Gas Permeation Model of Mixed-Matrix Membranes with Embedded Impermeable Cuboid Nanoparticles

In the packaging industry, the barrier property of packaging materials is of paramount importance. The enhancement of barrier properties of materials can be achieved by adding impermeable nanoparticles into thin polymeric films, known as mixed-matrix membranes (MMMs). Three-dimensional numerical sim...

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Main Authors: Haoyu Wu, Maryam Zamanian, Boguslaw Kruczek, Jules Thibault
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Membranes
Subjects:
Online Access:https://www.mdpi.com/2077-0375/10/12/422
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author Haoyu Wu
Maryam Zamanian
Boguslaw Kruczek
Jules Thibault
author_facet Haoyu Wu
Maryam Zamanian
Boguslaw Kruczek
Jules Thibault
author_sort Haoyu Wu
collection DOAJ
description In the packaging industry, the barrier property of packaging materials is of paramount importance. The enhancement of barrier properties of materials can be achieved by adding impermeable nanoparticles into thin polymeric films, known as mixed-matrix membranes (MMMs). Three-dimensional numerical simulations were performed to study the barrier property of these MMMs and to estimate the effective membrane gas permeability. Results show that horizontally-aligned thin cuboid nanoparticles offer far superior barrier properties than spherical nanoparticles for an identical solid volume fraction. Maxwell’s model predicts very well the relative permeability of spherical and cubic nanoparticles over a wide range of the solid volume fraction. However, Maxwell’s model shows an increasingly poor prediction of the relative permeability of MMM as the aspect ratio of cuboid nanoparticles tends to zero or infinity. An artificial neural network (ANN) model was developed successfully to predict the relative permeability of MMMs as a function of the relative thickness and the relative projected area of the embedded nanoparticles. However, since an ANN model does not provide an explicit form of the relation of the relative permeability with the physical characteristics of the MMM, a new model based on multivariable regression analysis is introduced to represent the relative permeability in a MMM with impermeable cuboid nanoparticles. The new model possesses a simple explicit form and can predict, very well, the relative permeability over an extensive range of the solid volume fraction and aspect ratio, compared with many existing models.
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spelling doaj.art-2b97d3df3f2e42a391811791288a4cde2023-11-21T00:52:16ZengMDPI AGMembranes2077-03752020-12-01101242210.3390/membranes10120422Gas Permeation Model of Mixed-Matrix Membranes with Embedded Impermeable Cuboid NanoparticlesHaoyu Wu0Maryam Zamanian1Boguslaw Kruczek2Jules Thibault3Department of Chemical and Biological Engineering, University of Ottawa, 161 Louis Pasteur St., Ottawa, ON K1N 6N5, CanadaDepartment of Biosystems Engineering, Ferdowsi University of Mashhad, Azadi Square, Mashhad, Razavi Khorasan Province 9177948974, IranDepartment of Chemical and Biological Engineering, University of Ottawa, 161 Louis Pasteur St., Ottawa, ON K1N 6N5, CanadaDepartment of Chemical and Biological Engineering, University of Ottawa, 161 Louis Pasteur St., Ottawa, ON K1N 6N5, CanadaIn the packaging industry, the barrier property of packaging materials is of paramount importance. The enhancement of barrier properties of materials can be achieved by adding impermeable nanoparticles into thin polymeric films, known as mixed-matrix membranes (MMMs). Three-dimensional numerical simulations were performed to study the barrier property of these MMMs and to estimate the effective membrane gas permeability. Results show that horizontally-aligned thin cuboid nanoparticles offer far superior barrier properties than spherical nanoparticles for an identical solid volume fraction. Maxwell’s model predicts very well the relative permeability of spherical and cubic nanoparticles over a wide range of the solid volume fraction. However, Maxwell’s model shows an increasingly poor prediction of the relative permeability of MMM as the aspect ratio of cuboid nanoparticles tends to zero or infinity. An artificial neural network (ANN) model was developed successfully to predict the relative permeability of MMMs as a function of the relative thickness and the relative projected area of the embedded nanoparticles. However, since an ANN model does not provide an explicit form of the relation of the relative permeability with the physical characteristics of the MMM, a new model based on multivariable regression analysis is introduced to represent the relative permeability in a MMM with impermeable cuboid nanoparticles. The new model possesses a simple explicit form and can predict, very well, the relative permeability over an extensive range of the solid volume fraction and aspect ratio, compared with many existing models.https://www.mdpi.com/2077-0375/10/12/422mixed-matrix membranesimpermeable nanoparticlesthree-dimensional modellingrelative permeabilitypredictive permeability model
spellingShingle Haoyu Wu
Maryam Zamanian
Boguslaw Kruczek
Jules Thibault
Gas Permeation Model of Mixed-Matrix Membranes with Embedded Impermeable Cuboid Nanoparticles
Membranes
mixed-matrix membranes
impermeable nanoparticles
three-dimensional modelling
relative permeability
predictive permeability model
title Gas Permeation Model of Mixed-Matrix Membranes with Embedded Impermeable Cuboid Nanoparticles
title_full Gas Permeation Model of Mixed-Matrix Membranes with Embedded Impermeable Cuboid Nanoparticles
title_fullStr Gas Permeation Model of Mixed-Matrix Membranes with Embedded Impermeable Cuboid Nanoparticles
title_full_unstemmed Gas Permeation Model of Mixed-Matrix Membranes with Embedded Impermeable Cuboid Nanoparticles
title_short Gas Permeation Model of Mixed-Matrix Membranes with Embedded Impermeable Cuboid Nanoparticles
title_sort gas permeation model of mixed matrix membranes with embedded impermeable cuboid nanoparticles
topic mixed-matrix membranes
impermeable nanoparticles
three-dimensional modelling
relative permeability
predictive permeability model
url https://www.mdpi.com/2077-0375/10/12/422
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AT boguslawkruczek gaspermeationmodelofmixedmatrixmembraneswithembeddedimpermeablecuboidnanoparticles
AT julesthibault gaspermeationmodelofmixedmatrixmembraneswithembeddedimpermeablecuboidnanoparticles