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.

Automated summary

This study investigated the thermal degradation kinetics of potato stalk using an isoconversional technique and mathematical deconvolution approach. The results showed the average activation energy values for different components of potato stalk and demonstrated the correlation between real and anticipated values through an artificial neural network. These findings are crucial for developing pyrolysis reactors that can utilize waste biomass for bioenergy production.