Assessment of CO₂ biofixation and bioenergy potential of microalga Gonium pectorale through its biomass pyrolysis, and elucidation of pyrolysis reaction via kinetics modeling and artificial neural network

This study investigates CO₂ biofixation and pyrolytic kinetics of microalga G. pectorale using model-fitting and model-free methods. Microalga was grown in two different media. The highest rate of CO₂ fixation (0.130 g/L/day) was observed at a CO₂ concentration of 2%. The pyrokinetics of the biomass was performed by a thermogravimetric analyzer (TGA). Thermogravimetric (TG) and derivative thermogravimetric (DTG) curves at 5, 10 and 20°C/min indicated the presence of multiple peaks in the active pyrolysis zones. The activation energy was calculated by different model-free methods such as Friedman, Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), and Popescu. The obtained activation energy which are 61.7–287 kJ/mol using Friedman, 40.6–262 kJ/mol using FWO, 35–262 kJ/mol using KAS, and 66.4–255 kJ/mol using Popescu showed good agreement with the experimental values with higher than 0.96 determination coefficient (R²). Moreover, it was found that the most probable reaction mechanism for G. pectorale pyrolysis was a third-order function. Furthermore, the multilayer perceptron-based artificial neural network (MLP-ANN) regression model of the 4-10-1 architecture demonstrated excellent agreement with the experimental values of the thermal decomposition of the G. pectoral. Therefore, the study suggests that the MLP-ANN regression model could be utilized to predict thermogravimetric parameters.