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Maleic anhydride is a key intermediate in the chemical industry, predominantly produced through the partial oxidation of n-butane over vanadium-phosphorus-oxide (VPO) catalysts. This reaction is accompanied by side reactions that lead to the formation of undesired by-products, primarily CO and CO2. In this work, a previously developed mathematical model of a fixed-bed tubular reactor was extended to include a catalyst activity function accounting for catalyst deactivation, and the kinetic parameters were optimized using experimental data from an industrial reactor at Koksara d.o.o. Lukavac. The model describes the partial oxidation of n-butane to maleic anhydride through multiple reactions, with reaction rates expressed as functions of temperature, partial pressures, and catalyst activity. Numerical simulations were performed using MATLAB, employing a nonlinear least-squares solver to minimize the deviation between the predicted and measured temperature profiles along the reactor. The validated model showed good agreement with experimental data, demonstrating its capability to accurately simulate reactor behavior under typical industrial conditions. Parametric studies were conducted to analyze the effects of inlet n-butane and oxygen flow rates, reaction mixture temperature, and pressure on the formation of CO and CO2. The results indicate that by-product formation is strongly influenced by the oxygen/n-butane ratio, temperature, pressure, and the catalyst oxidation state. Higher oxygen flow rates and elevated temperatures increase CO and CO2 formation, while lower values reduce their production. Changes in n-butane flow have a minor effect on CO2, but more pronounced effects on CO due to the interplay between partial and complete oxidation at different catalyst sites. Increasing the inlet pressure enhances by-product formation by increasing reactant concentrations, whereas reduced pressure decreases CO and CO2 formation. The developed model provides a practical tool for understanding and optimizing industrial maleic anhydride production. It offers insights into the effects of key process parameters on by-product formation, supporting improved reactor operation, reduced trial-and-error experimentation, and more efficient industrial process design.
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Karić et al. (2025) studied this question.
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