Implementation of Spiegler–Kedem and Steric Hindrance Pore Models for Analyzing Nanofiltration Membrane Performance for Smart Water Production
A predictive model correlating the parameters in the mass transfer-based model Spiegler–Kedem to the pure water permeability is presented in this research, which helps to select porous polyamide membranes for enhanced oil recovery (EOR) applications. Using the experimentally obtained value...
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doaj-7ca0e92b80f1455abcd4b6b2cc19f5e42020-11-24T21:04:42ZengMDPI AGMembranes2077-03752018-09-01837810.3390/membranes8030078membranes8030078Implementation of Spiegler–Kedem and Steric Hindrance Pore Models for Analyzing Nanofiltration Membrane Performance for Smart Water ProductionRemya R. Nair0Evgenia Protasova1Skule Strand2Torleiv Bilstad3Department of Chemistry, Bioscience and Environmental Engineering, University of Stavanger, Kjell Arholmsgate 41, 4036 Stavanger, NorwayDepartment of Chemistry, Bioscience and Environmental Engineering, University of Stavanger, Kjell Arholmsgate 41, 4036 Stavanger, NorwayDepartment of Energy and Petroleum Engineering, University of Stavanger, Kjell Arholmsgate 41, 4036 Stavanger, NorwayDepartment of Chemistry, Bioscience and Environmental Engineering, University of Stavanger, Kjell Arholmsgate 41, 4036 Stavanger, NorwayA predictive model correlating the parameters in the mass transfer-based model Spiegler–Kedem to the pure water permeability is presented in this research, which helps to select porous polyamide membranes for enhanced oil recovery (EOR) applications. Using the experimentally obtained values of flux and rejection, the reflection coefficient σ and solute permeability Ps have been estimated as the mass transfer-based model parameters for individual ions in seawater. The reflection coefficient and solute permeability determined were correlated with the pure water permeability of a membrane, which is related to the structural parameters of a membrane. The novelty of this research is the development of a model that consolidates the various complex mechanisms in the mass transfer of ions through the membrane to an empirical correlation for a given feed concentration and membrane type. These correlations were later used to predict ion rejections of any polyamide membrane with a known pure water permeability and flux with seawater as a feed that aids in the selection of suitable nanofiltration (NF) for smart water production.http://www.mdpi.com/2077-0375/8/3/78nanofiltrationSpiegler–Kedem modelsteric hindrance pore modelion rejectionreflection coefficientsolute permeabilitypure water permeability |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Remya R. Nair Evgenia Protasova Skule Strand Torleiv Bilstad |
spellingShingle |
Remya R. Nair Evgenia Protasova Skule Strand Torleiv Bilstad Implementation of Spiegler–Kedem and Steric Hindrance Pore Models for Analyzing Nanofiltration Membrane Performance for Smart Water Production Membranes nanofiltration Spiegler–Kedem model steric hindrance pore model ion rejection reflection coefficient solute permeability pure water permeability |
author_facet |
Remya R. Nair Evgenia Protasova Skule Strand Torleiv Bilstad |
author_sort |
Remya R. Nair |
title |
Implementation of Spiegler–Kedem and Steric Hindrance Pore Models for Analyzing Nanofiltration Membrane Performance for Smart Water Production |
title_short |
Implementation of Spiegler–Kedem and Steric Hindrance Pore Models for Analyzing Nanofiltration Membrane Performance for Smart Water Production |
title_full |
Implementation of Spiegler–Kedem and Steric Hindrance Pore Models for Analyzing Nanofiltration Membrane Performance for Smart Water Production |
title_fullStr |
Implementation of Spiegler–Kedem and Steric Hindrance Pore Models for Analyzing Nanofiltration Membrane Performance for Smart Water Production |
title_full_unstemmed |
Implementation of Spiegler–Kedem and Steric Hindrance Pore Models for Analyzing Nanofiltration Membrane Performance for Smart Water Production |
title_sort |
implementation of spiegler–kedem and steric hindrance pore models for analyzing nanofiltration membrane performance for smart water production |
publisher |
MDPI AG |
series |
Membranes |
issn |
2077-0375 |
publishDate |
2018-09-01 |
description |
A predictive model correlating the parameters in the mass transfer-based model Spiegler–Kedem to the pure water permeability is presented in this research, which helps to select porous polyamide membranes for enhanced oil recovery (EOR) applications. Using the experimentally obtained values of flux and rejection, the reflection coefficient σ and solute permeability Ps have been estimated as the mass transfer-based model parameters for individual ions in seawater. The reflection coefficient and solute permeability determined were correlated with the pure water permeability of a membrane, which is related to the structural parameters of a membrane. The novelty of this research is the development of a model that consolidates the various complex mechanisms in the mass transfer of ions through the membrane to an empirical correlation for a given feed concentration and membrane type. These correlations were later used to predict ion rejections of any polyamide membrane with a known pure water permeability and flux with seawater as a feed that aids in the selection of suitable nanofiltration (NF) for smart water production. |
topic |
nanofiltration Spiegler–Kedem model steric hindrance pore model ion rejection reflection coefficient solute permeability pure water permeability |
url |
http://www.mdpi.com/2077-0375/8/3/78 |
work_keys_str_mv |
AT remyarnair implementationofspieglerkedemandsterichindranceporemodelsforanalyzingnanofiltrationmembraneperformanceforsmartwaterproduction AT evgeniaprotasova implementationofspieglerkedemandsterichindranceporemodelsforanalyzingnanofiltrationmembraneperformanceforsmartwaterproduction AT skulestrand implementationofspieglerkedemandsterichindranceporemodelsforanalyzingnanofiltrationmembraneperformanceforsmartwaterproduction AT torleivbilstad implementationofspieglerkedemandsterichindranceporemodelsforanalyzingnanofiltrationmembraneperformanceforsmartwaterproduction |
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