Vol.:(0123456789) https://doi.org/10.1007/s13399-024-05706-y
ORIGINAL ARTICLE
Thermokinetic study of coconut husk pyrolysis in the devolatilization zone using volatile state approach
Pandit Hernowo1 · Soen Steven2,3 · Muhammad Maulidin4 · Alif Gita Arumsari4 · Yazid Bindar3,5 · Amalia Syauket6 · Komang Ria Saraswati7 · Dede Rukmayadi8
Received: 28 February 2024 / Revised: 25 April 2024 / Accepted: 26 April 2024
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024
Abstract
Coconut husk is a residue from coconut processing plants that has not been widely utilized. Pyrolysis has the opportunity to convert it into chemicals in the form of bio-crude oil (BCO). Therefore, this study aims to examine the thermal decom- position behavior as well as determine the kinetic and activation thermodynamic parameters of coconut husk pyrolysis in the devolatilization zone using thermogravimetric analysis (TGA). Volatile state Kissinger-Akahira Sunose (KAS), volatile state Flynn–Wall–Ozawa (FWO), volatile state Friedman, and volatile state Coats-Redfern (CR) methods were employed with heating rates of 5, 10, and 20 °C.min−1. The TGA result supports the evidence of the non-isothermal pattern in the mass loss profile. Besides, the average ranges of activation energy, pre-exponential factor, activation enthalpy, activation entropy, and activation Gibbs free energy of coconut husk pyrolysis are 197.56–198.41 kJ.mol−1, 6.08 × 1020–1.41 × 1022 s−1, 192.87–193.73 kJ.mol−1, − 0.24–0.28 kJ.mol−1.K−1, and 152.39–166.12 kJ.mol−1, in a respective term. The pattern of acti- vation energy shows that it initially enhances along with reaction progress and temperature due to low molecular mobility and then the value alleviates as the completion decomposition process to form BCO. On the other side, the results of the activation thermodynamics parameters prove that this process is endothermic, forms a transition state (ordered) before form- ing the product (disordered), and requires an external supply of heat. As a recommendation, the volatile approach is proven can describe the relationship between activation energy and activation thermodynamic parameters in the transition state.
Keywords Coconut husk · Kinetic · Pyrolysis · Thermogravimetry · Activation thermodynamic
* Pandit Hernowo
1 Department of Chemical Engineering, Universitas Bhayangkara Jakarta Raya, Kampus II, West Java 17121, Indonesia
2 Research Center For Sustainable Production System and Life Cycle Assessment, National Research and Innovation Agency (BRIN), KST BJ Habibie, Building 720 Puspiptek Area, South Tangerang, Banten 15314, Indonesia
3 Biomass Technology Workshop, Faculty of Industrial Technology, Institut Teknologi Bandung, Sumedang 45363, Indonesia
4 Department of Chemical Engineering, Institut Sains Dan Teknologi Al-Kamal, West Jakarta 11520, Indonesia
5 Research Group On Biomass and Food Processing Technology, Faculty of Industrial Technology, Institut Teknologi Bandung, Bandung 40132, Indonesia
6 Research Group On Law and Science, Universitas Bhayangkara Jakarta Raya, Kampus II, West Java 17121, Indonesia
7 Government Junior High School, SMPN 2 Tigaraksa, Tangerang 15720, Indonesia
8 Department of Industrial Engineering, Universitas Bhayangkara Jakarta Raya, Kampus II, West Java 17121, Indonesia
1 Introduction
Coconut plants are mostly found in coastal countries where Indonesia, Philippines, and India contribute 75% of the world’s total coconut production [1]. Coconut process- ing always generates residues such as shell and husk [2].
Coconut shell is frequently used for direct solid fuels such as charcoals or briquettes [3]. Meanwhile, the coconut husk is still overlooked and poorly utilized. One proposed route for utilizing this lignocellulosic biomass is pyrolysis.
It is a thermochemical process in converting biomass to biochar, bio-crude oil (BCO), and gas [4, 5]. Typically, pyrolysis is carried out in the absence of oxygen and its performance is influenced by biomass physicochemical properties, heating rate, reactor geometry, and process temperature [6, 7].
Recently, research on lignocellulosic biomass pyrolysis plays a pivotal role in renewable chemical producers [8, 9].
The objective is also to reduce dependence on the exploita- tion of fossil resources which are believed to pollute the environment [10, 11]. Pyrolysis involves complex reac- tions but the explanation of its reaction progress in iso- thermal systems is considered still unsatisfying [12, 13].
Another idea has emerged to explain it in non-isothermal systems via the iso-conversion model. This theory explains that each reaction progress will have different values of activation energy ( Ea ) and pre-exponential factor ( A ) at every pyrolysis temperature [14].
Several studies of thermogravimetric analysis (TGA) application which involves heating rate variations have been widely disclosed [15, 16]. TGA acts as a tool to investigate and estimate thermal process behavior, fuel reactivity, char zone, devolatilization zone, and volatile release [17, 18]. It can also reveal comprehensive physical and chemical mechanisms in biomass pyrolysis [19, 20].
Consequently, the kinetic parameters of biomass pyrolysis can be determined through this method [21, 22]. Biomass pyrolysis has different mechanisms in response to tem- perature increases at a constant heating rate. This causes the pre-exponential factor and activation energy to be unique and different for various types of treatments [23].
The iso-conversion model is more widely used to explain complicated mechanisms than isothermal model [16, 24].
Likewise, the iso-conversion model is recommended by the International Confederation for Thermal Analysis and Calorimetry (ICTAC) for analyzing analytical data such as TGA, differential scanning calorimetry, and differential thermal analysis [25].
As illustrated in Fig. 1, the TGA curve of biomass ther- mal decomposition is usually categorized into three zones.
The first zone occurs until reaches 150 °C. It is a drying zone which is endothermic. The second zone consists of subse- quent phenomena by means of a devolatilization zone in the temperature range of 150–600 °C. The decrease of mass loss in this zone is caused by hemicellulose and cellulose decomposition at 150–400 °C, while lignin decomposition occurs at 400–600 °C [9]. The third zone corresponds to the decomposition of char. After the char zone, the remained material consists of ash particles [26].
The devolatilization zone occurs non-isothermally while the char zone occurs isothermally. In the devolatilization zone, there is a significant release of volatile matter as an effect of endothermic heat absorption until the pyrolysis temperature is reached. After the pyrolysis temperature is reached, the release of volatile matter tends to slow down in the char zone, so the temperature alteration is relatively constant [19]. For this reason, it can be considered isother- mal conditions [21, 27].
The determination of kinetic parameters of biomass pyrolysis is mostly derived from a solid-state approach [26, 29]. This approach explains that the process of releasing
Fig. 1 Thermal decomposition zones of camel manure at a constant heating rate of 10 °C.
min−1, processed from [28]
0 10 20 30 40 50 60 70 80 90 100
0 100 200 300 400 500 600 700 800 900 1000
0 25 50 75 100 125
Conversion t vs T
Mass Loss or Conversion (%) Temperature (oC)
Time (min) Drying
Zone
Devolatilization Zone Char Zone Mass Loss
volatile matter at a constant heating rate can be approxi- mated by the mass loss of biomass during the pyrolysis pro- cess to produce char [30]. It is usually based on measuring the degree of conversion as a function of time at constant temperature [16, 19, 31]. The relationship of kinetic rate law ( r ) with conversion is served in Eq. (1) whereas the mathematical relationship of mass loss is expressed by a conversion variable, Eq. (3) [25].
where 𝛼 is the degree of conversion (progress of reaction) for biomass pyrolysis, A is the pre-exponential factor, Ea is the activation energy, R is the ideal gas constant, T is the pyrolysis temperature, and f(𝛼) is the decomposition reac- tion model where the first-order model is frequently offered because of simplicity [20], m0 is initial mass of biomass, mp is biomass mass at instantaneous temperature, and mf is mass at final temperature pyrolysis which automatically the mass of ash.
There are four well-known iso-conversion models for determining kinetic parameters of biomass pyrolysis, i.e., Kissinger–Akahira–Sunose (KAS), Flynn–Wall–Ozawa (FWO), Friedman, and Coats-Redfern (CR). The equations are summarized in Table 1.
In accordance with Steven et al., many researchers rely on the solid-state approach in obtaining the kinetic param- eters of biomass pyrolysis [26]. However, this approach observes the progress of the pyrolysis reaction by forcing 100% conversion at the end of the pyrolysis process, as (1) Biomass(s) 𝛼,conversion
�
���������������������������������������→Char(s)+Volatiles(g)
(2) r= d𝛼
dt =A.exp (−Ea
R.T )
.f(𝛼)
(3) 𝛼=
m0−mp m0−mf
mathematically stated in Eq. (3). It is certainly ambiguous because the pyrolysis process always remains char and ash as also confirmed in the TGA curve [32]. The ash is only obtained after both the devolatilization zone under non- isothermal conditions and the char zone under isothermal conditions have completely passed. This forcing treatment leads to the signifying activation energy near the end of the complete pyrolysis process which is inconsistent with the actual phenomena [29, 32].
Besides, this inconsistency affects the value of acti- vation thermodynamic parameters in the transition state [33, 34]. The reported values of activation Gibbs free energy and activation entropy are positive and the larger progress of the reaction enlarges the activation enthalpy [35, 36]. This reason is acceptable because the pyrolysis temperature requires an amount of heat and it is absorbed by cellulose, hemicellulose, and lignin. Nevertheless, the activation enthalpy still continues to rise in the char zone, whereas the components of cellulose, hemicellulose, and lignin have been degraded into char [37].
According to the previous evidence, the aim of this study is, hence, to examine the kinetic and activation ther- modynamic parameters of coconut husk pyrolysis using a volatile state approach. The focus of this study lies on the devolatilization zone which describes the non-isothermal decomposition process. The calculation utilizes an iso- conversion model that adapts volatile state KAS, volatile state FWO, volatile state Friedman, and volatile state CR methods. Afterward, the kinetic parameters are applied to obtain activation thermodynamic parameters such as activation enthalpy ( ΔH∗ ), activation entropy ( ΔS∗ ), and activation Gibbs free energy ( ΔG∗ ). All of the results are used to reveal the kinetic and spontaneous behavior of coconut husk pyrolysis. Apart from that, this study also addresses a brief enrichment section that aims to prove the potential of coconut husk pyrolysis as a chemical pro- ducer. This section is deliberately presented separately in the Supplementary Materials (Sections S.1–S.4).
Table 1 Equations for the iso- conversion model based on the solid-state approach [26]
where 𝛽 is the heating rate [°C.min−1], g(𝛼) is the integral form of f(𝛼) , Ea is the activation energy [kJ.
mol−1], R is the ideal gas constant [8.314 J.mol−1.K−1], T is the process temperature [K], and A is a pre- exponential factor [min−1]
Method Equation Plot y vs. x
Solid-state KAS 𝑙𝑛
(𝛽 T2
)
=ln ( A.R
g(𝛼).Ea
)
−Ea
RT ln
(𝛽 T2
) vs.
(
1 T
)
Solid-state FWO 𝑙𝑛(𝛽) =𝑙𝑛(A.E
a g(𝛼).R
)
−5.331−1.052
Ea
RT ln𝛽 vs.
(
1 T
)
Solid-state Friedman 𝑙𝑛(
𝑑𝛼 𝑑𝑡
)
=𝑙𝑛( 𝛽d𝛼
dT
)
=𝑙𝑛[ A.f(𝛼)]
−Ea
RT 𝑙𝑛(d𝛼
dt
) vs.
(
1 T
)
Solid-state CR 𝑙𝑛
(g(𝛼) T2
)
=ln (AR
𝛽.Ea
)
− Ea
RT 𝑙𝑛
(g(𝛼) T2
) vs.
(
1 T
)
2 Material and methods
2.1 Collection and preparation of biomass
The coconut husk was purchased and collected from a local market in Bogor, Indonesia. It was initially chopped until it has an average size of 1–2 cm. The chopped biomass was then sun-dried for a total average drying time of 18 h. In order to prevent moisture from adhering to the raw materials, dried and chopped biomass was stored in airtight containers.
The prepared coconut husk is served in Fig. 2.
2.2 Proximate and ultimate analysis
The proximate analysis of coconut husk encompassed sam- ple preparation following ASTM D2013-20, total moisture content following ASTM D3302-19, inherent moisture measurement following ASTM D3173-17a, and ash determi- nation following ASTM D3174-18. All were using Furnace AAF 1100. Subsequently, the volatile matter was recorded following ASTM D3175-20 by Furnace VMF 1000, and fixed carbon was calculated by difference. In the meantime, the ultimate analysis in the form of CHN element measure- ment was referred to ASTM D5373-21 using LECO CHN- 628, S element determination applied ASTM D 4239–18 using LECO S-632, and O element was calculated by dif- ference [%O = 100 − (%C + %H + %N + %S)].
2.3 Thermogravimetric analysis (TGA)
and differential thermogravimetric analysis (DTG)
TGA and DTG of coconut husk using a PerkinElmer TGA 4000 were employed to assess the thermal decomposi- tion curve and pyrolysis thermokinetic. The weight of the samples was maintained at 8.62 ± 0.1 mg to reduce aspects of heat and mass transfer resistances. The samples were subjected to a programmed temperature of 30–500 °C at
constant heating rates of 5, 10, and 20 °C.min−1. The final temperature was deliberately terminated at 500 °C because this study only focused on the observation of the devola- tilization zone which is non-isothermal. In order to prevent undesirable oxidation reactions in the pyrolysis process, nitrogen gas (N2) at a flow rate of 20 mL.min−1 was applied for purging for all experimental variations.
2.4 Pyrolysis reaction mechanism
The actual mechanism of biomass pyrolysis cannot easily be explained in detail because it is a complex process due to the large number and variety of substances participat- ing in different parallel and sequential reactions. For this reason, efforts to develop simplified formal kinetic models of pyrolysis have been ongoing. Biomass composition and pyrolysis operating conditions are key parameters that affect the pyrolysis process because they led to the emergence of a series of formal kinetic models for testing processes [26].
The one-step global reaction mechanism of biomass pyroly- sis to volatile and char that can be described is served in Fig. 3.
This mechanism consists of a single reaction with com- plex kinetics. In this case, the role of kinetic studies is the selection of three values (kinetic triplet) that encompass pre-exponential factor, activation energy, and a function describing the dependence of the reaction rate on the conver- sion [38]. Several studies use multicomponent single-stage
Fig. 2 Dried and chopped coconut husk
One-step global reaction mechanism
Biomass(s)→ Char(s) + Volatiles(g)
A(s)→ B(s) + C(g)
BIOMASS
VOLATILE
CHAR
Fig. 3 One-step global reaction mechanism of biomass pyrolysis to volatile and char
models as main components of biomass (hemicellulose, cel- lulose, and lignin) to independently decompose. The model of three independent parallel 1st-order reactions successfully described the pyrolysis kinetic of various types of biomass and waste [38, 39].
Non-isothermal kinetic model for biomass decomposi- tion is mostly generated based on the solid-state approach [40, 41]. This approach studies the decomposition process at a constant heating rate which is observed by mass loss of biomass during the pyrolysis process to produce char. The mathematical expression of mass loss is represented by a conversion variable indicating the progress of the reaction ( 𝛼 ) [42, 43]. Several other studies reveal that the kinetic parameters of biomass pyrolysis can also be modeled from a new approach for the quantification method, namely the volatile state approach under non-isothermal conditions [26, 44]. This approach focuses on the devolatilization stage and presumes that all product components have different kinetic parameters because of the independent series reactions. The mass fraction of the components decomposed at T1 has the parameter E(T1) , at T2 has the parameter E(T2) , and so on until it reaches the char reaction zone at T5 with the param- eter E(T5) [26], as illustrated in Fig. 4.
2.5 Thermokinetic modelling using volatile state approach
The volatile state approach scrutinizes the release of volatile matter in the devolatilization zone. The linear increase in tem- perature at a constant heating rate continues until the pyrolysis temperature limit ends. For this reason, it can be considered non-isothermal conditions. This approach improves Eq. (3) by entering the mf variable as 0 because ash has not been formed
at this stage. Apart from that, this approach also introduces a new variable, namely volatile release yield ( YVY ) [29, 45]. The rearrangement of Eq. (3) will obtain Eq. (4). If both sides are divided by m0 , it results in Eq. (6).
By applying mass balance, the total amount of volatile and char is equal to the whole amount of biomass. Therefore, the total fraction of volatile yield and char yield is 1 (Eq. (7)). In another expression, Eq. (6) can be transformed into Eq. (8).
After that, the mathematical transformation from solid-state approach (Table 1) into volatile state approach was held by replacing 𝛼 with YVY . The adaptation of Eq. (8) to the KAS, FWO, Friedman, and CR methods then generates volatile state KAS, volatile state FWO, volatile state Friedman, and volatile state CR methods. If the plot of ln(𝛽
T2
) , ln𝛽 , 𝑙𝑛(dY
VY
dt
) , 𝑙𝑛(g(YVY)
T2
) vs. 1T generates a linear line pattern, as summarized in Table 2, the activation energy can be obtained from the slope, and the pre-exponential factor can be determined by the intercept.
Besides, the activation thermodynamic parameters, which involve activation enthalpy ( ΔH∗ ), activation entropy ( ΔS∗ ), and activation Gibbs free energy ( ΔG∗ ), were evaluated using Eqs. (7)–(11) [37, 46].
where kB represents the Boltzmann constant [1.381 × 10−23 J.
K−1], and h is the Plank constant [6.626 × 10−34 J.s].
(4) (m0−mf)
𝛼=m0−mp→mf=0
(5) (m0)
𝛼� =m0−mp
(6) 𝛼� =1−
mp
m0 =1−Ychar
(7) Ychar+YVY=1
(8) 𝛼� =YVY= m0−mp
m0
(9) ΔH∗=Ea−RT
(10) ΔG∗ =RT𝑙𝑛
(kBT h.A
) +Ea
(11) ΔS∗= ΔH∗− ΔG∗
T
drying devolatilization zone non-isothermal 0
100
Temperature
char zone isothermal biomass
particle E(T
1)
E(T
2)
E (T
3)
E(T5) H2O
E(T
4)
Mass Loss (%)
Fig. 4 The mechanism of biomass decomposition of multiple inde- pendent parallel reactions [26]
3 Results and discussions
3.1 Proximate and ultimate analysis of coconut husk
The proximate and ultimate analysis of coconut husk is outlined in Table 3. The S content below 0.1% indicates negligible SOX emission during pyrolysis. Apart from that, the N content in coconut husk of 0.48%-wt can have the potential of NOX formation. However, it should be emphasized that this process has a maximum temperature of 500 °C so that the equilibrium conversion of the NOX formation reaction is low [47, 48]. It can be said that this process has also a negligible amount of NOX emissions.
Furthermore, the calorific value, low ash content, and high volatile matter in coconut husk reflect that pyrolysis is feasible to produce BCO [4, 9].
In another study, coconut husk was found to have vola- tile matter at 82.94% with a calorific value of 14.08 MJ.
kg−1 and low ash at 0.92% [49]. The calorific value was also found to be 17 MJ.kg−1 [1], 19.71 MJ.kg−1 [46], and 19.71 MJ.kg−1 [50]. The difference in the results of the analysis between this study and others is that biomass has characteristics that cannot be exactly the same as each other but are diverse depending on the origin, climate, and geography where it grows [51]. Despite coconut husk having a lower calorific value compared to coal (29.5 MJ.
kg−1) [52], all of the results confirm that coconut husk biomass is still suitable for chemical producers in the form of BCO through a more sustainable process.
The chemical components in BCO are derived from the cellulose, hemicellulose, and lignin decomposition [53].
At temperatures above 300 °C, cellulose undergoes depo- lymerization reaction and fragmentation to form pyran- and furan-based compounds in BCO [9]. On the other hand, ther- mal decomposition of hemicellulose produces furfural com- pounds in BCO with a lower yield than cellulose because hemicellulose is not thermally stable due to its low crys- tallinity [54]. Meanwhile, lignin is a complex heterogene- ous polymer derived from phenylpropane monomers unit, i.e., guaiacyl, syringyl, and p-hydroxyphenyl [55]. Thermal decomposition of lignin occurs at 400–600 °C which pro- duces aromatic molecules and phenolic compounds in BCO [9, 56].
3.2 TGA and DTG curve analysis of coconut husk The thermal decomposition process in TGA and DTG is dominantly controlled by chemical reactions instead of heat and mass transfer resistance effects. In general, the effect of those resistances in evaluating pyrolysis thermokinetic can be neglected because of the low sample amount and small particle size [57, 58]. It is proven by the low biomass amount therein, 8.62 ± 0.1 mg. TGA curves at constant heat- ing rates of 5, 10, and 20 °C.min−1 are then analyzed to explain the decomposition and thermal behavior of coconut husk. According to Fig. 5, the TGA curve of coconut husk demonstrates a devolatilization pattern with an initial ther- mal decomposition starting at 120 °C.
In addition, three different stages of pyrolysis are observed. The first stage, which occurs at temperatures up to 250 °C, is associated with loss of moisture, extractives, and low molecular weight compounds due to the hygro- scopic nature of coconut husk [49, 59]. This study observed a mass loss of 14.82% during the first stage of coconut husk decomposition. The second stage of mass loss, also known as the active pyrolysis zone, occurs at a greater temperature of 250–360 °C. Most of the thermal decomposition occurs during this stage because of the fragmentation of higher molecular weight compounds into smaller compounds. This stage is equivalent to the loss of hemicellulose, a part of cel- lulose, and a small amount of lignin [53, 60]. A mass loss
Table 2 Equations for the iso- conversion model based on the volatile state approach [29]
Method Equation Linearization plot
Volatile state KAS 𝑙𝑛(𝛽
T2
)
=ln( A.R
g(YVY).Ea
)
− Ea
RT ln(𝛽
T2
) vs.
(
1 T
)
Volatile state FWO 𝑙𝑛(𝛽) =𝑙𝑛 ( A.E
a g(YVY).R
)
−5.331−1.052
Ea
RT ln𝛽 vs.
(
1 T
)
Volatile state Friedman 𝑙𝑛(dY
VY 𝑑𝑡
)
=𝑙𝑛( 𝛽dYVY
dT
)
=𝑙𝑛[ A.f(
Y
VY
)]−Ea
RT 𝑙𝑛(dY
VY dt
) vs.
(
1 T
)
Volatile state CR 𝑙𝑛(g(YVY)
T2
)
=(
A.R 𝛽.Ea
)
−Ea
RT 𝑙𝑛(g(YVY)
T2
) vs.
(
1 T
)
Table 3 Proximate and ultimate analysis of coconut husk on a dry basis
Proximate analysis Ultimate analysis
Moisture content (%-wt) - C (%-wt) 47.28
Volatile matter (%-wt) 72.61 H (%-wt) 6.28
Fixed carbon (%-wt) 23.89 O (%-wt) 45.89
Ash (%-wt) 3.50 N (%-wt) 0.48
Calorific calue (MJ.kg−1) 17.51 S (%-wt) 0.07
of 40.63% is recorded during the second stage of coconut husk decomposition.
The last stage of thermal decomposition occurs at 360–500 °C. This stage is also known as the passive pyrol- ysis zone and corresponds to the completion of cellulose decomposition and endothermic decomposition of lignin [49, 60]. Yet, the decomposition rate is much slower com- pared to other stages because of the tough characteristic of lignin. It has complex polymeric structures consisting of a phenylpropane molecule and complicated branched C-H groups [55]. The mass loss of 12.18% is reached during the last stage of coconut husk decomposition.
In the 1st stage of decomposition or temperature of below 250 °C, the calculated YVY at 5, 10, and 20 °C.min−1 is quite similar (13.82%, 13.61%, and 13.57%). In the meantime, YVY in the 2nd stage of decomposition (e.g., at 300 °C) is more contrasted which obtained at 31.07%, 28.13%, and 25.71% for 5, 10, and 20 °C.min−1. Consequently, the value of YVY does not depend on the heating rate at low pyrolysis
temperatures. In contrast, the strong influence of the heat- ing rate on YVY is denoted at high pyrolysis temperatures because the yield of gas product is rapidly augmented and then becomes constant under the higher heating rate [61].
The greater gas product yield is the result of BCO second- ary cracking under higher pyrolysis temperatures in the char zone. However, once the pyrolysis temperature is reached the secondary reaction, the gas yield cannot escalate any further so it tends to remain constant.
In accordance with the DTG curve, the coconut husk pyrolysis has evidence of two-step decomposition as in Fig. 6. The first peak is observed at 276.31–301.30 °C which is related to the loss of hemicellulose because it decom- poses in the temperature range of 220–315 °C [62]. On the other hand, the maximum peak temperature (Tpeak) at 328.25–346.90 °C corresponds to cellulose decomposition where it undergoes thermal decomposition at 320–400 °C [63]. Subsequently, lignin decomposition has a wide tem- perature range above 400 °C. The maximum decomposition
Fig. 5 TGA curve profiles of coconut husk
0 10 20 30 40 50 60 70 80 90 100
20 60 100 140 180 220 260 300 340 380 420 460 500
Mass Loss (%)
Temperature (oC) 1st stage of
decomposition
2nd stage of decomposition
3rd stage of decomposition
5oC.min−1 10oC.min−1 20oC.min−1
Fig. 6 DTG profiles of coconut husk
-1.1 -1.0 -0.9 -0.8 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0.0
0 50 100 150 200 250 300 350 400 450 500
dα/dt (mg.min-1)
Temperature (oC)
325 330 335 340 345 350
0 5 10 15 20
Tpeak (oC)
Heating Rate (oC.min-1) Effect of heating
rate on Tpeak
5oC.min−1 10oC.min−1 20oC.min−1
rates are recorded at 40.64%, 43.08%, and 37.42% along with the heating rate of 5, 10, and 20 °C.min−1.
3.3 Results of thermokinetic analysis using volatile state approach
3.3.1 Volatile state approach vs. solid‑state approach Equations (3) and (8) imply that the conversion value ( 𝛼 ) in the solid-state approach always has a greater value than the volatile released yield ( YVY ) in the volatile state approach as also confirmed in Fig. 7. This happens because the solid- state approach forces 100% conversion at conditions near the end of pyrolysis, which are actually not yet 100% converted (leaving char and ash). This means that at every specific temperature, the actual conversion value has not yet reached that level but is still lower as proven in Table 4. For example, at 344.73 °C, 𝛼 has reached 74.39%, but YVY is still at 50%.
This certainly has an impact on greater activation energy values between the solid-state approach and the volatile state approach (374.81 kJ.mol−1 vs. 201.78 kJ.mol−1).
Additionally, several studies have proven that the activa- tion energy of biomass pyrolysis is not as high as the lit- erature reports [26, 29, 57]. It is proven that the volatile state approach shows a lower activation energy than the solid-state approach. Furthermore, the activation energy from the solid-state approach increases with temperature enhancement of 336.21–344.73 °C, indicating a more dif- ficult process to occur under higher temperatures. This cer- tainly contradicts the phenomenon that occurs that the con- version process should continue under these conditions to form volatiles, char, and ash (lower activation energy). Since the pattern of activation energy from the volatile state dimin- ishes at temperature enhancement of 336.21–344.73 °C, it can be concluded that this approach offers more logical and relevant results.
3.3.2 Kinetic parameters: activation energy and pre‑exponential factor
Figure 8 reveals the kinetic plots of coconut husk pyrolysis using volatile state KAS, volatile state FWO, volatile state Friedman, and volatile state CR methods to determine the activation energy at YVY of 0.1–0.55. It should be noted that YVY beyond 0.1–0.55 is not used in this study due to its non- linear characteristics and lower correlation coefficient ( R2 ).
The plots of all methods generally reflect the same trend, while the volatile state Friedman method gives a slight dis- crepancy. In addition, all methods used in this study fit with the experimental data. The accuracy of the methods used is confirmed and evidenced by the average R2 value at YVY 0.1–0.55 of 0.92, 0.93, 0.93, and 0.92 for volatile state KAS, volatile state FWO, volatile state Friedman, and volatile state CR methods.
From the previous plots, the kinetic parameters ( Ea and A ) of coconut husk pyrolysis at YVY of 0.1–0.55 are described in Table 5. The obtained activation energy with the volatile state KAS method ranges from 90.37 to 241.19 kJ.mol−1.
Fig. 7 Profile of mass loss, volatile release yield ( YVY ), and conversion ( 𝛼 ) of coconut husk pyrolysis at 5 °C.min−1
0 10 20 30 40 50 60 70 80 90 100
0 10 20 30 40 50 60 70 80 90 100
20 80 140 200 260 320 380 440 500
Mass Loss or Conversion or Volatile Release Yield (%) time (min)
Temperature (oC)
Volatile Release Conversion Mass Loss t vs T Table 4 The volatile release yield and conversion values from vola- tile-state and solid-state approaches
Volatile state Solid-state T (°C)
Y
VY(%) Ea(kJ.mol−1) 𝛼(%) Ea(kJ.mol−1)
10 90.37 11.27 102.68 87.38
15 146.08 22.95 234.47 255.57
20 237.61 30.28 269.89 277.17
25 231.54 37.64 293.80 291.10
30 241.19 45.39 310.81 304.92
35 229.13 53.23 307.97 317.68
40 204.27 60.49 280.25 327.76
45 212.59 68.43 233.08 336.21
50 201.78 74.39 374.81 344.73
Likewise, volatile state FWO, volatile state Friedman, and volatile state CR methods produce activation energies between 91.63–238.45 kJ.mol−1, 111.57–245.84 kJ.mol−1, and 90.40–241.20 kJ.mol−1, respectively. The average values of activation energy reported in this study are lower than the activation energies of palm kernel shell, 262.0 kJ.mol−1 [64], castor, 215.6 kJ.mol−1 [34], and raw rice straw, 200.8 kJ.
mol−1 [65]. In pyrolysis, activation energy represents the fuel reactivity, and it is more difficult to initiate a reaction with a large activation energy because it indicates that a more difficult reaction occurs [17]. In other words, low val- ues of activation energy are more desirable.
Pre-exponential factor values ranging from 1012 to 1021 s−1 are derived from volatile state FWO, volatile state KAS, and volatile state CR methods whereas 1015–1022 s−1 are from volatile state Friedman method. The range of first- order pre-exponential factors can vary from 104 to 1018 s−1 [66]. The variation with reaction conversion is due to the complex biomass structure and decomposition reactions.
The low value of the pre-exponential factor (< 109 s−1) indi- cates surface reactions. When the reaction is independent of surface area, low pre-exponential factor values represent closed complexes, but larger values denote simple com- plexes [34, 37]. The escalating value of the pre-exponential factor might be due to the more intensive molecular collision
under higher heating rates. This behavior indicates the com- plex nature of coconut husk and its components which lead to a multi-step decomposition chemical reaction [33].
Each of the parameters above will have a combined influ- ence on the reaction progress. It describes the unique phe- nomenon of the decomposition process of each biomass in the devolatilization zone and char zone, thereby providing a compensatory effect on the value of the activation energy and pre-exponential factor [29]. The various values of acti- vation energy are influenced by several factors such as bio- mass characteristics, kinetic model, heating rate, and conver- sion. Sharma et al. argued that the greater value of biomass heat capacity results in a longer reaction time [67]. Di Blasi stated that the heating rate influences the reaction temper- ature [61]. Di Blasi reported that the biomass conversion process tends to take longer as the biomass density value increases, and the biomass conversion time takes longer as the biomass thermal conductivity value decreases [68].
Moreover, fixed carbon and volatile matter contents also play a major role in the varying values of activation energy [64].
The values of activation energy at every YVY and tem- perature from KAS, FWO, Friedman, and CR methods using volatile state approach are further illustrated in Fig. 9. The activation energy pattern in coconut husk pyrolysis shows an increasing and decreasing pattern
Fig. 8 The plot for determina- tion of activation energy of coconut pyrolysis using volatile state KAS (a), volatile state FWO (b), volatile state Fried- man (c), and volatile state CR (d) methods
(a) (b)
(c) (d)
-11.5 -11.0 -10.5 -10.0 -9.5 -9.0 -8.5
1.5 1.7 1.9 2.1 2.3 2.5 2.7 2.9 ln (β.T−2)
1000/T (K−1)
Volatile State KAS
1.5 1.7 1.9 2.1 2.3 2.5 2.7 2.9 3.1
1.5 1.7 1.9 2.1 2.3 2.5 2.7 2.9
lnβ
1000/T (K−1)
Volatile State FWO
-1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5
1.5 1.7 1.9 2.1 2.3 2.5 2.7 2.9 ln (β.d(YVY).dT−1)
1000/T (K−1)
Volatile State Friedman
-13.0 -12.5 -12.0 -11.5 -11.0 -10.5 -10.0
1.5 1.7 1.9 2.1 2.3 2.5 2.7 2.9 ln (-ln(1-YVY).T−2)
1000/T (K−1)
Volatile State CR
forming a second-order temperature function as also found in other studies [26, 29, 46, 57]. Under higher tempera- tures, the activation energy values initially escalate as the more rigid structure and lower molecular mobility of bio- mass [69]. Afterward, a diminishing pattern is found in activation energy since the decomposition is near to com- pletely forming BCO [29, 70]. The dependence of activa- tion energy on YVY indicates that the reaction mechanism
is not the same throughout the decomposition process [14, 71]. As suggested by Vyazovkin et al., most of the solid thermal decomposition phenomena exhibit dependence on activation energy with YVY . If the activation energy is constant over the entire YVY range, the process is likely to be a single-step dominated process which is widely found in homogeneous reactions [14].
Table 5 The kinetic parameters of coconut husk pyrolysis using volatile state approach
Y
VY(%) Volatile state KAS Volatile state FWO
Ea(kJ.mol−1) A(s−1) Ea(kJ.mol−1) A(s−1)
10 90.37 1.12 × 1012 91.63 1.83 × 1012
15 146.08 2.78 × 1013 147.29 3.81 × 1013
20 237.61 7.66 × 1021 234.65 4.39 × 1021
25 231.54 7.01 × 1020 229.12 4.43 × 1020
30 241.19 1.95 × 1021 238.45 1.20 × 1021
35 229.13 6.25 × 1019 227.22 4.41 × 1019
40 204.27 1.11 × 1017 211.64 9.40 × 1017
45 212.59 1.29 × 1018 203.82 1.23 × 1017
50 201.78 5.15 × 1016 201.68 5.14 × 1016
55 189.31 1.93 × 1015 190.06 2.29 × 1015
Average 198.39 1.04 × 1021 197.56 6.08 × 1020
Y
VY(%) Volatile state Friedman Volatile state CR
Ea(kJ.mol−1) A(s−1) Ea(kJ.mol−1) A(s−1)
10 111.57 1.50 × 1016 90.40 1.10 × 1012
15 168.19 7.04 × 1016 146.10 2.80 × 1013
20 217.58 1.95 × 1021 237.60 7.70 × 1021
25 237.61 5.06 × 1022 231.50 7.00 × 1020
30 245.84 8.84 × 1022 241.20 2.00 × 1021
35 211.09 3.16 × 1019 229.10 6.30 × 1019
40 200.20 2.42 × 1018 212.60 1.10 × 1018
45 199.04 1.32 × 1018 204.30 1.30 × 1017
50 213.42 1.20 × 1019 201.80 5.20 × 1016
55 179.58 2.94 × 1015 189.30 1.90 × 1015
Average 198.41 1.41 × 1022 198.40 1.10 × 1021
Fig. 9 Activation energy of coconut husk pyrolysis at every YVY (a) and temperature (b) using volatile state approach
(a) (b)
75 100 125 150 175 200 225 250
0 10 20 30 40 50 60
KAS FWO Friedman CR
Ea (kJ.mol-1)
YVY (%)
75 100 125 150 175 200 225 250
0 100 200 300 400
KAS FWO Friedman CR
Ea (kJ.mol-1)
Temperature (oC)
3.3.3 Activation thermodynamic parameters
The activation thermodynamic parameters provide infor- mation on ΔH∗ (kJ.mol−1), ΔS∗ (kJ.mol−1.K−1), and ΔG∗ (kJ.mol−1) with YVY and temperature. Enthalpy is a state function to identify whether the heat is being absorbed or released in chemical reactions which also represents the total heat contained in an open system [72]. The activation enthalpy at every YVY and temperature are presented in Fig. 10a, b. The average values obtained using the vola- tile state KAS, volatile state FWO, volatile state Fried- man, and volatile state CR methods are 193.71 kJ.mol−1,
192.87 kJ.mol−1, 193.73 kJ.mol−1, and 193.71 kJ.mol−1, in a respective term.
For all four iso-conversion models, the highest ΔH∗ value is obtained in the YVY range of 0.1–0.3. This is because of endothermic reactions where heat is absorbed to decompose cellulose, hemicellulose, and lignin. The total enthalpies of the three components continue to enhance as the pyrolysis temperature intensifies [29, 34]. On the other hand, the slight alleviation in enthalpy under enhancing YVY is because of the depleted amount of biomass where cellulose, hemicellulose, and lignin have partially converted to volatile matter. Consequently, the
Fig. 10 Activation enthalpy of coconut husk pyrolysis at every YVY (a) and temperature (b) using volatile state approach.
Activation entropy of coconut husk pyrolysis at every YVY (c) and temperature (d) using vola- tile state approach. Activation Gibbs free energy of coconut husk pyrolysis at every YVY
(e) and temperature (f) using volatile state approach
(e) (f)
90 110 130 150 170 190
0 10 20 30 40 50 60 KAS FWO Friedman CR
ΔG* (kJ.mol-1)
YVY (%)
90 110 130 150 170 190
0 100 200 300 400
KAS FWO Friedman CR
ΔG* (kJ.mol-1)
Temperature (oC)
(a) (b)
(c) (d)
75 100 125 150 175 200 225 250
0 10 20 30 40 50 60
KAS FWO Friedman CR
ΔH* (kJ.mol-1)
YVY (%)
75 100 125 150 175 200 225 250
0 100 200 300 400
KAS FWO Friedman CR
ΔH* (kJ.mol-1)
Temperature (oC)
-0.3 -0.2 -0.1 0.0 0.1 0.2 0.3
0 10 20 30 40 50 60
KAS FWO Friedman CR
ΔS* (kJ.mol-1.K-1)
YVY (%)
-0.3 -0.2 -0.1 0.0 0.1 0.2 0.3
50 150 250 350 450
KAS FWO Friedman CR
ΔS* (kJ.mol-1.K-1)
Temperature (oC)
heat from the pyrolysis temperature is only absorbed to remained substances [33, 37].
The entropy of a system measures the degree of random- ness or disorder of the reacting system [37, 73]. In Fig. 10c, d, it is observed that ΔS∗ augments from − 0.24 to 0.16 kJ.
mol−1.K−1 along with the progress of reaction (higher YVY and temperature) with the maximal value of 0.28 kJ.mol−1. K−1 at YVY 0.3. It can be said that the coconut husk pyrolysis occur irreversibly. Fascinatingly, the activation entropy value is negative for YVY of 0.1–0.15 and becomes positive for YVY of 0.2–0.55. Although a negative entropy value which reflects the degree of disorder of product bond dissocia- tion is lower than the initial reactants, it is not the common case in thermal decomposition reactions. Hence, this phe- nomenon is strongly caused by the formation of transition complex compounds (ordered) before they are rearranged to form products (disordered) [33, 34, 36].
Another parameter, the Gibbs free energy, is an expres- sion of the maximum potential work done by a chemical reaction in the environment [37]. As informed in Fig. 10e, f, ΔG∗ along with enhancing YVY and temperature has a posi- tive value. The steepst gradient is found at YVY 0.1–0.2 since the reaction is difficult to occur spontaneously in the transi- tion state [33]. Therefore, an amount of energy should be supplied to stimulate the reaction and it is sourced from heat.
Sequentially, the average ΔG from volatile state KAS, vola- tile state FWO, volatile state Friedman, and volatile state CR methods are 166.10 kJ.mol−1, 165.90 kJ.mol−1, 152.39 kJ.
mol−1, and 166.12 kJ.mol−1. Alhough those values are lower than the calculation using solid-state approach, the escalat- ing pattern of ΔG∗ in this study is in line with Balogun et al.
[36] and Zhao et al. [73].
4 Conclusions
The thermokinetic study of coconut husk pyrolysis using volatile state KAS, volatile state FWO, volatile state Fried- man, and volatile state CR methods has been successfully demonstrated. The activation energy, pre-exponential factor, activation enthalpy, activation entropy, and activation Gibbs free energy have been evaluated. From studies using TGA and DTG, the thermal decomposition process is limited to devolatilation only (until 500 °C). This process is divided into three stages which represent the release of moisture and low molecular weight compounds, active pyrolysis (decom- position of hemicellulose and cellulose), and passive pyrol- ysis (decomposition of cellulose and lignin). The volatile state approach succeeded in calculating the activation energy of coconut husk pyrolysis on average 197.56–198.41 kJ.
mol−1. The activation energy initially signifies because of the lower molecular mobility of biomass and then reduces as the thermal decomposition takes place until completion.
On the other side, the volatile state approach is also proven can describe the relationship between activation energy and activation thermodynamic parameters in the transition state.
The results of activation enthalpy indicate that this process is endothermal. The results of activated entropy strengthen the phenomenon of forming a transition state so the value is initially negative (ordered) and then increases again along with the pyrolysis process taking place to form a product (disordered). In the meantime, the results of activated Gibbs free energy show that this process is not spontaneous so it requires a heat supply.
Supplementary Information The online version contains supplemen- tary material available at https:// doi. org/ 10. 1007/ s13399- 024- 05706-y.
Acknowledgements We thank the National Innovation Research Agency (BRIN) in Cibinong for the TGA analysis.
Author contribution Pandit Hernowo: conceptualization, writing—
original draft, writing—review and editing, and visualization. Soen Steven: writing—review and editing, formal analysis, critical revising, and visualization. Muhammad Maulidin and Alif Gita Arumsari: meth- odology, investigation, and data curation. Yazid Bindar: conceptualiza- tion and formal analysis. Amalia Syauket, Komang Ria Saraswati and Dede Rukmayadi: formal analysis.
Data availability The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.
Declarations
Ethical approval This declaration is not applicable.
Competing interests The authors declare no competing interests.
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