Determination of Kinetic and Thermodynamic Parameters of Biomass Gasification with TG-FTIR and Regression Model Fitting

Viktória Zsinka, Bálint Levente Tarcsay and Norbert Miskolczi ()
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Viktória Zsinka: MOL Department of Hydrocarbon and Coal Processing, Research Centre of Biochemical, Environmental and Chemical Engineering, University of Pannonia, Egyetem u. 10, H-8200 Veszprém, Hungary
Bálint Levente Tarcsay: Department of Process Engineering, Research Centre of Biochemical, Environmental and Chemical Engineering, University of Pannonia, Egyetem u. 10, H-8200 Veszprém, Hungary
Norbert Miskolczi: MOL Department of Hydrocarbon and Coal Processing, Research Centre of Biochemical, Environmental and Chemical Engineering, University of Pannonia, Egyetem u. 10, H-8200 Veszprém, Hungary

Energies, 2024, vol. 17, issue 8, 1-15

Abstract: In this study, the decomposition of five different raw materials (maize, wheat and piney biomass, industrial wood chips and sunflower husk) were investigated using the TG-FTIR method to obtain raw data for model-based calculations. The data obtained from the thermogravimetric analysis served as a basis for kinetic analysis with three different isoconversional, model-free methods, which were the KAS, FWO and Friedman methods. Afterwards, the activation energy and the pre-exponential factor were determined, and no significant difference could be identified among the used methods (difference was under 5%), achieving 203–270 kJ/mol of E a on average. Thereafter, the thermodynamic parameters were studied. Based on the TG-FTIR data, a logistic regression model was fitted to the data, which gives information about the thermal degradation and the obtained components with different heating rates. The FTIR analysis resulted in differential peaks corresponding to the studied components that were detected within the temperature range of 350–380 °C. The primary degradation processes occurred within a broader temperature range of 200–600 °C. Accordingly, in this work, the use of logistic mixture models as an alternative to traditional kinetic models for the description of the TGA process was also investigated, reaching adequate performance in fitting by a validation data coefficient of determination of R 2 = 0.9988.

Keywords: TG-FTIR; kinetics; logistic regression model; activation energy; biomass (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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