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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Main Authors: Remya R. Nair, Evgenia Protasova, Skule Strand, Torleiv Bilstad
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:Membranes
Subjects:
Online Access:http://www.mdpi.com/2077-0375/8/3/78
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spelling 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
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AT evgeniaprotasova implementationofspieglerkedemandsterichindranceporemodelsforanalyzingnanofiltrationmembraneperformanceforsmartwaterproduction
AT skulestrand implementationofspieglerkedemandsterichindranceporemodelsforanalyzingnanofiltrationmembraneperformanceforsmartwaterproduction
AT torleivbilstad implementationofspieglerkedemandsterichindranceporemodelsforanalyzingnanofiltrationmembraneperformanceforsmartwaterproduction
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