|Siti Jamilatun||Department of Chemical Engineering, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Jalan Kapas 9, Yogyakarta 55166, Indonesia|
|Budhijanto||Department of Chemical Engineering, Faculty of Engineering, Universitas Gadjah Mada, Jalan Grafika 2, Yogyakarta 55284, Indonesia|
|Rochmadi||Department of Chemical Engineering, Faculty of Engineering, Universitas Gadjah Mada, Jalan Grafika 2, Yogyakarta 55284, Indonesia|
|Avido Yuliestyan||Department of Chemical Engineering, Faculty of Industrial Technology, Universitas Pembangunan Nasional “Veteran” Yogyakarta, Jalan SWK 104, Yogyakarta 55283, Indonesia|
|Muhammad Aziz||-Institute of Innovative Research, Tokyo Institute of Technology, i6-25, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550 Japan -Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Megu|
|Jun-ichiro Hayashi||Institute for Material Chemistry and Engineering, Kyushu University, Kasuga 816-8580 Japan|
|Arief Budiman||Department of Chemical Engineering, Faculty of Engineering, Universitas Gadjah Mada, Jalan Grafika 2, Yogyakarta 55284, Indonesia|
The pyrolysis characteristics of Spirulina platensis residue (SPR) with silica–alumina catalysts were investigated using thermogravimetric analysis (TGA). The effects of differing amounts of catalysts on thermochemical behavior and kinetics parameters (pre-exponential factor in Arrhenius equation [A] and activation energy [Ea]) were studied. The experiment was carried out from 30 to 1000? at a heating rate of 20?/min for the case of non-catalytic and catalytic pyrolysis (silica–alumina). For the catalytic pyrolysis, also of interest were the catalyst-to-SPR weight ratios of 1:1 and 1:2. The TGA curve and differential thermogravimetric peak analysis results suggest that the use of catalysts in pyrolysis (particularly at a catalyst-to-SPR weight ratio of 1:1) reduces both pyrolysis time and temperature range to 14.68 min and 230–555?, respectively. The kinetic parameters were then calculated in a one-step global non-isothermal model and solved using a least squares method in MATLAB. The presence of catalyst was able to reduce Ea to the lowest value from 41.10 kJ/mol (without catalyst) to 40.77 kJ/mol (weight ratio of 1:2) and 39.46 kJ/mol (weight ratio of 1:1) in Zone 1. However, the increase of catalyst quantity was not in line with the increase of reaction rate constant (k) and resulted in reasonably low A of, respectively, 593.30, 406.31, and 266.37.
Activation energy, Catalytic pyrolysis; Pre-exponential factor; Spirulina platensis residue
By 2040, the world’s energy demand is estimated to have increased by 56%, with fossil fuels still contributing about 80% of the required supply (Anggorowati et al., 2018). This expectation has motivated an acceleration of the utilization of renewable sources, including algae. Microalgae such as Spirulina platensis have tremendous potential to be converted as a renewable fuel (Pradana et al., 2018). After the removal of lipid content by extraction, biomass in the form of Spirulina platensis residue (SPR), used as a biofuel material, has the potential to be converted through a process of pyrolysis (Jamilatun et al., 2017a; Kusrini et al., 2018; Jamilatun et al., 2019a).
Generally, a biofuel derived from the pyrolysis of SPR exhibits several deficiencies, including the presence of high levels of oxygenous and nitrogenous compounds. However, these disadvantages can be overcome through the use of a catalyst to reduce the levels of oxygenous and nitrogenous compounds (Bui et al., 2016). One suitable catalyst for upgrading the bio-oil is silica–alumina, which is widely used to support the production of petrochemicals, chemicals, and energy. The Al2O3 can promote the formation of aromatic compounds, such as polycyclic aromatic hydrocarbons. And with its low acidity, SiO2 can also help remove oxygenated compounds and inhibit the formation of coke on the catalyst thanks to the porous medium (Aho et al., 2013; Busca, 2019; Jamilatun et al., 2019c). Jamilatun (2019c) reported that the catalytic pyrolysis on SPR using a silica–alumina catalyst (surface area of 240.553 m2/g, pore size of 3.3 nm, average pore volume of 0.199 cm3/g, and SiO2/Al2O3 of 1.71) could reduce oxygenated compounds 37.47% (without catalyst) to 12.82% (a decrease of 65.80%). Further investigation on the catalytic thermal decomposition of SPR is crucially demanded to accelerate the development of bio-oil production (Sunarno et al., 2018; Jamilatun et al., 2019b; Jamilatun et al., 2019c). Its kinetic analysis and the thermal decomposition mechanisms necessary to obtain pre-exponential factor (A) and the reaction kinetics constant (k) from catalytic pyrolysis are the critical tools for designing reactor developments for industrial-scale bio-oil production (Li et al., 2013).
One effective method of analyzing both thermal decomposition and reaction kinetics is thermogravimetry (TG). Thermogravimetric analysis (TGA) has become a proven technique for investigating the non-catalytic pyrolysis of algae, including Chlorella sp., Tetraselmis suecica (Kassim et al., 2014), Spirulina extraction wastes (Li et al., 2013; Jamilatun et al., 2017b), and Sargassum sp. (Kim et al., 2013). On the other hand, there is minimal research on catalytic pyrolysis using the TGA method with microalgae raw materials, but Jamilatun et al. (2017b) reported that analysis of thermal decomposition and pyrolysis reaction kinetics of SPR with TGA indicated that the activation energy (Ea) for the heating rate of 20?/min for Zones 1 and 2 was 41.102 kJ/mol and 0.0001240 kJ/mol. However, there has been almost no research work conducted on thermochemistry and kinetics of catalytic pyrolysis reactions using TGA. For this reason, research on catalytic pyrolysis of SPR needs to be developed, particularly with regard to pyrolysis thermochemical behavior and kinetics.
Based on TGA data, reaction kinetics can be approximated using a one-step reaction model derived from the Flynn–Wall–Ozawa and Kissinger–Akahira–Sunose methods (Kassim et al., 2014; Quan et al., 2016). In this method, a one-stage global single-reaction model can be determined via various approaches, such as the distributed activation energy model (DAEM), the iso-conventional method from Vyazovkin (Marriott et al., 2016), and nonlinear least squares regression (Kim et al., 2013). To the best knowledge of the authors, there is no previous study on biomass kinetic reactions incorporating natural and straightforward processes. Hence, as an alternative to establishing a one-stage global single-reaction model, a reaction model using a least squares method and MATLAB simulation tools was developed in this study. The data of catalytic thermal decomposition characteristics of SPR in TGA are required to determine the reaction kinetics, and the kinetics data are necessary to design the pyrolysis equipment for bio-oil production (Kim et al., 2013; Kassim et al., 2014; Quan et al., 2016).
This paper discusses the characteristics of thermal decomposition using a silica–alumina (SiO2/Al2O3) catalyst, including the extent of the catalyst’s effect on SPR weight reduction. This work uses TG and differential thermogravimetric (DTG) curves to obtain the temperature ranges for Stage I (drying), Stage II (pyrolysis), and Stage III (gasification). The kinetic reaction was calculated through a one-step global non-isothermal model and solved with a least squares fitting using MATLAB simulation.
This study evaluated TG-DTG analyses as a feasible method for determining SPR pyrolysis characteristics. The release of volatile matter, seen in the DTG curve as a sharp peak, was observed in non-catalytic pyrolysis. In contrast, volatile matter release was relatively similar in the presence of the catalyst. Based on TG-DTG data, the presence of catalyst was able to reduce the pyrolysis time and temperature range, with observed data of 230–570? (15.10 min); 230–565? (15.07 min), and 230–555? (14.68 min) for the cases of no catalyst, catalyst-to-SPR weight ratio of 1:2, and catalyst-to-SPR weight ratio of 1:1, respectively. In the same case sequence, the kinetic study reported the reduction of activation energy in Zone 1 as 41.10, 40.77, and 39.46 kJ/mol. However, the pre-exponential factor supports also appeared lower, at 593.30, 406.31, and 266.37. The reduction of activation energy due to the use of the catalyst is not in line with the increase of k due to the quite low pre-exponential factor. However, the rate in Zone 2 was not significantly affected because the values of the kinetic parameters were rather small and relatively similar to one another, in the range of 8.53×10?5–1.42×10?4 kJ/mol and 0.0505–0.0488 for each activation energy and pre-exponential factor, respectively.
authors are very grateful to the Ministry of Research and Technology/National
Agency for Research and Innovation of the Republic of Indonesia for financial
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