A novel pseudo-multicomponent isoconversional approach for the estimation of kinetic and thermodynamic parameters of potato stalk thermal degradation.

This study examined the thermal degradation kinetics of potato stalk (PS) using a unique isoconversional technique. The kinetic analysis was assessed based on mathematical deconvolution approach with model-free method. The thermogravimetric analyzer (TGA) was used for the non-isothermal pyrolysis of PS at different heating rates. The Gaussian function was then used to extract three pseudo-components (PC) from the TGA findings. The average activation energy value for PS (125.99, 122.79, and 122.85 kJ/mol), PC1 (106.78, 103.83, and 103.92 kJ/mol), PC2 (120.26, 116.31, and 116.55 kJ/mol), and PC3 (373.12, 379.40, and 378.93 kJ/mol) based on OFW, KAS, and VZN model respectively. Furthermore, an artificial neural network (ANN) was used to forecast the thermal degradation data. The findings demonstrated a significant correlation between real and anticipated values. The kinetic and thermodynamic results, along with ANN are critical for constructing pyrolysis reactors that might use waste biomass as a potential feedstock for bioenergy production.