Effects of Support Type on Stability of Nickel Catalysts in a Fixed-bed Reactor: Deactivation Modeling Using Hybrid ANN/GPLE Approaches
نویسندگان
1 Department of Chemical Engineering, Faculty of Engineering, University of Sistan and Baluchestan, P.O.Box 98164-161, Zahedan, Iran
2 Department of Chemistry, Faculty of Sciences, University of Sistan and Baluchestan,Zahedan, Iran
3 Department of chemical engineering, Shahid Nikbakht Faculty of Engineering, University of Sistan and Baluchestan, Zahedan, Iran
4 Chemical Engineering, Shahid Nikbakht faculty of engineering, University of Sistan and Baluchestan, Zahedan, Iran
doi
10.22036/pcr.2024.470263.2558چکیده
This paper used the neural network method to determine an appropriate deactivation model and the steady state activity. Using the wet impregnation method, the Nickel catalysts were prepared on the α-Al2O3, γ-Al2O3, SiO2, and TiO2 supports. The performances of catalysts were evaluated in a fixed bed reactor at constant conditions as follows: P = 20 bar, T = 583 K, and H2/CO = 3. For the 20%Ni/TiO2 catalyst, the second-order Generalized Power-Law Equation (GPLE) model and the other catalysts, the first-order GPLE model can predict the catalyst deactivation behavior well. A comparison of model parameters showed that the use of TiO2 as support increased the long-term stability of nickel catalyst in the fixed bed reactor. XRD analysis demonstrated crystal growth on the supports and sintering deactivation mechanism.
