Investigating the Predictive Capabilities of MARS for Biomass Pyrolysis Kinetics: A Case Study on an Oil Palm Empty Fruit Bunch

利用多区域自适应反射光谱法(MARS)预测生物质热解动力学的能力:以油棕空果串为例

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Abstract

This study aimed to emphasize the potential of pyrolysis of oil palm empty fruit bunch (PEFB) biomass as a sustainable energy source and underscore the significance of considering multiple factors in implementing renewable energy. The kinetic analysis of PEFB pyrolysis was carried out using the Friedman, Kissinger-Akahira-Sunose (KAS), Ozawa-Flynn-Wall (OFW), and advanced Vyazovkin (VZ) methods, which yielded matching trends. The average activation energies (E) were found to be 187.40, 165.23, 166.24, and 183.23 kJ/mol for the Friedman, KAS, OFW, and VZ methods, respectively. Additionally, thermodynamic parameters, specifically the changes in enthalpy of activation (ΔH), entropy of activation (ΔS (‡)), and Gibbs free energy of activation (ΔG (‡)) were derived. Average values of ΔH (‡), ΔG (‡), and ΔS (‡) were 161.44, 169.52, and -15.28 kJ/mol K, respectively. E was modeled using multivariate adaptive regression splines (MARS), considering temperature (T), heating rate (β), and conversion (α) as the contributing factors. The MARS model demonstrated a high coefficient of correlation (R (2) = 0.987), low mean absolute error (MEA = 2.71), and root-mean-square error (RMSE = 4.94) to predict E. The results of this study highlight the potential of MARS to accurately represent complex relationships, predict biomass pyrolysis kinetics, and demonstrate the feasibility of PEFB pyrolysis as a sustainable energy source.

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