Catalytic oxidation of 2-Propanol over (Cr,Mn,Fe)-Pt/gamma-Al2O3 bimetallic catalysts and modeling of experimental results by artificial neural networks.

The catalytic activity of transition metals (Cr,Mn,Fe) supported on the Pt/gamma -Al(2)O(3) industrial catalyst was investigated to bring about the complete oxidation of 2-Propanol. Catalytic studies were carried out under atmospheric pressure in a fixed bed reactor. X-ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscopy (TEM) and ICP-AES techniques were used to characterize a series of catalysts. Results showed that the Pt-Mn/gamma -Al(2)O(3) (3.88 wt.%Mn) at calcination temperature of 300 degrees C was the most promising catalyst based on activity, which might be contributed to the quantity of manganese loading, the favorable synergetic effects between Pt and Mn and the well-dispersed bimetallic phase. An artificial neural networks (ANN) model was developed to predict the performance of catalytic oxidation process over Pt-Mn/gamma -Al(2)O(3) bimetallic catalyst based on experimental data. For this purpose the Levenberg-Marquardt (LM) learning algorithm was employed to train the model by using laboratory experimental data. A comparison between the predicted results of the designed ANN model and experimental data was also conducted. The developed model can describe the catalytic oxidation over bimetallic catalysts under different conditions.