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May 24, 2026RSC Advances5 citationsOpen Access

Machine learning-based prediction of biomass pyrolysis kinetics: integrating mechanistic modeling and compositional features

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MAMuhammad AsifLHLuqman HakeemCYChengxi Yao

Key Points

  • This research aims to predict the kinetic triplet of biomass pyrolysis using machine learning and mechanistic modeling.
  • Utilized machine learning to analyze descriptors related to sapodilla-leaves pyrolysis.
  • Applied Coats–Redfern thermogravimetric analysis (TGA) for kinetic and thermodynamic parameter fitting.
  • Successfully predicted the kinetic triplet of pyrolysis using machine learning techniques.
  • Identified stage-specific kinetic and thermodynamic parameters through the mechanistic interpretation of the data.

Abstract

ML predicted the kinetic triplet of sapodilla-leaves pyrolysis from descriptors, while Coats–Redfern TGA fitting provided stage-specific kinetic and thermodynamic parameters for mechanistic interpretation.

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Cite This Study

Asif et al. (2026) studied this question.

synapsesocial.com/papers/6a1295e248a0ea1665672360https://doi.org/10.1039/d6ra01011c
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