Catalytic oxidation of 2-Propanol over (Cr,Mn,Fe)-Pt/γ-Al 2 O 3 bimetallic catalysts and modeling of experimental results by artificial neural networks
Catalytic oxidation of 2-Propanol over (Cr,Mn,Fe)-Pt/γ-Al 2 O 3 bimetallic catalysts and modeling of experimental results by artificial neural networks
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(Cr,Mn,Fe)-Pt/γ-Al 2 O 3 双金属催化剂催化氧化 2-丙醇及人工神经网络实验结果建模
DOI:
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发表时间:
2010
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通讯作者:
A. Sepehrianazar
中科院分区:
文献类型:
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作者:
A. Niaei;D. Salari;F. Aghazadeh;N. Çaylak;A. Sepehrianazar
The catalytic activity of transition metals (Cr,Mn,Fe) supported on the Pt/γ -Al2O3 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/γ -Al2O3 (3.88 wt.%Mn) at calcination temperature of 300°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/γ -Al2O3 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.