General distributed activation energy model (G-DAEM) on co-pyrolysis kinetics of bagasse and sewage sludge

Lin, Yan; Tian, Ye; Xia, Yuqing; Fang, Shiwen; Liao, Yanfen; Yu, Zhaosheng; Ma, Xiaoqian

doi:10.1016/j.biortech.2018.11.051

Cited by 52 publications

(15 citation statements)

References 40 publications

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“…The use of the DSC result enabled us to predict the number of pseudo-components in cellulose and lignin thermogravimetric pyrolysis. To our knowledge, there is still limited work in the literature that correlates the kinetics study of biomass pyrolysis to DSC results in determining the number of pseudo-components [ 5 , 12 , 31 , 32 , 33 , 34 , 43 , 44 , 45 , 46 , 47 ]. It is also important to note that the use of aggressive data filtering and a higher heating rate may conceal minor DTG peaks.…”

Section: Resultsmentioning

confidence: 99%

“…Nevertheless, this approach tends to simplify the pyrolysis sequence's proper mechanistic behavior by depleting minor reactions with a mathematic generalization. The use of pseudo-components has also been developed for 4 to 5-pseudo-components to describe the decomposition of plastic waste, lignocellulosic, and marine biomass [ 31 , 32 , 33 , 34 ]. Two studies reported a detailed approach with more pseudo-components for cellulose, hemicellulose, and lignin [ 6 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

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Multi-distribution activation energy model on slow pyrolysis of cellulose and lignin in TGA/DSC

Kristanto

Azis

Purwono

2021

Heliyon

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Developing a kinetic model to analyze the multi-step reaction of biomass pyrolysis is pivotal to elucidate the mechanism of the pyrolysis. For this purpose, a model-fitting method such as multi-distribution the Distributed Activation Energy Model (DAEM) is one of the most reliable methods. DAEM with 4 different distribution functions of Gaussian, Logarithmic, Gumbel, and Cauchy was utilized to characterize the pyrolysis of cellulose and lignin during Thermogravimetric Analysis/Differential Scanning Calorimetry (TGA/DSC) instrumentation. By comparing Derivative Thermogravimetry (DTG) and DSC profiles, determination of pseudo-components can be done more accurately. A kinetics analysis on the pyrolysis of cellulose with a single Gaussian distribution DAEM yielded a single activation energy of 178 kJ mol −1 with a narrow standard deviation. This result was justified by a single and dominant endothermic peak followed by minor exothermic peaks in the DSC result. For lignin pyrolysis, the presence of multiple peaks is characterized by four pseudo-components in DAEM with activation energies of 157, 174, 194, and 200 kJ mol −1 . These pseudo-components were confirmed by the DSC result which indicated the occurrences of two exothermic peaks with two lesser exothermic or possibly endothermic peaks at the same temperature range. These findings imply the importance of DSC to support a kinetics study of thermogravimetric pyrolysis.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-distribution activation energy model on slow pyrolysis of cellulose and lignin in TGA/DSC

Kristanto

Azis

Purwono

2021

Heliyon

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“…As commented above, few approximations of p s ( x , s ) can be found in the literature. The one recently released by Lin et al 52 can be considered the most precise as compared to previous approximations 15,17,20 . It works in the ranges 4 ≤ x ≤ 200 and −2.5 ≤ s ≤ 2.5, and has the structure of Equation (15), in which h s ( x , s ) is of the rational type and can be evaluated as:

h_{s} false(x, s false) = \frac{a_{1} x + b_{1} s + c_{1}}{x + b_{2} s + c_{2}}

where a 1 = 0.00038236, b 1 = −0.98071110, c 1 = −1.96306291, b 2 = 0.36195384, and c 2 = 1.47704119.…”

Section: Resultsmentioning

confidence: 99%

“…There are other mathematical expressions with a very slightly lower error than that obtained with these parameters, but they are only valid for s = 0 19 . Therefore, the five‐parameters approximation by Lin et al 52 will be used as reference in the present work. Following the nomenclature employed by the authors, it will be named as the Lin_New approximation.…”

Section: Resultsmentioning

confidence: 99%

Combined kinetic analysis of solid‐state reactions: The integral method (ICKA)

Casal

Marbán

2020

Int J of Chemical Kinetics

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In this work, we propose the first Integral method for the Combined Kinetic Analysis (ICKA) of solid-state reactions typically performed in a thermogravimetric analyzer. The ICKA method prevents the systematic inaccuracies inherent to all the differential methods, including the standard CKA method. Two main achievements have been made for implementing the method: (1) the most accurate approximation for the general temperature integral yet developed, and (2) a general integral form of the kinetic model of the type g (α) = (abcZ) −1 [1 − (1 − α a) b ] c , where Z is a parameter evaluated together with the preexponential factor and a, b, and c are fitting parameters. This expression allows any known kinetic model to be exactly or very closely reproduced. Together, the two developments yield an equation for the conversion, α, that has been successfully fitted to simulated conversion values of single-step reaction processes following different kinetic models. The curve fitting resulted in the same values of the kinetic and model parameters as those from which the simulated conversion curves were originally built, proving the validity of the ICKA method.

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“…Although there are studies regarding the kinetic modelling of sewage sludge during pyrolysis, they were unable to provide the details regarding the product properties or immobilisation of heavy metals (Lin et al, 2019). This is mainly due to the heterogeneous nature of sewage sludge and the limitations of these models in predicting complex reactions during sewage sludge pyrolysis (Sharma et al, 2015).…”

Section: Perspectives and Challengesmentioning

confidence: 99%

Valorisation of sewage sludge through pyrolysis : product properties and immobilisation of heavy metals

Udayanga¹

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General distributed activation energy model (G-DAEM) on co-pyrolysis kinetics of bagasse and sewage sludge

Cited by 52 publications

References 40 publications

Multi-distribution activation energy model on slow pyrolysis of cellulose and lignin in TGA/DSC

Multi-distribution activation energy model on slow pyrolysis of cellulose and lignin in TGA/DSC

Combined kinetic analysis of solid‐state reactions: The integral method (ICKA)

Valorisation of sewage sludge through pyrolysis : product properties and immobilisation of heavy metals

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