Machine Learning-Based Prediction of the Gasification Reaction Rates of Biomass-Derived Char

Gasification reaction rates of biomass-derived char were predicted using a machine learning model based on fuel properties. A comparison among a kinetic model, a machine learning model, and a hybrid model confirmed that the prediction formula based solely on machine learning demonstrated high accuracy in predicting the gasification reaction rates of biomass-derived char. While the kinetic model, originally developed for coal, requires manual parameter tuning to be applied to biomass fuels, the machine learning model showed potential for making accurate predictions without the need for manual tuning. Looking ahead, we aim to further improve the accuracy of the prediction formula using machine learning, thereby facilitating the exploration of diverse fuel applications and contributing to the realization of a carbon-neutral society.