Machine learning-based prediction of biomass pyrolysis kinetics: integrating mechanistic modeling and compositional features

) and identifying volatile matter, carbon content, and O/C and H/C ratios as influential compositional descriptors. The combined use of mechanistic analysis and interpretable ML provides a proof-of-concept comparison between stage-specific fitting and descriptor-based prediction, while also highlighting the present limitations in predictive robustness and generalizability.