eprintid: 11278
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/12/78
datestamp: 2023-11-10 03:25:47
lastmod: 2023-11-10 03:25:47
status_changed: 2023-11-10 01:14:53
type: article
metadata_visibility: show
creators_name: Ullah, S.
creators_name: Assiri, M.A.
creators_name: Al-Sehemi, A.G.
creators_name: Bustam, M.A.
creators_name: Abdul Mannan, H.
creators_name: Abdulkareem, F.A.
creators_name: Irfan, A.
creators_name: Saqib, S.
title: High-temperature CO2 removal from CH4 using silica membrane: experimental and neural network modeling
ispublished: pub
keywords: 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
note: cited By 24
abstract: 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.
date: 2019
publisher: John Wiley and Sons Inc
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071302455&doi=10.1002%2fghg.1916&partnerID=40&md5=0c6a91b3680d69735790f6974b87e62a
id_number: 10.1002/ghg.1916
full_text_status: none
publication: Greenhouse Gases: Science and Technology
volume: 9
number: 5
pagerange: 1010-1026
refereed: TRUE
issn: 21523878
citation:   Ullah, S. and Assiri, M.A. and Al-Sehemi, A.G. and Bustam, M.A. and Abdul Mannan, H. and Abdulkareem, F.A. and Irfan, A. and Saqib, S.  (2019) High-temperature CO2 removal from CH4 using silica membrane: experimental and neural network modeling.  Greenhouse Gases: Science and Technology, 9 (5).  pp. 1010-1026.  ISSN 21523878