Statistical modeling and optimization of low-temperature oxidation dehydrogenation of propane process using manganese catalyst based on CuBTC organic metal framework

Because of the rising global demand for propylene, various extensive studies and research have been done in order to develop alternative ways that are both more energy-efficient and require less energy. In this research, CuBTC is used as a manganese catalyst base in the oxidative dehydrogenation of propane to produce propylene. The wet impregnation method is used to manufacture the catalysts.

Wet impregnation is used to prepare the catalysts, which is a step in the manufacturing process. Analyses such as FTIR, XRD, BET, SEM, and EDX are used to examine and describe catalysts that have been created. On the basis of the central composition method, we have investigated the impacts of reaction temperature, manganese loading percentage, oxygen-to-propylene ratio, and their interactions on the synthesis of propylene in this study. The central composite method's input parameters include manganese concentrations ranging from 1 to 5 percent, a propane-to-oxygen ratio ranging from 1 to 3 percent, and a temperature ranging from 140 to 280 degrees Celsius.

After that, it is shown that the projected models for propane conversion, propylene selectivity, and oxidative dehydrogenation efficiency percentage are about 95 percent based on reactor testing and evaluation of the Design-Expert software results. It was possible to improve the efficiency of the oxidation dehydration process by 4.9 percent by using a conversion percentage of 28.38 percent, a selectivity of 18.14 percent at 278 degrees Celsius, a metal oxide loading of 3.74 percent, and propane to oxygen ratio of 1.5 percent. When laboratory data were compared to predicted data, the correlation coefficient was 93% in favor of the laboratory data.