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A. Hafizi,A. AHMADPOUR,M. Koolivand-Salooki,M.M. Heravi,F.F. Bamoharram 한국공업화학회 2013 Journal of Industrial and Engineering Chemistry Vol.19 No.6
Design of experiments (DOE) and artificial neural networks (ANNs) were successfully applied for studying the operating parameters of benzene alkylation with 1-decene over H14[NaP5W30O110]/SiO2catalyst. In this reaction catalyst loading, catalyst weight percent and benzene to 1-decene molar ratio (Bz/C10) were chosen as independent variables in experimental design. Prediction of 1-decene conversion and 2-phenyldecane selectivity was performed applying response surface method (RSM) and ANN models. Final selected multi-layer (3-6-2-2) ANN model resulted a coefficient of determination (R2)of 0.95 for 1-decene conversion and 0.99 for 2-phenyldecane selectivity, while the R2 of RSM was 0.93and 0.92 for these two parameters.
F. F. BAMOHARRAM,A. AHMADPOUR,M. M. HERAVI 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2011 NANO Vol.6 No.4
Multiwalled carbon nanotubes (MWCNTs) were synthesized by catalytic chemical vapor deposition method using Fe/Co catalyst over CaCO_3 support and acetylene gas as a carbon precursor in the temperature range of 650–800°C, and were modified with Preyssler anion nanostructures via impregnation method. The existence of nanoheteropolyacid [NaP_5W_(30)O_(110)]^(14) inside the MWCNTs was confirmed by infrared spectroscopy and transmission electron microscopy.