Reza Azin

Hydrothermal liquefaction (HTL) is a green technology for biocrude production from algae. The global reaction kinetic, component additivity model (CAM), and response surface methodology (RSM) of HTL from high-lipid microalgae (Aurantiochytrium sp.) were evaluated. Lipids, proteins, and carbohydrates of the microalgae cell reacted at different rates and produced the aqueous phase, bio-oil, and gas phase in the kinetic model. Performing global kinetic modelling, understanding the reactions, and the performance of algae for biofuel production by HTL were the main ideas and novelty behind this work. Also, the predictive ability of bio-oil yield was examined by kinetic, CAM, and RSM approaches. MATLAB was utilized to solve the system of ordinary differential equations and calculate the optimum values for Arrhenius kinetic parameters by minimizing the least-square differences between model and experimental yields. R-squared of 0.997 showed that the global kinetic modelling provides a great prediction of bio-oil yields. Activation energies were calculated at 32.31, 38.50, and 46.99 kJ/mol for the conversion of lipids, proteins, and carbohydrates to bio-oil. Furthermore, a maximum bio-oil yield of 53.43 wt% was predicted at 800 K in 2 min. Also, the result of bio-oil prediction by global kinetic modelling compared to CAM and RSM equations. In comparison with the CAM model, the RSM equations showed better adaption with the bio-oil yield at 350 °C and 40 min. However, the kinetic model had the best potential for bio-oil predicting yields of Aurantiochytrium sp. because of the minimum mean absolute error of 2.078%.