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.
Niaei
A
A
Petroleum Research Technology Laboratory, Department of Applied Chemistry and Chemical Engineering, University of Tabriz, Tabriz, Iran. niaei@yahoo.com
Salari
D
D
Aghazadeh
F
F
Caylak
N
N
Sepehrianazar
A
A
D019840:2-Propanol / Q000737:chemistry*; D002384:Catalysis; D008670:Metals / Q000737:chemistry*; D008855:Microscopy, Electron, Scanning; D046529:Microscopy, Electron, Transmission; D016571:Neural Networks, Computer; D010084:Oxidation-Reduction; D013696:Temperature; D014961:X-Ray Diffraction
D008670:Metals; D019840:2-Propanol