%P 1010-1026
%T High-temperature CO2 removal from CH4 using silica membrane: experimental and neural network modeling
%I John Wiley and Sons Inc
%A S. Ullah
%A M.A. Assiri
%A A.G. Al-Sehemi
%A M.A. Bustam
%A H. Abdul Mannan
%A F.A. Abdulkareem
%A A. Irfan
%A S. Saqib
%V 9
%O cited By 24
%L scholars11278
%J Greenhouse Gases: Science and Technology
%D 2019
%R 10.1002/ghg.1916
%N 5
%K Alumina; Aluminum oxide; Backpropagation; Carbon dioxide; Chemical industry; Coatings; Gas permeable membranes; Inlet flow; Silica; Sols, Artificial neural network modeling; Dip coating; Feed-forward back-propagation neural networks; Gel method; Permselectivities; Silica membrane, Neural networks, artificial neural network; back propagation; carbon dioxide; experimental study; high temperature; membrane; methane; separation
%X Inorganic membranes can operate under harsh conditions. However, successful synthesis of inorganic membranes is still challenging, and its performance depends on many factors. This work reports the effect of dip-coating duration, inlet pressure, and inlet flow rate on the flux, permeability, and selectivity of silica membranes. A silica membrane was prepared by the deposition of silica sol onto porous alumina support. The permeability test was conducted at 100 °C using a single gas of CO2 and CH4. The highest flux was observed at the maximum inlet pressure and inlet flow rate for the membrane prepared at the minimum dip-coating duration. The neural network modeling of the membrane predicted permeabilities showed a considerably high validity regression (R � 0.99) of the predicted data linked to the experimental sets. The separation factor (α) was the highest at the maximum dip-coating duration. The synthesized silica membrane has potential for CO2/CH4 separation under harsh operating conditions. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.