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Systematical analysis and application of distributed activation energy model (DAEM) with Weibull distribution for pyrolysis kinetics of lignocellulosic biomass

Author

Listed:
  • Yang, Yantao
  • Jiang, Mingshen
  • Song, Lei
  • Shen, Yilin
  • Lei, Tingzhou
  • Cai, Junmeng

Abstract

The distributed activation energy model (DAEM) is a comprehensive and accurate kinetic model for describing the thermal decomposition kinetics of complex materials. The Gaussian distribution is commonly used for representing the activation energy distribution, however, it is symmetric and cannot reflect the reactivity asymmetry involved in complex chemical kinetics. The Weibull distribution offers an alternative to represent the distribution of activation energies. This study performed a systematical investigation of the DAEM with Weibull distribution, focusing particularly on its asymmetric characteristics. Additionally, the DAEM with Weibull distribution was applied to analyze the pyrolysis kinetics of rice straw and cotton stalk. The theoretical analysis results showed that the DAEM with Weibull distribution could provide abundant flexibility to elucidate the asymmetric reactivity of complex chemical kinetics. The pyrolysis processes of rice straw and cotton stalk could be deconvoluted into several sub-processes, which could be accurately described by the DAEMs with Weibull distribution. The obtained Weibull distributions of activation energies for those deconvoluted sub-processes validated their asymmetric reactivities. It is expected that the results could help in exploring the kinetic mechanisms of lignocellulosic biomass pyrolysis and facilitate the application of the DAEM with Weibull distribution in analyzing complex chemical kinetics.

Suggested Citation

  • Yang, Yantao & Jiang, Mingshen & Song, Lei & Shen, Yilin & Lei, Tingzhou & Cai, Junmeng, 2024. "Systematical analysis and application of distributed activation energy model (DAEM) with Weibull distribution for pyrolysis kinetics of lignocellulosic biomass," Renewable Energy, Elsevier, vol. 237(PA).
  • Handle: RePEc:eee:renene:v:237:y:2024:i:pa:s0960148124016173
    DOI: 10.1016/j.renene.2024.121549
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