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Development of a global kinetic model based on chemical compositions of lignocellulosic biomass for predicting product yields from hydrothermal liquefaction

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  • Wang, Haoyu
  • Han, Xue
  • Zeng, Yimin
  • Xu, Chunbao Charles

Abstract

This study aimed to develop a global kinetic model to predict product yields from hydrothermal liquefaction (HTL) of lignocellulosic biomass based on its chemical compositions (contents of cellulose, hemicellulose, and lignin). HTL experiments were carried out with biomass model compounds (cellulose, xylan, and lignin) and lignocellulosic biomass (bamboo, cornstalk, and pinewood) at various temperatures (225–300 °C) and reaction times (10–60 min) with K2CO3 catalyst. Out of the three major components of lignocellulosic biomass, lignin was found to be the main contributor to bio-oil formation. A universal reaction network was proposed, and a kinetic model was developed based on the experimental results obtained from HTL of biomass model compounds. The kinetic parameters were determined by the lease-squares method using a MATLAB optimization function. Assuming no interactions among the components (cellulose, hemicellulose, and lignin) of lignocellulosic biomass during HTL, a global kinetic model was developed based on the chemical compositions of lignocellulosic biomass and the kinetic parameters obtained from the model compound. The developed model was validated with our experimental results from HTL of bamboo, cornstalk, and pinewood and the publicly available HTL data in literature obtained with lignocellulosic biomass feedstocks.

Suggested Citation

  • Wang, Haoyu & Han, Xue & Zeng, Yimin & Xu, Chunbao Charles, 2023. "Development of a global kinetic model based on chemical compositions of lignocellulosic biomass for predicting product yields from hydrothermal liquefaction," Renewable Energy, Elsevier, vol. 215(C).
    • Handle: RePEc:eee:renene:v:215:y:2023:i:c:s0960148123008625
    DOI: 10.1016/j.renene.2023.118956
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