Machine learning-based prediction of biomass pyrolysis kinetics: integrating mechanistic modeling and compositional features
Abstract
) 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.
Fields of Study & Subjects
Thermochemical Biomass Conversion Processes
Thermal and Kinetic Analysis
Heat transfer and supercritical fluids
Publication details
- Journal / source
- RSC Advances
- Publisher
- Royal Society of Chemistry (RSC)
- Volume
- 16
- Issue
- 30
- Pages
- 28036–28047
- Publication date
- 1 January 2026
- Language
- EN