Catalytic dehydration of ethanol is a key step in the production of polyethylene from renewable raw materials. Obtaining a mathematical model to optimize the ethanol-to-ethylene reactor setup is of great interest to the industry, allowing the optimal design of larger plants and improvements to existing plants. This work presents a phenomenological model of an ethanol dehydration reactor that takes into account 8 chemical reactions and 10 chemical species, considering nonidealities in the reaction rates and axial catalyst activity profile. Additionally, the axial variation of pressure, velocity, and thermodynamics properties are considered in the proposed model. Model validation at different operating conditions shows that the predicted temperature and composition profiles match the data from an industrial plant with relative deviations below 5% and from a pilot plant with relative deviation below 0.4%.

-The use of carbon-based waste biomass in the production of plastics can partially meet the growing demand for plastics in the near future. An interest in the production of ethylene from bioethanol has been renewing, motivated mainly by environmental appeal and economics. The main objective of this work is the development of a mathematical model for simulation and optimization of the production of ethylene by the dehydration of ethanol, improving the performance of the process. The phenomenological model proposed is based on mass, momentum and energy balances for the process. The results obtained are satisfactory in comparison with theoretical results and experimental data found in the literature.

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The catalytic ethanol dehydration route is a reality for the production of polyethylene from renewable sources. Ethanol dehydration process is performed in the presence of acid catalysts, under temperatures ranging from 500 K to 800 K, obtaining ethylene selectivity ranging from 95% to 99% and ethanol conversion of >98%. Despite the favorable values of conversion and selectivity, catalyst deactivation by coking is a well-known phenomenon that occurs in this process. This phenomenon leads to catalyst regeneration cycles, given that the catalyst’s life cycle is dependent on the process operating conditions. Thus, obtaining a mathematical model to optimize the ethanol dehydration process is of great interest to industry, allowing process optimization and optimal design of reactors. This work presents a phenomenological model of an ethanol dehydration fixed-bed reactor considering the catalyst deactivation and several chemical species. The developed mathematical model for catalyst deactivation considers species present in the reaction system as coke precursors. The predictive ability of the model, which has been validated with industrial plant data, are shown in the results, presenting deviations of <5% in the reactor temperature profile.