Pyrolysis kinetics behaviour and thermal pyrolysis of Samanea saman seeds towards the production of renewable fuel

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Pyrolysis kinetics behaviour and thermal pyrolysis of Samanea saman seed towards the production of renewable fuel Q7 Q1

Ranjeet Kumar Mishra a, Vineet kumar b, Kaustubha Mohanty a, * a

Q2

b

Department of Chemical Engineering, Indian Institute of Technology Guwahati, Guwahati, 781039, India Department of Civil Engineering, University Institute of Engineering and Technology MDU Rohtak, 124001, India

a r t i c l e i n f o

a b s t r a c t

Article history: Received 5 August 2019 Received in revised form 16 October 2019 Accepted 21 October 2019 Available online xxx

The present study addresses pyrolysis behaviour and potential of Samanea saman seeds (SS) towards its bioenergy potential using thermogravimetric analyzer and in a cylindrical pyrolyzer (semi-batch reactor). Pyrolysis kinetic behaviour of biomass was carried out using Kissinger, Distributed Activation Energy Model (DAEM) and Miura-Maki-Integral method (MMI) while thermal pyrolysis was carried out in a cylindrical shaped semi-batch reactor. Kinetic results confirmed that the average activation energy was found 118.24 kJ mol
1, 168.70 kJ mol
1, and 97.87 kJ mol
1 for Kissinger, DAEM, and MMI model respectively. Further, thermal pyrolysis of SS biomass yielded 44.20 wt% yield of pyrolytic liquid (31.20 wt % pyrolytic oil/organic oil and 13 wt% aqueous fraction). Characterization results of pyrolytic oil showed the presence of higher viscosity (86.01 cSt), higher oxygen content (33.11%), and lower ash content (0.46 wt%) and gross heating value. FTIR analysis confirmed mainly the presence of aromatics, acid, alkene, water, and protein impurities. Gas Chromatography (GC) results declared, an increase in hydrocarbon and hydrogen gas with an increase in temperature while reduced the generation of CO and CO2. Further, GC-MS analysis of pyrolytic oil revealed the presence of higher acids (19.46%), phenols (11.01%) ethers (11.12%) and ester (7.33%) which is a potent source of oxygenated compounds. Characterization results of biochar showed the presence of higher gross heating value (23.14 MJ kg), carbon content (62.66%), volatile matter (34.15%) and lower moisture (5.14%) and BET surface area (8.20 m2 g
1). Combining these results, it can be suggested that SS biomass has the potential to produce renewable fuel and chemicals, while biochar can be used for various applications. © 2019 Energy Institute. Published by Elsevier Ltd. All rights reserved.

Keywords: Waste biomass Kinetic analysis Thermodynamic analysis Pyrolysis Characterization of biochar

1. Introduction Energy is an essential factor of human civilization and the development of new technologies. Thus, the production of clean and sustainable energy becomes a major challenge. Currently, fossil fuel is the major source of all the energy, which is also the major source of emissions. Thus, renewable energy is the only hope for the production of clean and sustainable energy. Among all renewable energy sources, lignocellulosic biomass contributes an opportunity to produce clean and renewable energy from abundant sources, which reduces the dependence on fossil fuels [12]. Additionally, biomass is considered as carbon neutral source; thus, it is considered as a promising renewable source to mitigate the environmental emission. Moreover, if used effectively, it has the potential to provide job security to the rural sector, through sustainable management of locally available raw materials such as forestry debris, agricultural waste, etc. These materials can be further processed into desired products via the development of small-scale industries. Among all types of biomass, oilseed biomass has substantial potential to produce pyrolytic oil and reduced the carbon emission [37]. Indian Institute of Oilseeds Research (ICAR-IIOR) (201314) reported that about 28.51 million hectares of land were engaged in the cultivation of oilseed crops, which implies enormous production of renewable fuel and chemicals. Biochemical, thermochemical and mechanical extraction are the major methods for conversion of biomass into bio-oil or other desired products. The biochemical conversion process (BCC) involves break down of heavy molecules into smaller molecules by using bacteria and

* Corresponding author. E-mail address: [email protected] (K. Mohanty). https://doi.org/10.1016/j.joei.2019.10.008 1743-9671/© 2019 Energy Institute. Published by Elsevier Ltd. All rights reserved.

Please cite this article as: R.K. Mishra et al., Pyrolysis kinetics behaviour and thermal pyrolysis of Samanea saman seed towards the production of renewable fuel, Journal of the Energy Institute, https://doi.org/10.1016/j.joei.2019.10.008

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enzymes as catalysts. However, it requires a longer time for conversion of biomass into fuels such as ethanol. Mechanical extraction is an ancient technology for conversion of biomass which results in a lower yield of products. The thermochemical conversion process (TCC) has the potential to convert solid biomass into renewable fuels/chemicals by breaking the higher molecular weight compounds into lower molecular weight compounds due to the continuous supply of heat. Also, it has advantages over other processes since it can decompose biomass within a few seconds or minutes; however, it does depend on types of the pyrolysis process applied. Combustion, pyrolysis, gasification, and liquefaction (hydrothermal) are the major thermochemical processes. Among all the thermochemical processes, pyrolysis is considered a promising option for waste treatment, due to the conversion of biomass into various form of energy (liquid, solid, and gaseous products). Additionally, in this process, the recovery of energy is easier, when compared with other TCC methods [46]. Thermal degradation of the solid matrix such as biomass, into various end products, depends on the reaction kinetics; however, with use of the appropriate kinetic models, the possible reaction mechanism can be predicted [38]. To understand the pyrolysis reaction kinetics, pyrolysis of biomass/materials in a thermogravimetric analyzer (TGA) under a nonisothermal condition has proven an attractive method [5,7,27,38,43]. TGA worked on the rate of change in the mass as a function of temperature or time. The pyrolysis of biomass was performed at a lower heating rate (1  C min
1 -100  C min
1) and moderate temperature (400  Ce700  C) because, at a lower heating rate, the probability of turbulence is reduced and the conversion efficiency is enhanced. At higher heating rates, the residence time was reduced, which results in a reduction in interaction time of biomass particles, which causes the generation of turbulence. Two consequential methods: isothermal and non-isothermal are widely used to predict pyrolysis reaction kinetics. Non-isothermal methods have an advantage over isothermal methods such as shorter times and required lesser experimental data [6,14]. To reduce/avoid the possible error in reaction kinetics, the rate kinetics are estimated over the complete range of temperature (room to final temperature). Moreover, to understand the possible pyrolysis reaction kinetics, number of global and semi-global models are employed. These models characterise the transformation of a chemical reaction from one phase to another phase; such as solid to gas and/or solid to liquid. Several researchers have developed different mathematical models using TGA to explore the pyrolysis behaviour of biomass. Due to ease of application, simplicity and accuracy, the Kissinger, Miura-Maki integral method (MMI) and Distributed Activation Energy Model (DAEM) were used widely to evaluate and explain the kinetics of the multifaceted reaction of biomass pyrolysis [7,49]. DAEM model accepts numerous irreversible first-order parallel reactions, which are ascribed with multiple rate parameters that occur simultaneously [32]. Miura and Maki (1998) summarized, the model for the assessment of activation energy and frequency factor at multiple heating rates (minimum three TGA curves). Samanea saman is an evergreen tree which belongs to the Fabaceae (Legume) family. Usually, the height of the trees varies from 15 m to 25 m, but in some cases, it varied from 15 m to 50 m depends on the geographical condition, types of soil, etc. The seed is found in the pod while each pod is usually black-brown, oblong and lumpy (10 cme20 cm long, 15 mme19 mm wide, 6 mm thick) and straight or slightly curved in shape. The pod has an oblong-ellipsoid shape (8.0 mme11.5 mm long, 5.0 mme7.5 mm wide) and slightly flattened from side to side. Moreover, each pod has 15e20 seeds and becomes dark glossy brown with yellowish marking after-ripening [37]. Biochar is a high energy content solid fuel, leftover after the thermal decomposition of biomass such as pyrolysis and gasification. It can be used in different types of application such as solid fuel, soil remediation, greenhouse gas reduction, waste management, etc; since it is less expensive and more environmental friendly [8]. Although biochar has a maximum amount of carbon, but it also has small amounts of hydrogen, nitrogen, oxygen, and a trace amount of sulfur [8]. The elemental composition of biochar varied with the composition of biomass, types of pyrolysis processes, and geographical conditions [47]. Biochar has a higher specific area (>700  C under specified condition), surface functional groups, porous structure, and various useful mineral matter. It can be used as bio-adsorbents for treatment of water and wastewater, as a catalyst for the production of biodiesel, soil enhancer, making of the fuel cell, making of nanotubes and supercapacitors [8,19,50]. The objective of the present study is to understand the pyrolysis kinetic characteristics of SS biomass using TGA analyzer under a nonisothermal condition at multiple heating rates such as 10  C min
1, 20  C min
1, 30  C min
1, and 40  C min
1 respectively. In this study, activation energy and frequency factor were evaluated using Kissinger, Distributed Activation Energy Model (DAEM) and Miura-Maki Integral method (MMI). Thermodynamic analysis of SS biomass was also carried out to understand the behaviour of pyrolysis reaction. Further, thermal pyrolysis of SS biomass was executed in a cylindrical shaped semi-batch reactor to produce renewable pyrolytic oil. The pyrolytic oil and biochar were characterised based on their physicochemical properties. However, pyrolytic gas concentration was estimated using Gas Chromatography (GC). 2. Material and methods 2.1. Sample collection and preparation Samanea saman seeds (SS) or rain tree seeds were collected from Indian Institute of Technology Guwahati (IITG), Assam, India. The collected seeds were then detached from its cover and sundried for 2e3 days (as per atmospheric condition) and stored in airtight plastic bags to avoid absorbing the moisture. The airtight stored biomass was pulverized into the desired particle size (0.5 mm, 1 mm, 1.2, and 1.5 mm) in a lab-scale mixture grinder before the experiment. 2.2. Characterization of biomass Characterization of Samanea saman seed (SS) was reported in our previous study [37]. Briefly, proximate analysis of SS was performed using ASTM E871-82 (2006), ASTM E1755-01 (2007) and ASTM E872-82 (2006). An elemental analyzer (Euro EA3000, Euro Vector, Italy) was used to determine C, H, S, and N, while oxygen was determined by difference basis. Extractive content was determined using a Soxhlet apparatus while chemical analysis of the SS (hemicellulose, cellulose, and lignin) was performed using the wet chemistry method. Bomb calorimeter (Parr Instrument, 1341 Plain Jacket Bomb Calorimeter) was used to estimate the gross heating value of fuel while the bulk density of biomass was measured using a digital balance and a graduated cylinder. The mass of the sample was measured by digital balance, and volume of the sample was measured by a graduated cylinder. Please cite this article as: R.K. Mishra et al., Pyrolysis kinetics behaviour and thermal pyrolysis of Samanea saman seed towards the production of renewable fuel, Journal of the Energy Institute, https://doi.org/10.1016/j.joei.2019.10.008

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2.3. Thermal analysis The thermal behaviour of biomass was determined using thermogravimetric analyzer (NETZSCH, STA-449F3) under an inert atmosphere. About 9 mg biomass was placed in the crucible and heated from 30  C to 900  C at 20  C min
1 heating rate with 40 mL min
1 nitrogen gas flow rate. TGA was also used to understand the pyrolysis reaction kinetics at dynamic heating rates such as 10  C min
1, 20  C min
1, 30  C min
1, and 40  C min
1. Each experiment was repeated thrice for better accuracy of results. 2.4. FTIR analysis The presence of useful functional groups in biomass, pyrolytic oil, and biochar was analyzed using FTIR analysis (FTS 3500 GX analyzer attached with DRS). The oven-dried KBr powder and powdered biomass were mixed uniformly in a ratio of 1:100 and placed in the sample holder. The analysis was done using a scanning rate of 40 with a step size of 4 cm
1 within the range of 400 cm
1- 4000 cm
1 wavenumber. The above prescribed experimental conditions were employed for biochar. Further, pyrolytic oil was analyzed using Attenuated Total Reflectance (ATR) with the above-prescribed method. 2.5. Kinetic theory Pyrolysis is a multi-dimensional process due to the occurrence of thousands of reactions within the seconds or minutes, which is again dependant on the types of pyrolysis. Thus, prediction of complete and exact reaction mechanism becomes almost impossible however an overall proposed reaction mechanism as followed; k

Biomass

!Volatile þ Biochar þ Gases

(1)

k ¼ the rate of reaction. The conversion value can be determined using the following equation;

m0
mt a¼ m0
mf

! (2)

where, m0 ¼ initial weight of biomass, mt ¼ weight of biomass at the particular temperature, and mf ¼ final weight of biomass.The rate of reaction can be written as;

da ¼ kðTÞf ðaÞ dt

(3)

where, f ðaÞ ¼ reaction model and kðTÞ ¼ rate constant. The rate constant kðTÞ is a function of temperature and thus, can be described by the Arrhenius equation as;

 
E RT

kðTÞ ¼ Ae

(4)

where, A ¼ pre-exponential factor or frequency factor, E ¼ activation energy, R ¼ universal gas constant, and T ¼ absolute temperature. Substituting Eq. (3) in Eq. (4) we get,

  da ¼ Ae dt


E RT

f ðaÞ

(5)

Further, heating rate b, defined as:

b¼

dT dT da ¼ dt da dt

(6)

Combining Eq. (5) and Eq. (6), and rearranging we get,

Zx gðaÞ ¼ 0

da ¼ f ðaÞ

ZT 0

  A e

b


E RT

dT ¼

AE bR

Z∞ x

u
2 e
u du ¼

AE pðxÞ bR

(7)

E . In Eq. (7), AE pðxÞ has no mathematical solution. Therefore, numerical integration and approximation methods were used to where, x ¼ RT bR solve the equation. However, it was observed that the use of different types of approximation gives different activation energy and frequency factors [27].

2.5.1. Kissinger method Kissinger established a technique to estimate the apparent activation energy in physical or chemical processes data obtained from thermogravimetric analyzer at several non-isothermal conditions at constant heating rate [24]. Although, Kissinger method considered as model-free method but did not consider as an iso-conversional method due to assumption of the constant activation energy with increase in conversion value. According to Kissinger, the equation can be written as; Please cite this article as: R.K. Mishra et al., Pyrolysis kinetics behaviour and thermal pyrolysis of Samanea saman seed towards the production of renewable fuel, Journal of the Energy Institute, https://doi.org/10.1016/j.joei.2019.10.008

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1 !   b AR E 2
2 ln 2 ¼ ln (8) 3 E Tm RT m ! 4 The linear plot between ln b2 versus 1/T gives slope and intercept, which is used for estimation of activation energy and frequency 5 Tm factor. 6 7 2.5.2. Distributed Activation Energy Model (DAEM) 8 Distributed Activation Energy Model (DAEM) is used for the analysis of very complex reaction mechanisms during pyrolysis. This model 9 acts by considering the first-order reactions, which may be irreversible parallel reactions associated with different activation energies and 10 bond strength species. It produces more accurate results at a lower heating rate [5,27]. According to the DAEM model, the equation can be 11 written as; 12 13     b AR E 14 þ 0:6075
(9) Ln 2 ¼ ln E RT T 15   16 The liner plot between Ln Tb2 against 1/T provides slope and intercepts, which is used for estimation of activation energy and fre17 quency factor. 18 19 2.5.3. MiuraeMaki integral method (MMI) 20 This method was proposed by Miura and Maki (1998) for determining the value of f(E) and ko without any previous assumption for f(E) 21 and ko, unlike other iso-conversional models. This method required a minimum of three sets of data at dynamic heating rates. As from DAEM 22 method, 23 1 0 24   ZT Z∞ V
A E 25 dT Af ðEÞdE (10) ¼1
exp@ exp
Vt RT b 26 0 0   Z T 27 E 28 dT is known as temperature integral, which does not have any analytical solution and can be solved using In Eq. (10), exp
RT 0 29 Q3 different types of approximation. Miura-Maki methods used a modification of Coats-Redfern approximation and Eq. (10) become as; 30 31     ZT E RT 2 E 32 dTy (11) exp
exp
33 RT RT E 0 34 35 Then double exponential function becomes 36 " #  37 ART 2 E (12) exp
fðE; TÞyexp
38 RT bE 39 40 It was assuming that the function of E and T is a step function then Eq. (10) becomes 41 Z∞ 42 V y1
f ðEÞdE (13) 43 Vt 44 ES 45 Putting the value of Es ¼ 0.58 using the approximation Eq. (14) becomes 46   47 bES E 48 (14) 0:545 ¼ exp
RT AET 2 49 50 Using this treatment, approximation reaction occurred at a specific temperature and heating rate. The approximation means that 51   dV dðVÞ E 52 y ¼ A exp
ðVt
VÞ (15) 53 dt dt RT 54 Integrating Eq. (15) at a constant heating rate and rearranging and inserting Eq. (13) gives: 55 1 0 56 "  #   ZT 57 V A E ART 2 E A @ dT yexp
(16) exp
1
exp
exp
58 Vt RT RT b bE 0 59 60 Rearranging Eq. (16) and can be written as 61        62 b AR V E
ln
ln 1
(17) ¼ ln
ln 63 E Vt RT T2 64 By using approximation 1
VVt ¼ 0.58, Eq. (17) becomes 65 Please cite this article as: R.K. Mishra et al., Pyrolysis kinetics behaviour and thermal pyrolysis of Samanea saman seed towards the production of renewable fuel, Journal of the Energy Institute, https://doi.org/10.1016/j.joei.2019.10.008

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 ln

b

T2



 ¼ ln

 AR E þ 0:6075
E RT

5

(18)  

Eq. (18) is known as Miura-Maki integral method. The linear plot between ln Tb2 can be used for determination of activation energy and frequency factor.

against temperature gives slope and intercept, which

2.6. Thermodynamic analysis The thermodynamic parameters such as pre-exponential factor (A), enthalpy (DH), Gibbs energy (DG), and change in entropy (DS) were calculated by the following equations:



 A¼

E RTm

dEe

(19)

RT 2m

DH ¼ E
RTm

(20) 

DG ¼ E þ R  Tm  ln DS ¼

KB Tm hA

 (21)

DH
DG

(22)

Tm

where A is the pre-exponential factor (s
1), Tm is the peak decomposition temperature in (K), KB is Boltzmann constant (1.381  10
23 J/K), and h is Planck's constant (6.626  10
34 Js). 2.7. Optimization of process parameters Majority of process parameters directly affected the pyrolytic products yield (PPY). Among all the process parameters, temperature, heating rate, particle size, and gas flow rate have a substantial effect on PPY. Moreover, Mishra and Mohanty [41,42] studied pyrolysis of sawdust of pine, sal and areca nut husk in a semi-batch reactor at 500  C temperature, 80  C min
1 heating rate, 0.5 mm particle size and 100 mL min
1 inert gas flow rate and reported that biomass beds thickness and distance between beds directly altered the yield of pyrolytic liquid and its properties [42]. Since these process parameters were directly associated with pyrolysis, the optimization of these parameters become essential before pyrolysis. In order to optimizing the effect of temperature, heating rate and particle size, four temperatures 450  C, 500  C, 550  C and 600  C, four heating rates, 50  C min
1, 80  C min
1, 100  C min
1 and 120  C min
1 and four different size of particles (0.5 mm, 1 mm, 1.2 mm, and 1.5 mm) were chosen. However, the nitrogen gas flow rate was kept constant (100 mL min
1) throughout the experiments. 2.8. Pyrolysis experimental setup Pyrolysis of SS seed was conducted in a cylindrical shaped semi-batch reactor made of stainless steel (SS - 304) with dimensions of 4 cm internal diameter, 4.6 cm outer diameter and 30 cm of length. The pyrolysis experiment was carried out in a nitrogen atmosphere where gas was started 20 min before the experiment, to remove/purge air and other unwanted impurities. The detailed explanation about the pyrolysis setup and experimental procedure was reported in our previous study [40]. Further, the following equation was used for calculation of liquid, char, and gas yield.

 %Liquid yield ¼  %Char yield ¼

Liquid fuel weight Weight of total feed

  100

 Weight of char  100 Weight of total feed

%Gas yield ¼ 100
ð%Liquid yield þ %Char yieldÞ

(23)

(24) (25)

2.9. Characterization of pyrolytic oil The viscosity of oil was determined by using a Rheometer (HAKEERheostress 1) with cone and plate at 40  C at 50 RPM. A series of data were obtained from the analysis, and the average data is reported in this study. The calorific value of pyrolytic oil was determined by using oxygen bomb calorimeter (Parr Instrument, 1341 Plain Jacket Bomb Calorimeter). The acidity of pyrolytic oil was determined using Eutech waterproof (pH spear) pH meter by calibrating with a buffer solution of 4, 7 and 10. Moisture was determine using Karl Fischer water analyzer (Metrohm 787 KF Titrino) using ASTM E
203 and E
1064 with a standard error of ±3.5%. The density of pyrolytic oil was carried out by a density meter (Anton Paar, DMA-4500M), and the average value was reported in this study. The pour point of the pyrolytic oil was determined by ASTM D-97 while ash content was analyzed using hot air oven and muffle furnace. Approx., 3 g of pyrolytic oil was kept in a Please cite this article as: R.K. Mishra et al., Pyrolysis kinetics behaviour and thermal pyrolysis of Samanea saman seed towards the production of renewable fuel, Journal of the Energy Institute, https://doi.org/10.1016/j.joei.2019.10.008

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crucible and placed in a hot air oven at 105  C for 1 h to remove water and light volatile matter. Further, the oven-dried pyrolytic oil was placed in a pre-dried and pre-weight ceramics crucible and placed in a muffle furnace at 775  C for 24 h. After 24 h, the crucible was placed in the desiccator for isothermal cooling and then weighed. This experiment was repeated until a constant weight was obtained, while the final and initial weight difference indicated the amount of ash content. 2.10. Gas chromatography analysis of gases The pyrolytic gases at 450  C, 500  C, 550  C, and 600  C were collected in Tedlar gas sampling bags (Sigma-Aldrich) and analysis was done within 24 h. PerkinElmer Gas Chromatography (model: Clarus 580) was equipped with a Helium ionization detector (HID), and a thermal conductivity detector (TCD). Helium gas was used as carrier gas while Silica gel column (60 Molecular Sieve 13X and 6’ Silica Gel) was used for gas concentration analysis. The column was operated at initially 65  C for 8 min at the rate of 15  C min
1 to 250  C final temperature. The calibration gas standard mixture used consisted of H2, N2, O2, CO, CH4, CO2 and C2H6 with analytical accuracy of ±5%. Each gas sample was collected thrice at each temperature, and average data was reported in this study. 2.11. Gas chromatography-mass spectrometry (GC-MS) analysis The qualitative and quantitative analysis of pyrolytic oil was performed using Gas chromatography and Mass spectroscopy (PerkinElmer, Clarus 600/680) using Elite 5 MS column (30 mm  0.250 mm) column. Sample analysis was done at 40  C for 30 s, then increased at 10  C min
1 to 300  C while keeping 30 min total GC run time. 1.0 mL prepared pyrolytic oil (filtered with filter paper and diluted in dichloromethane) was injected in the injector where the carrier gas flow rate was set at 0.6 mL min
1. The chromatograph was collected with their retention time and mass spectra of the compounds. NIST library was used to identify the compounds and their composition. 2.12. Characterization of biochar Proximate analysis, ultimate analysis, gross heating value and bulk density of biochar were analyzed as described in section 2.2. The surface area was determined on dry biochar samples via N2 adsorption at 77 K on a Surface Area Analyser (Micromeritics ASAP-2020 BET). The degasification temperature of biochar was kept 200  C for 6 h. The morphology study of biochar was carried out by using Field Emission Scanning Electron Microscope (FESEM, Zeiss Supra 40) equipped with an Energy Dispersive X-ray Spectrometer (EDS, Oxford Inca Energy 350). The oven-dried biochar was placed on the carbon tape, and the double gold coating was done to prevent sample charging. FESEM was used under high vacuum with acceleration voltage between 5 kV and 15 kV. Further, the acidity of biochar was measured using pH meter by calibrating with standard pH buffers at pH 4, 7 and 10 before analysis. All analyses were performed in triplicate, and average results reported in this study. 3. Results and discussion 3.1. Physicochemical characterization of biomass Physicochemical characterization results of SS biomass was reported in our recent study [37]. Briefly, the proximate analysis confirmed the presence of higher volatile matter (76%) and lower ash content (3.06%) while elemental analysis confirmed presence of higher carbon content (48.46%) and lower nitrogen (7.30%). Heating value and bulk density were also found to be 17.68 MJ kg
1 and 657.41 kg m
3, respectively. Further, extractive content and chemical composition of biomass were found to be 30.66 wt% and 67.95 wt% (26.55 wt% hemicellulose, 30.81 wt% cellulose and 10.59 wt% lignin) respectively. 3.2. Thermal analysis Thermal analysis of biomass SS seed was carried out in a TGA analyzer at 20  C min
1 and TG profile is presented in Fig. 1. TGA curve showed three major decomposition stages known as drying, devolatilization (active stage) and char formation stage (passive stage). A similar study was reported by Mishra and Mohanty [38] for sawdust; Ceylan, and Topçu [6,7] for hazelnut husk. From the TGA curve, it was noticed that water molecule and light volatile matter were evaporated in the first stage (up to 150  C). Further, major decomposition occurred in the second stage (150  Ce550  C) due to mainly decomposition of hemicellulose and cellulose. In this stage, heavy molecules fragmented into lighter molecules by the continuous supply of heat. At the final stage, lignin decomposed at a slower rate at a higher temperature >550  C due to higher thermal stability, which resulted in the formation of biochar. Most of the cyclic compounds such as benzene rings, that are abundantly associated with lignin, cause higher thermal stability during decomposition, as compared to polysaccharide compounds such as cellulose and hemicellulose [30]. FTIR analysis suggested that the presence of hydroxyl phenolic compounds increase the thermal stability of lignin. Further, DTG thermograph of SS seed (Fig. 1) confirmed that the initial peak found at around 96  Ce105  C, showed the removal of the water molecules, however at higher temperature up to 150  C, light volatile compounds evaporated. The second peak appeared at 244  C, confirmed decomposition of hemicellulose while third and fourth peaks appeared at 343  C and 406  C confirmed decomposition of cellulose. At the final stage greater than 550  C, lignin decomposed at a slower rate without having any decomposition peak. Thermal analysis of SS seed confirmed 3.65 wt%, 69.80 wt%, and 3.84 wt% decomposition in first, second and third stage respectively. 3.3. Effect of heating rates Thermal decomposition profile of SS seeds at dynamic heating rates such as 10  C min
1, 20  C min
1, 30  C min
1, and 40  C min
1 under inert gas atmosphere was presented in Fig. 2. DTG thermograph showed that with increasing heating rates, thermal degradation profile Please cite this article as: R.K. Mishra et al., Pyrolysis kinetics behaviour and thermal pyrolysis of Samanea saman seed towards the production of renewable fuel, Journal of the Energy Institute, https://doi.org/10.1016/j.joei.2019.10.008

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Fig. 1. TG profile of SS seeds at 20  C min
1 heating rate.

Fig. 2. Effect of dynamic heating rates on the thermal profile of SS seeds.

shifted towards a higher temperature without altering decomposition profile. The alteration in the thermal decomposition of SS biomass arises due to lower heat transfer between biomass particles because biomass is a poor conductor of heat, which creates thermal resistance around the cross-section of particles. Also, the formation of secondary reactions of the primary pyrolysis products such as tar and other heavy molecules might be a possible motivation for alteration in thermal decomposition profile at dynamic heating rates [27]. Pyrolysis of jatropha wastes in a TGA suggested that maximum degradation occurred with higher heating rates due to increased thermal energy [23]. Our results showed that the peak temperature of SS biomass are 178  C, 187  C, 199  C and 215  C at 10  C min
1, 20  C min
1, 30  C min
1, and 40  C min
1 heating rates respectively. Similar studies were also reported by Mishra and Mohanty [38], Ashraf et al. [3] and Mishra et. al. [35,36,43]. Mishra and Mohanty [37]. studied sawdust of pine, sal and areca nut husk at multiple heating rates (5  C min
1, 10  C min
1, 15  C min
1, 20  C min
1, and 25  C min
1) in a TGA analyzer and reported that with increase in heating rates, TGA curves moved to higher

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Q8

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temperature region. Ashraf et al. [3]. studied coal and agricultural residue and reported that with an increase in heating rate from 10  C min
1, 20  C min
1, 30  C min
1, and 40  C min
1, TGA curves moved to higher temperature region without altering the decomposition profile. Further, Mishra et al. [35]. studied kinetics pyrolysis behaviour of waste dahlia flowers at dynamic heating rates (5  C min
1, 10  C min
1, 20  C min
1) in a TGA analyzer and summarized that TGA thermographs shifted at higher temperature zone 198  C, 206  C, and 218  C respectively with a steady increase in heating rates from 5  C min
1, 10  C min
1, and 20  C min
1. From the results, it was found that with an increase in heating rates thermal decomposition of individual constituents of SS biomass altered [6,38]. Moreover, results also revealed that with an increase in heating rates from 10  C min
1 to 40  C min
1 in the second stage (150  Ce550  C), the overall conversion was found to be 68.42%, 69.35%, 70%, and 71.19% respectively. This revealed that with an increase in heating rates total volatiles in the active stage increased, while at a lower heating rates, volatiles were reduced due to a longer residence time in the reactor, which resulted in formation of secondary reaction (cracking, re-polymerization and re-condensation) and offered formation of higher biochar [33]. The thermal decomposition of biomass is a complicated phenomenon thus at a lower heating rate, it may form a thermal barrier across the particles, whereas at the higher heating rate this barrier may breakdown due to rapid deterioration of biomass which offers a higher conversion yield. Results also confirmed that with increasing heating rates from 10  C min
1 to 40  C min
1, the solid residue also increased from 20.65 wt%, 22.42 wt%, 22.61 wt%, and 24.52 wt% respectively. At the higher heating rate, the residence time is reduced which means the interaction between biomass particles get partially pyrolyzed. While at lower heating rates, the residence time is higher, thus allowing the interaction between biomass particles to occur effectively or completely. This study showed that our results are consistent with other reported studies [43]. 3.4. FTIR analysis of SS biomass A wavenumber against transmittance spectra was plotted and presented in Fig. 3. The adsorption band 3313 cm
1 - 3000 cm
1 attributed to eOH symmetric vibration, which confirmed the presence of water, phenol, acid, protein, and aromatics compounds [11]. Further adsorption band 2924 cm
1 attributed to CeH and ¼ CeH stretching vibration, which confirmed the presence of alkanes and alkenes [2]. Peak 1656 cm
1 attributed to C]O stretching vibration, which showed the presence of in unconjugated ketone and aliphatic group [21]. Further, peak 1660 cm
1 - 1525 cm
1 ascribed with C]C stretching vibration showed the presence of alkene and aromatics [15] while peak 1470 cm
1 - 1350 cm
1 was ascribed with C^C deformation vibration due to the presence of alkyne [11]. The peak 1300 cm
1 - 950 cm
1 ascribed with C]O stretching, and deformation vibration confirmed the presence of ether and esters [11,36]. Finally, peak 534 cm
1 attributed to OeH bending confirmed the presence of mono and polycyclic substituted aromatics groups [11,13]. It was reported that the presence of aliphatic and aromatics compounds confirmed the existence of hemicellulose, cellulose, and lignin in the biomass [4,11,22]. 3.5. Kinetic analysis Kinetic parameters of SS seed was calculated by DAEM, MMI and Kissinger models at dynamic heating rates (10  C min
1, 20  C min
1, 30  C min
1, and 40  C min
1) presented in Table 1. It was noticed that conversion value higher than 0.8 is not fitted well due to low correlation value [6,27]. The average activation energy obtained from DAEM, MMI and Kissinger models are 168.76 kJ mol
1, 97.87 kJ mol
1, and 118.24 kJ mol
1 respectively; however, frequency factors are 4.16463Eþ12 min
1, 9.43Eþ7 min
1 and 1.33Eþ8 min
1 respectively. Further, the correlation coefficient was also found to be higher than 0.90 for each model at each conversion value, which showed best-fitted value with experimental data (Table 1 and Fig. S1). Results revealed that activation energy hardly varies with the rate of conversion, which implies a high degree of probability to present a single-step reaction [55]. The activation energy calculated via DAEM and MMI model varies from 123.85 kJ mol
1 to 220.76 kJ mol
1 and 66.21 kJ mol
1 - 154.34 kJ mol
1 respectively, while frequency factor varied from 4.12829Eþ9 min
1 - 1.65786Eþ13 min
1 and 2.5207Eþ4 min
1 - 7.47Eþ08 min
1 respectively from 0.1 to 0.8 conversion value. Since activation energy is a function of pyrolysis reaction, a higher value of activation energy means slower reaction. It was also reported that reactivity of fuel could be calculated from activation energy [17]. Reactivity of fuel has a substantial effect of pyrolysis and gasification of biomass, which helps the design and development of new pyrolyzers. The variation in activation energy with respect to conversion along with standard deviation was presented in Fig. 4. It was noticed that both models give different activation energy at each conversion point. This difference appeared in both models due to their used

Fig. 3. FTIR analysis of SS seeds.

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Table 1 Kinetic analysis of SS seed using DAEM and MMI model. Conversion

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Average

DAEM

MMI

A (1/min)

E (kJ/mol)

R2

Equation

4.128Eþ9 4.501Eþ9 1.13718Eþ11 2.89846Eþ11 6.62677Eþ11 2.24484Eþ12 1.34187Eþ13 1.65786Eþ13 4.16463Eþ12

123.85 131.05 152.16 162.48 172.00 184.49 202.88 220.76 168.70

0.9924 0.9702 0.9739 0.9793 0.9688 0.9567 0.9454 0.9925

y y y y y y y y

¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼


14897x
15763x
18302x
19544x
20688x
22191x
24403x
26553x

þ þ þ þ þ þ þ þ

19.449 19.478 22.553 23.421 24.192 25.346 27.033 27.16

A (1/min)

E (kJ/mol)

R2

Equation

2.52Eþ6 4.55Eþ6 1.10Eþ5 4.51Eþ6 1.27Eþ6 5.62Eþ6 6.54Eþ6 7.47Eþ08 9.43Eþ7

66.21 73.27 81.50 92.52 96.63 100.36 118.15 154.34 97.87

0.9949 0.9961 0.9948 0.9922 0.9812 0.9819 0.9824 0.9779

y y y y y y y y

¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼


7963.4x þ 8.0666
8813.2x þ 8.5532
8813.2x þ 8.5532
11008x þ 10.619
11622x þ 10.709
12072x þ 10.754
14211x þ 13.048
18564x þ 17.514

Table 2 Comparison table of kinetic parameters with other reported biomass. Biomass

Heating rate ( C/min)

DAEM (kJ/mol)

MMI (kJ/mol)

Kissinger (kJ/mol)

References

SS Pine sawdust Sal sawdust Areca nut husk sawdust Gliricidia Rubber wood

10, 20, 30 and 40 5, 10, 15, 20, and 25 5, 10, 15, 20, and 25 5, 10, 15, 20, and 25 10, 20 and 30 10, 20 and 30

168.70 206.62 171.63 160.45 190e230 111e179

97.87 e e e e e

118.24 e e e 107.19 83.44

Present study [38]

[49] [49]

Fig. 4. Variation of activation energy with respect to conversion value.

approximation and types of used models. A comparison table of calculated activation energy along with other biomass such as sawdust of pine, sal, areca nut [38], gliricidia and rubber wood [49] are listed in Table 3. Results revealed that the calculated activation energy has very similar results with other reported biomass in Table 2. Biomass pyrolysis is a very complex mechanism where each chemical composition of biomass had their own degradation range, which was also dependent on temperature; thus, a slight variation in activation energy appeared. 3.6. Thermodynamic analysis (TD) Thermodynamic parameters of SS seed were calculated using activation energy obtained from the DAEM model at 10  C min
1 and listed in Table 3. The result revealed that the average pre-exponential factor of SS biomass was found to be 2.05Eþ13 s
1 while it is varied from Table 3 Thermodynamic analysis of SS seed. Conversion

A (1/s)

DH (kJ/mol)

DG (kJ/mol)

DS (J/mol.K)

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Average

3.63Eþ06 1.61Eþ06 1.26Eþ08 1.06Eþ09 7.46Eþ09 9.66Eþ10 4.16Eþ12 1.60Eþ14 2.05Eþ13

118.83 126.03 147.14 157.46 166.98 179.47 197.86 215.74 163.69

210.90 210.61 209.86 209.53 209.25 208.90 208.42 208.00 209.43


152.64
140.23
103.99
86.33
70.07
48.78
17.50 12.83
75.84

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3.63Eþ6 s
1 - 1.6Eþ14 s
1. The difference in the pre-exponential factor showed that SS biomass followed complex reaction mechanism [54]. The change in enthalpy confirmed the nature of reaction (endothermic and exothermic). Results (Table 3) showed that calculated enthalpy varied from 118.83 kJ mol
1 to 215.74 kJ mol
1, and average enthalpy was found to be 163.69 kJ mol
1. The positive value of enthalpy suggests that energy will be required for the degradation of biomass during pyrolysis. Further, alteration in enthalpy with conversion value implies a complex nature of biomass [56]. [56] explained a similar trend of change in enthalpy. The variation in entropy implies that the degree of disorder of products formed through bond dissociations was lower than that of initial reactants. The calculated entropy varied from
152.64 J mol
1. K
1 to 12.83 J mol
1. K
1 while average entropy was found to be 75.84 J mol
1. K
1. The variation in entropy implied that biomass went through a physical and chemical degradation which helped to bring it near its own thermodynamic equilibrium. In this situation, biomass demonstrates little reactivity and upsurges the time to form the activity complex. Further, higher entropy implies that biomass is too far from its own thermodynamic equilibrium. At this condition, material reactivity is faster to produce the activated complex, which offers a shorter reaction time [53]. The variation in Gibbs free energy implies that the degree and spontaneity of the reactions. The calculated Gibbs free energy varied from 210.90 kJ mol
1 to 208 kJ mol
1 while average Gibbs energy was found to be 209.43 kJ mol
1. 3.7. Process parameter optimization The process parameters such as temperature, heating rates, and particle size of biomass were studied and presented in Fig. 5(aec). From Fig. 5(a), it was noticed that maximum pyrolytic liquid yield (44.20 ± 1.2 wt%) was achieved at 550  C due to complete pyrolysis of biomass. At this condition, maximum heat and mass transfer occurred between biomass particles due to higher residence time which allowed complete conversion of biomass, thereby increasing the yield of pyrolytic liquid. However, at a lower temperature such as 450  C and 500  C, pyrolytic liquid yield and gas yield were reduced while char yield increased due to partial pyrolysis of biomass (lower heat transfer between biomass particles). At partial pyrolysis condition, the hot volatiles present in biomass did not escape from the shell/core of the biomass due to lower heat transfer which results in a decrease in the yield of pyrolytic liquid. Beyond 550  C, it was noticed that pyrolytic liquid yield and char yield were reduced while yield of gaseous products increased due to a rapid endothermic fragmentation of biomass where the condensable gases might have changed to non-condensable gases [34]. Therefore, 550  C was considered as optimum temperature for liquid production. From Fig. 5(b), it was noticed that maximum liquid yield (44.20 ± 1.2 wt%) was obtained at 80  C min
1 due to complete pyrolysis of biomass. At this condition, the overall residence time (interaction between biomass particles) of pyrolysis increased, which ultimately increased the yield of pyrolytic liquid. Further, at a lower heating rate 50  C min
1, the lower yield of pyrolytic liquid and gas was obtained while char yield was higher due to incomplete pyrolysis of biomass (lower heat and mass transfer between biomass particles). Results also confirmed that further increasing heating rate above 80  C min
1, liquid and char yield reduced whereas gas yield increased due to the rapid

Fig. 5. Process parameters optimization, (a) temperature, (b) heating rate, and (c) particle size on pyrolytic products yield (PPY).

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endothermic decomposition of biomass (rapid fragmentation of biomass). Therefore, 80  C min
1 heating rate was considered as the optimum heating rate for liquid production. A similar study was reported by Haykiri-Acma et al. [20]. From Fig. 5(c), it was confirmed that at smaller particle size (0.5 mm) gives a maximum yield of pyrolytic liquid (44.20 ± 1.2 wt%) due to higher heat and mass transfer which showed complete conversion of biomass. However, at bigger particle sizes such as 1 mm, 1.2 mm and 1.5 mm, yield of pyrolytic liquid, and gas reduced whereas the char yield increased due to incomplete conversion of biomass. At this condition, heat transfer between biomass particles lowered which ultimately reduced the yield of pyrolytic liquid. A similar study was reported by Mishra and Mohanty [37,38,39,40]. The sweeping gas flow rate was kept 100 mL min
1 since at lower flow rate of sweeping gas flow rate did not affect pyrolytic products yield [1]. From Fig. 5(aec), 550  C temperature, 80  C min
1 heating rate, 0.5 mm particle size, and 100 mL min
1 sweeping gas flow rate was considered as optimum pyrolysis condition for liquid production. 3.8. FTIR analysis of thermal pyrolytic oil A wavenumber against transmittance spectra was plotted and presented in Fig. 6. The peak 3738 cm
1 - 3000 cm
1 ascribed with eOH stretching vibration confirmed the presence of aromatics, phenols, acid, water, and protein impurities [11,45,52]. The peak 2960 cm
1 2840 cm
1 attributed to CeH stretching vibration, which confirmed the presence of alkane. Further peak 1707 cm
1 was generated due to C]O stretching vibrations and confirmed the presence of ketone [13]. The peak 1454 cm
1 had arisen due to C^C bond which confirmed the presence of alkyne; while peak 1300 cm
1 - 950 cm
1 confirmed the presence of ester due to CeO stretching and deformation [11,36]. The adsorption band 900 cm
1 - 500 cm
1 ascribed with OeH bending vibration, which confirmed the presence of mono and polycyclic substituted aromatic groups [11]. 3.9. Characterization of pyrolytic oil The characterization results of pyrolytic oil were compared with diesel fuel and listed in Table 4. The ultimate analysis confirmed the presence of higher carbon (55.41%) and lower nitrogen (1.42%), while the presence of higher amount of oxygen (33.11%) (also confirmed by GC-MS) resulted in a negative impact (altered the stability, flame temperature and fluidity) on the pyrolytic oil. Further, thermal pyrolytic oil has a lower gross heating value (25.73 MJ kg
1) than diesel due to the presence of higher acidic component in pyrolytic oil (GC-MS analysis) [40]. It was also noticed that thermal pyrolytic oil contained lower amount of moisture (1.4%). Although the pyrolytic oil has lower moisture which had a negative impact on the heating value of fuel, concurrently, it reduced the viscosity; which in turn, offers a positive effect during

Fig. 6. FTIR analysis of thermal pyrolytic oil.

Table 4 Characterization of thermal pyrolytic oil. Analysis

SS pyrolytic oil

Diesel [41]

Colour Odour C (%) H (%) O (%) N (%) S (%) Heating value (MJ/kg) Viscosity (cSt) at 40  C Density (kg/m3) Acidity Moisture (%) Pour point (oC) Ash content (%)

Dark brown Smoky 56.41 8.10 33.11 1.42 0.96 25.73 ± 1.2 86.01 ± 1.4 958.16 ± 1.6 6.2 ± 0.42 1.4 ± 1.2
14.20 0.46 ± 0.12

e e e e e e e 45.50 2e4.5 820 e e
40 to
1 e

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atomization and combustion of pyrolytic oil during the engine application [58]. The major drawback of the thermal pyrolytic oil was its higher viscosity which can be minimized by using appropriate upgradation technologies such as catalyst cracking [18]. Results revealed that pyrolytic oil had a higher viscosity (86.01 cSt) which reduced the fluidity and stability. The thermal pyrolytic oil had lower acidity which may cause corrosion in the storage vessel and boiler during the application, while the density of fuel was found to be higher (958.16 kg m
3) than diesel. The pour point of pyrolytic oil was found to be 14.20  C which indicated the presence of paraffin compounds. The pour point of pyrolytic oil relates to their paraffin content that means the higher the paraffin content, the higher the pour point. Finally, the ash content analysis of pyrolytic oil was found to be 0.46% which showed that it can be used as a transportation fuel or in boiler applications without much problem. 3.10. GC analysis of pyrolytic gases The pyrolytic gases collected at 450  C, 500  C, 550  C, and 600  C were analyzed in gas chromatography and presented in Fig. 7. GC results confirmed that the concentration of gases altered with temperatures; thus, higher temperatures raised the volume of hydrocarbon gases such as CH4, C2H6, C3H6, C3H8, along with H2, while carbon dioxide and carbon monoxide decreased. It is evident that at a higher temperature, the secondary cracking reaction generated favourable conditions to produce hydrocarbons and hydrogen gases [4]. Also, results confirmed that with increasing temperatures from 450  C to 600  C generation of hydrogen and hydrocarbons gases were increased, however at the same time, the formation of carbon dioxide and carbon monoxide decreased due to the decarboxylation process which ultimately reduced greenhouse gases from the environment [25]. A similar study was also carried out by Kongkasawan et al. [25]. 3.11. GC-MS analysis GC-MS analysis of thermal pyrolytic oil was analyzed and matched with the National Institute of Standards and Technology (NIST) library and presented in Fig. 8 while details compound list are listed in Supplementary Table S1. It is well established that pyrolytic oil is the mixture of mainly phenols, aromatics, hydrocarbons, acids, ethers, esters, furans derivatives, alkanes, ketones, aldehydes, amides etc., which made pyrolytic oil more suitable for engine application [10]. However, it is worth to mention that the composition of these compounds altered significantly with types of biomass, feed composition, types of pyrolysis and its operating conditions etc. The pyrolysis of hemicellulose and cellulose mainly yielded aromatic hydrocarbons, acids, kenotic compounds, cycloalkane, furanic compounds, and miscellaneous hydrocarbon [29,31,44]. From the results, the major compounds identified using GC-MS, were as followed: hydrocarbons (26.58%), acid (19.46%),

Fig. 7. GC analysis of gases collected at 450  C, 500  C, 550  C, and 600  C pyrolysis temperature.

Fig. 8. GC-MS analysis of thermal pyrolytic oil.

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ether (11.12%), ester (7.33%), ketone (1.18%), phenol (11.01%), amide (3.3%) nitrogenous compounds (6%) and others (2.13%). Pyrolytic oil contains a number of acidic compounds such as octadecanenitrile, oleanitrile, 9-octadecenoic acid methyl ester, stearic acid methyl ester, heptadecane, 9-octadecenamide, 11-hexadecenal, and pentadecane, etc., which is used for various industrial applications. Additionally, higher percentages of phenol content offered scope for many industrial applications [48]. Further, the presence of nitrogen-containing compounds in pyrolytic oil may lead to the formation of NOx compounds during combustion or engine application. Results confirmed that thermal pyrolytic oil can be used as furnace fuel for domestic heating or can be used for extraction of various valuable chemicals. However, using as an alternative of diesel fuel, need advance upgrading techniques such as catalytic cracking. 3.12. Characterization of biochar The leftover solid residue after pyrolysis is known as biochar, has a wide application and can be categorized based on the characterization results. The biochar of Samanea saman seed (SSC) obtained at 550  C was characterized and listed in Table 5 and compared with coal, palm shell hydro char (PSHC) [47] and Cassia siamea seed char (CSC) [9]. From Table 5, it was noticed that the lower moisture (5.14%), higher volatile matter (34.14%) and significant fixed carbon (47.54%) contents, clearly indicated the higher ignition efficiency of biochar. However, ash content was slightly higher (13.18%), which had a negative effect when it is used as solid fuel. The ultimate analysis of SSC revealed the presence of 62.66% carbon, 31.83% oxygen, 2.06% hydrogen, and 3.45% nitrogen. The presence of nitrogen in biochar made it more suitable for use as soil enhancer [51]. Further, the gross heating value of SSC was also found to be higher (23.14 MJ kg
1), which implies it can be utilized as a good solid fuel. From proximate analysis, it was found that biochar contained lower amount of moisture; thus, it can be stored for longer duration [47]. Moreover, the presence of oxygen content in biochar enhanced the properties of biochar during activation via leaching [9]. It was also noticed that fresh seeds have lower carbon content (49%) while biochar has higher carbon content (62.66%) due to the removal of oxygen content. Additionally, the percentage of nitrogen content was reduced in biochar compared with the fresh seed (6.30%) due to different types of the chemical reaction taking place during pyrolysis such as dehydration (removal of water or moisture), decarbonylation and decarboxylation [26]. During pyrolysis, diffusion of volatiles enhanced the heating value of biochar; thus, it can be utilized as good solid fuel for domestic heating and cooking [47]. Also, the biochar can be used as bio-adsorbents for the treatment of water and wastewater [28]. Characterisation results showed that BET surface area was found to be lower (8.20 m2 g
1); thus, it exhibits limited utility as bio-adsorbents. The bulk density of biochar was found to higher (478 kg m
3) than acid-activated biochar (221 kg m
3) which confirmed that storage and transportation will be easier. Finally, the acidity of the biochar was also found to be 7.60 which implied that it can be used as a soil enhancer.

Table 5 Physicochemical characterization of SSC and compared with coal, cassia siamea seeds char and palm shell hydro char. Analysis

SSC

Coal [47]

Cassia siamea seed char [9]

Palm shell hydro char [47]

Moisture (wt.%) Volatile matter (wt.%) Ash content (wt.%) Fixed carbon (wt.%) C (%) H (%) O (%) N (%) S (%) Heating value (MJ/kg) BET surface area (m2/g) Bulk density (kg/m3) Acidity

5.14 ± 0.4 34.14 ± 0.8 13.18 ± 0.4 47.54 ± 0.8 62.66 2.06 31.83 3.45 e 23.14 ± 1.2 8.20 ± 0.6 478 ± 1.6 7.60 ± 0.8

e e e e 55.38 5.86 34.07 2.48 2.21 22.54 e e e

e e e e 57.34 2.80 35.53 4.33 0.1 21.89 7.34 e e

e e e e 63.77 4.40 23.33 0.52 1.02 26.80 12.56 e e

Fig. 9. FESEM analysis of SSC biochar obtained at the optimized condition.

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1 3.13. FESEM analysis of SS biochar 2 3 FESEM analysis of SSC was presented in Fig. 9. It was noticed that after pyrolysis, the morphology become more complex due to the 4 aggregation of mineral compounds. During pyrolysis number of reactions such as dehydration, decarbonylation, and decarboxylation occur, 5 which alter the morphology of biochar [57]. In addition, a small number of pores were found in biochar due to decomposition and vola6 tilization of raw materials. During pyrolysis (550  C), a large amount of hot volatile materials pass through the pore at short periods of time 7 which shrink, split and alter the particle surface (Fig. 9). FESEM analysis also showed regular surface structure, and a long channel appeared 8 in biochar. It was reported that during pyrolysis, the chemical bond fragmented which changed the structure and pore of the biochar [16]. 9 10 4. Conclusion 11 12 The present study deals with the kinetics behaviour and thermal pyrolysis of Samanea saman seed (SS) towards producing renewable fuel 13 and valuable chemicals. Kinetic results showed that the calculated activation energy is the function of conversion value. Further, variation in 14 enthalpy indicated the nature of reaction and variation in entropy indicated reactivity of the reaction system. The thermal pyrolysis yielded 15 31.20 wt% pyrolytic oil at an optimized condition which had a higher viscosity, oxygen content, and ash content which needed further 16 upgradation for its use as transportation fuel. FTIR results suggested the existence of water, phenols, aromatics, and alkanes, while GC results 17 pointed reduction in greenhouse gases (CO, and CO2) with an increase in temperature from 450  C to 600  C. It was also noticed that with an 18 increase in temperature, formation of hydrogen and hydrocarbons gases increased. GC-MS results confirmed the presence of oxygenated 19 compounds and various valuable chemicals in the pyrolytic oil. Characterization results of biochar indicated that it can be used for different 20 applications such as solid fuel, fertilisers, and bio-adsorbents. 21 22 Acknowledgement 23 24 The author would like to thank you for the Department of Chemical Engineering for TGA analysis, Centre for Energy for heating value 25 Q4 analysis and Central Instruments Facility (CIF) for FESEM analysis, at Indian Institute of Technology Guwahati (IITG). 26 27 Appendix A. Supplementary data 28 29 Supplementary data to this article can be found online at https://doi.org/10.1016/j.joei.2019.10.008. 30 31 32 List of Abbreviation 33 34 35 SS Samanea saman seed 36 TGA Thermogravimetric analysis 37 DTG Differential thermogravimetric analyzer 38 DAEM Distributed Activation Energy Model 39 MMI Miura-Maki Integral model 40 FTIR Fourier-transform infrared spectroscopy 41 GC-MS Gas chromatography-mass spectrometry 42 BET Brunauer-Emmett-Teller theory 43 FESEM Field Emission Scanning Electron Microscopy 44 PPY Pyrolytic products yield 45 SSC Samanea saman seeds char 46 47 References 48 49 Q5 [1] J. Akhtar, N.S. Amin, A review on operating parameters for optimum liquid oil yield in biomass pyrolysis, Renew. Sustain. Energy Rev. 16 (7) (2012) 5101e5109. [2] V. Anand, R. Gautam, R. Vinu, Non-catalytic and catalytic fast pyrolysis of Schizochytrium limacinum microalga, Fuel 205 (2017) 1e10. 50 [3] A. Ashraf, H. Sattar, S. 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Please cite this article as: R.K. Mishra et al., Pyrolysis kinetics behaviour and thermal pyrolysis of Samanea saman seed towards the production of renewable fuel, Journal of the Energy Institute, https://doi.org/10.1016/j.joei.2019.10.008