondal (2019)
Peanut shell	KAS, and Kissinger	144–295, and 172–218				Torres-García et al. (2020)
Black gram straw	FWO, KAS, and Starink	172.96, 172.81, and 172.54	168.05, 167.90, and 167.64	166.99, 167.00, and 167.01	-20 to 69	Gajera and Panwar (2019)
Peanut shell	FWO, KAS	109.94, 96.33	104.76	128.33	-0.040	Varma et al. (2020)
Sugarcane leaves	KAS, and FWO	226.75, and 226.97	--	--	--	Kumar et al. 2019

<< Table. 4 >>

In present study, physicochemical characterization, calorific value, TG-DTG analysis, kinetic and thermodynamic analysis of soybean straw were explored. The maximum mass loss for soybean straw pyrolysis was observed in a temperature range 200–400 ^oC, mainly referred as active pyrolysis stage. The average value of activation energy and change of enthalpy were recorded to be near to each other (< 5 kJ/mol). The obtained kinetic data from all models disclosed a good agreement with the experimental results. Taking into consideration of lower ash and moisture content, the thermochemical conversion system creates a new window for appropriate utilization of soybean straw for energy generation.

Abbreviations:
Aα	Pre-exponential factor, s^− 1	R²	Correlation coefficient
α	Degree of conversion	F (α)	Model based function or reaction model
ΔH	Enthalpy, kJ/mol	m_o	Initial weight of sample, g
ΔG	Gibbs free energy, kJ/mol	m_t	Weight of sample after pyrolysis at a time t,
ΔS	Entropy, J/mol.k	m_f	Weight of biochar at the end of pyrolysis, g
ß	Heating rate, k/min	t	Time, s
R	Universal gas constant (8.314 J/K.mol).	T	Process temperature, k
h	Planks constant, m²kg s^− 1	k_B	Boltzmann constant, m²kg s^− 1K^− 1
Eα	Activation energy, kJ/mol	KAS	Kissinger-Akahira-Sunose
HHV	Higher Heating Value	FWO	Flynn-Wall-Ozawa (FWO)
TG	Thermo Gravimetric	DTG	Differential Thermo Gravimetric

Declarations

Ethical approval:

Not applicable

Consent to participate:

Not applicable

Declarations

Declaration of competing interest:

Author declares that there is no conflict of interest.

Funding:

No funding is available

Authors contribution:

Ms. Abolee Jagtap (First Author) was performed experimental study and wrote the manuscript. Surendra Kalbande (Co Author) was checked and edited the manuscript.

Acknowledgements

Authors are thankful to Maharana Pratap University of Agriculture and Technology (MPUAT), Udaipur (RAJ) for providing thermogravimetric analysis facility. Author grateful to National Agricultural Higher Education Project (ICAR) Department of Unconventional energy sources and electrical engineering, Dr. Panjabrao Deshmukh Krishi Vidyapeeth Akola providing fund for research. Author (Abolee Jagtap) also thankful to SARTHI, Govt. of Maharashtra for providing the research fellowship.

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Influence of Model Free Methods on Pyrolysis Kinetics and Thermodynamic Parameters of Soybean Straw

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Abstract

1. Introduction

2. Material and Methods

2.1 Raw Material

2.2 Methods

2.2.1 Proximate, ultimate analysis, and higher heating value

2.2.2 Thermo and differential thermogravimetric analysis

2.3 Kinetic analysis

2.4 Iso-conversional models

2.4.1 Flynn-Wall-Ozawa (FWO) method

2.4.2 Kissinger-Akahira-Sunose (KAS) method

2.4.3 Starink method

2.5 Thermodynamic parameters

3. Results and Discussion

3.1 Characteristics of soybean straw biomass

3.2 Thermal decomposition behaviour of soybean straw

3.3 Kinetic analysis

3.3.1 Evaluation of activation energy and pre-exponential factor

3.3.2 Analysis of Thermodynamic parameters

4. Conclusion

Declarations

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Funding:

Authors contribution:

Acknowledgements

References

Status:

Version 1