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Monte Carlo Simulations for the Estimation of the Effective Permeability of Mixed-Matrix Membranes
Recent years have seen the explosive development of mixed-matrix membranes (MMMs) for a myriad of applications. In gas separation, it is desired to concurrently enhance the permeability, selectivity and physicochemical properties of the membrane. To help achieving these objectives, experimental char...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9694028/ https://www.ncbi.nlm.nih.gov/pubmed/36363607 http://dx.doi.org/10.3390/membranes12111053 |
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author | Cao, Zheng Kruczek, Boguslaw Thibault, Jules |
author_facet | Cao, Zheng Kruczek, Boguslaw Thibault, Jules |
author_sort | Cao, Zheng |
collection | PubMed |
description | Recent years have seen the explosive development of mixed-matrix membranes (MMMs) for a myriad of applications. In gas separation, it is desired to concurrently enhance the permeability, selectivity and physicochemical properties of the membrane. To help achieving these objectives, experimental characterization and predictive models can be used synergistically. In this investigation, a Monte Carlo (MC) algorithm is proposed to rapidly and accurately estimate the relative permeability of ideal MMMs over a wide range of conditions. The difference in diffusivity coefficients between the polymer matrix and the filler particle is used to adjust the random progression of the migrating species inside each phase. The solubility coefficients of both phases at the polymer–filler interface are used to control the migration of molecules from one phase to the other in a way to achieve progressively phase equilibrium at the interface. Results for various MMMs were compared with the results obtained with the finite difference method under identical conditions, where the results from the finite difference method are used in this investigation as the benchmark method to test the accuracy of the Monte Carlo algorithm. Results were found to be very accurate (in general, <1% error) over a wide range of polymer and filler characteristics. The MC algorithm is simple and swift to implement and provides an accurate estimation of the relative permeability of ideal MMMs. The MC method can easily be extended to investigate more readily non-ideal MMMs with particle agglomeration, interfacial void, polymer-chain rigidification and/or pore blockage, and MMMs with any filler geometry. |
format | Online Article Text |
id | pubmed-9694028 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96940282022-11-26 Monte Carlo Simulations for the Estimation of the Effective Permeability of Mixed-Matrix Membranes Cao, Zheng Kruczek, Boguslaw Thibault, Jules Membranes (Basel) Article Recent years have seen the explosive development of mixed-matrix membranes (MMMs) for a myriad of applications. In gas separation, it is desired to concurrently enhance the permeability, selectivity and physicochemical properties of the membrane. To help achieving these objectives, experimental characterization and predictive models can be used synergistically. In this investigation, a Monte Carlo (MC) algorithm is proposed to rapidly and accurately estimate the relative permeability of ideal MMMs over a wide range of conditions. The difference in diffusivity coefficients between the polymer matrix and the filler particle is used to adjust the random progression of the migrating species inside each phase. The solubility coefficients of both phases at the polymer–filler interface are used to control the migration of molecules from one phase to the other in a way to achieve progressively phase equilibrium at the interface. Results for various MMMs were compared with the results obtained with the finite difference method under identical conditions, where the results from the finite difference method are used in this investigation as the benchmark method to test the accuracy of the Monte Carlo algorithm. Results were found to be very accurate (in general, <1% error) over a wide range of polymer and filler characteristics. The MC algorithm is simple and swift to implement and provides an accurate estimation of the relative permeability of ideal MMMs. The MC method can easily be extended to investigate more readily non-ideal MMMs with particle agglomeration, interfacial void, polymer-chain rigidification and/or pore blockage, and MMMs with any filler geometry. MDPI 2022-10-27 /pmc/articles/PMC9694028/ /pubmed/36363607 http://dx.doi.org/10.3390/membranes12111053 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Cao, Zheng Kruczek, Boguslaw Thibault, Jules Monte Carlo Simulations for the Estimation of the Effective Permeability of Mixed-Matrix Membranes |
title | Monte Carlo Simulations for the Estimation of the Effective Permeability of Mixed-Matrix Membranes |
title_full | Monte Carlo Simulations for the Estimation of the Effective Permeability of Mixed-Matrix Membranes |
title_fullStr | Monte Carlo Simulations for the Estimation of the Effective Permeability of Mixed-Matrix Membranes |
title_full_unstemmed | Monte Carlo Simulations for the Estimation of the Effective Permeability of Mixed-Matrix Membranes |
title_short | Monte Carlo Simulations for the Estimation of the Effective Permeability of Mixed-Matrix Membranes |
title_sort | monte carlo simulations for the estimation of the effective permeability of mixed-matrix membranes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9694028/ https://www.ncbi.nlm.nih.gov/pubmed/36363607 http://dx.doi.org/10.3390/membranes12111053 |
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