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Study on the pyrolysis process of engineered wood material with multicomponent modeling and peaks deconvolution analysis

Author

Listed:
  • Xu, Li
  • Chen, Yu
  • Song, Xiaokai
  • Qi, Yongfeng
  • Li, Shengcai
  • Xu, Hao

Abstract

Knowledge of reaction kinetics is crucial in developing woody biomass energy conversion systems and understanding its fire behaviors. A suitable pathway that would more reliably extracting the kinetics of the pseudo-components degradation during the pyrolysis of wood-based combustibles was put forward. In particular, the Gaussian symmetric and Bi-Gaussian asymmetric function were identified and employed separately to deconvolve the overlapped peaks to capture the components reaction shapes for sassafras wood and medium density fiberboard degradation, respectively. Upon deconvolution, the overlapped peak of the mass loss rate profiles is separated into several sub-peaks corresponding to different pseudo-components, and systematic kinetic analysis of the pseudo-components was performed by Friedman differential iso-conversional, master plot and model reconstruction methods. Regarding sassafras wood, the estimated average Eα values for pseudo hemicellulose, cellulose and lignin were 176.95 kJ/mol, 178.54 kJ/mol, and 201.47 kJ/mol. As to MDF, the determined average Eα for pseudo resin, hemicellulose, cellulose and lignin were found to vary within the range of 123.18, 143.27, 174.51 and 202.02 kJ/mol, respectively. Based on model reconstruction, the modified reaction models of pseudo components were found to fit well with the experimental data. Finally, the enthalpy, the Gibbs free energy, and entropy were also determined for the pyrolysis thermodynamics. The procedures illustrated in the present work could be applicable to a much wider range of similar kinetic analysis and fire numerical simulation in future works.

Suggested Citation

  • Xu, Li & Chen, Yu & Song, Xiaokai & Qi, Yongfeng & Li, Shengcai & Xu, Hao, 2025. "Study on the pyrolysis process of engineered wood material with multicomponent modeling and peaks deconvolution analysis," Renewable Energy, Elsevier, vol. 248(C).
  • Handle: RePEc:eee:renene:v:248:y:2025:i:c:s0960148125008201
    DOI: 10.1016/j.renene.2025.123158
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