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Multi-Stage Kinetic Scheme for Slow Devolatilization of Chlorella vulgaris from Model-Free Kinetics and Simultaneous Global Optimization

Publicada
Servidor
Preprints.org
DOI
10.20944/preprints202605.0733.v1

The global energy crisis drives the search for sustainable biomass resources. Microalgae, particularly Chlorella vulgaris, represent a promising third-generation feedstock for bi-ochar and biofuels. However, detailed kinetic schemes for its slow devolatilization are still scarce. This work compares the thermogravimetric behavior of commercially Chlorella vulgaris with data reported in the literature under identical experimental conditions and develops a multi-stage kinetic scheme using model-free methods and simultaneous global optimization. A complete set of kinetic parameter is provided in conjunction with a mass wights in order to close the reaction scheme. Biological composition of microalgae was experimentally determined resulting in 21.20, 59.30 and 19.50% for carbohydrates, protein and lipids. Thermogravimetric (TG/DTG) analyses were conducted with 5, 10 and 20 °C/min heating rates. Activation energy distribution was obtained through isoconversional model-free methods (Fried-man, FWO, KAS and Starink). A parallel multi-stage kinetic model was subsequently optimized globally against the experimental data to determine the complete kinetic tri-plet (E, A, n). TG/DTG profiles exhibited in general a good agreement with the literature refer-ence in the number and the temperature of features, peaks and shoulders, however different in intensity probably due to the different amount of biological components, carbohydrates, proteins and lipids. The multi-stage model achieved excellent fitting quality accounting for 5 reactions. Activation energies for the principal devolatilization stages ranged from 140 to 220 kJ/mol, while ln(A) values lay between 20 and 35 s⁻¹. The findings an results provided by this study is considered useful for the community con-tributing with discussion and a robust kinetic scheme suitable for example for slow pyrolysis process simulation.

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