This research aims to predict the kinetic triplet of biomass pyrolysis using machine learning and mechanistic modeling.
Utilized machine learning to analyze descriptors related to sapodilla-leaves pyrolysis.
Applied Coats–Redfern thermogravimetric analysis (TGA) for kinetic and thermodynamic parameter fitting.
Successfully predicted the kinetic triplet of pyrolysis using machine learning techniques.
Identified stage-specific kinetic and thermodynamic parameters through the mechanistic interpretation of the data.
Abstract
ML predicted the kinetic triplet of sapodilla-leaves pyrolysis from descriptors, while Coats–Redfern TGA fitting provided stage-specific kinetic and thermodynamic parameters for mechanistic interpretation.