(397a) Kinetic Analysis of Aquatic Biomass-Duckweed Pyrolysis Using a Hybrid Scheme of Isoconversional Methods, Daem, and a Parallel-Reaction Mechanism

Biomass is considered as a promising alternative to fossil fuels and numerous valuable chemicals can be produced from pyrolysis. However, the optimal design of pyrolysis reactors is challenging due to the complexity of the kinetics of biomass pyrolysis. It is important to develop more detailed kinetic models to investigate the kinetics and optimize the process of biomass pyrolysis. Duckweed as an aquatic plant can grow rapidly in the nutrient-rich wastewater. It has great potentials as the good-quality feedstock for biofuel production, attributed to its low ash and high volatile contents. In this work, a new hybrid kinetic and optimization method was proposed to analyze pyrolysis of duckweed at the heating rates of 10, 20, and 30 K/min. As for the hybrid models, two types of kinetic methods, the TPC (three pseudo-component) DAEM and isoconversional methods, were applied and integrated with the parallel-reaction mechanism. In the hybrid TPC DAEM method, a 46-reaction-step mechanism was developed to simulate thermal decomposition of duckweed. The TPC DAEM was applied to calculate the initial inputs for the kinetic model. A nonlinear multi-objective optimization model was coupled with the kinetic model to achieve the optimal kinetic parameters for the 46-reaction-step mechanism. Comparatively, in the hybrid isoconversional method, the 12 and 13-reaction-step reaction mechanisms were proposed and the isoconversional methods including the Friedman, KAS, and FWO methods were utilized to compute the initial values of kinetic parameters. The nonlinear multi-objective function was then employed to find the optimal values of these parameters. The hybrid kinetic models were used to predict both the overall conversion and the decomposition rate of duckweed during the process of biomass pyrolysis. The model predictions were compared with TGA data of duckweed at all three heating rates and significant matching between the predictions and experimental data was achieved. Finally, the hybrid methods were compared with the conventional isoconversional methods and DAEM to investigate the limitations of the conventional methods and explore the potential of the current proposed hybrid approach.