Pyrolysis mechanism study on xylose by combining experiments, chemical reaction neural networks and density functional theory.
Journal:
Bioresource technology
PMID:
40222487
Abstract
Chemical reaction neural networks (CRNN) and density functional theory (DFT) are gaining attention in biomass pyrolysis mechanism research. Reaction pathways are often speculated based on a single method, influenced by expert knowledge. To address this, the pyrolysis mechanism of xylose, a hemicellulose model compound, is studied using thermogravimetric-Fourier transform infrared spectroscopy (TG-FTIR), CRNN, and DFT. Based on the TG-FTIR measured products, seven main pyrolysis products of xylose are applied. A CRNN model of 8 species (7 + 1) and 10 reactions, including kinetic parameters, is established, achieving an MAE below 2 × 10. Furthermore, the detailed reaction pathways and potential energy surfaces of evolution into each species are studied through DFT calculations. The activation energy for the xylose ring-opening, ring-condensation, and dehydration reactions, as obtained from the CRNN model, are 152.78 kJ/mol, 485.81 kJ/mol, and 320.01 kJ/mol, respectively. The deviations from the theoretical DFT calculations are less than 37 %, demonstrating good agreement. Compared to dehydration and ring condensation reactions, xylose is most susceptible to ring-opening reactions to form d-xylose. d-xylose easily undergoes hemi-acetalization, isomerization and dehydration at the 3-OH + 2-H, 5-OH + 4-H and 4-OH + 3-H sites. Xylose is most susceptible to dehydration reactions at the 1-OH + 2-H and 2-OH + 3-H sites to generate dehydrated xylose. Finally, xylose can also generate furfural through a cyclic condensation reaction. The conclusion can promote the improvement and development of hemicellulose pyrolysis kinetics models, and the research process can provide experience for the pyrolysis mechanism of other materials.