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Computational Screening of Metal–Organic Frameworks for Membrane-Based CO(2)/N(2)/H(2)O Separations: Best Materials for Flue Gas Separation
[Image: see text] It has become a significant challenge to select the best metal–organic frameworks (MOFs) for membrane-based gas separations because the number of synthesized MOFs is growing exceptionally fast. In this work, we used high-throughput computational screening to identify the top MOF me...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical
Society
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6077770/ https://www.ncbi.nlm.nih.gov/pubmed/30093931 http://dx.doi.org/10.1021/acs.jpcc.8b05416 |
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author | Daglar, Hilal Keskin, Seda |
author_facet | Daglar, Hilal Keskin, Seda |
author_sort | Daglar, Hilal |
collection | PubMed |
description | [Image: see text] It has become a significant challenge to select the best metal–organic frameworks (MOFs) for membrane-based gas separations because the number of synthesized MOFs is growing exceptionally fast. In this work, we used high-throughput computational screening to identify the top MOF membranes for flue gas separation. Grand canonical Monte Carlo and molecular dynamics simulations were performed to assess adsorption and diffusion properties of CO(2) and N(2) in 3806 different MOFs. Using these data, selectivities and permeabilities of MOF membranes were predicted and compared with those of conventional membranes, polymers, and zeolites. The best performing MOF membranes offering CO(2)/N(2) selectivity > 350 and CO(2) permeability > 10(6) Barrer were identified. Ternary CO(2)/N(2)/H(2)O mixture simulations were then performed for the top MOFs to unlock their potential under industrial operating conditions, and results showed that the presence of water decreases CO(2)/N(2) selectivity and CO(2) permeability of some MOF membranes. As a result of this stepwise screening procedure, the number of promising MOF membranes to be investigated for flue gas separation in future experimental studies was narrowed down from thousands to tens. We finally examined the structure–performance relations of MOFs to understand which properties lead to the greatest promise for flue gas separation and concluded that lanthanide-based MOFs with narrow pore openings (<4.5 Å), low porosities (<0.75), and low surface areas (<1000 m(2)/g) are the best materials for membrane-based CO(2)/N(2) separations. |
format | Online Article Text |
id | pubmed-6077770 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Chemical
Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-60777702018-08-07 Computational Screening of Metal–Organic Frameworks for Membrane-Based CO(2)/N(2)/H(2)O Separations: Best Materials for Flue Gas Separation Daglar, Hilal Keskin, Seda J Phys Chem C Nanomater Interfaces [Image: see text] It has become a significant challenge to select the best metal–organic frameworks (MOFs) for membrane-based gas separations because the number of synthesized MOFs is growing exceptionally fast. In this work, we used high-throughput computational screening to identify the top MOF membranes for flue gas separation. Grand canonical Monte Carlo and molecular dynamics simulations were performed to assess adsorption and diffusion properties of CO(2) and N(2) in 3806 different MOFs. Using these data, selectivities and permeabilities of MOF membranes were predicted and compared with those of conventional membranes, polymers, and zeolites. The best performing MOF membranes offering CO(2)/N(2) selectivity > 350 and CO(2) permeability > 10(6) Barrer were identified. Ternary CO(2)/N(2)/H(2)O mixture simulations were then performed for the top MOFs to unlock their potential under industrial operating conditions, and results showed that the presence of water decreases CO(2)/N(2) selectivity and CO(2) permeability of some MOF membranes. As a result of this stepwise screening procedure, the number of promising MOF membranes to be investigated for flue gas separation in future experimental studies was narrowed down from thousands to tens. We finally examined the structure–performance relations of MOFs to understand which properties lead to the greatest promise for flue gas separation and concluded that lanthanide-based MOFs with narrow pore openings (<4.5 Å), low porosities (<0.75), and low surface areas (<1000 m(2)/g) are the best materials for membrane-based CO(2)/N(2) separations. American Chemical Society 2018-07-03 2018-08-02 /pmc/articles/PMC6077770/ /pubmed/30093931 http://dx.doi.org/10.1021/acs.jpcc.8b05416 Text en Copyright © 2018 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Daglar, Hilal Keskin, Seda Computational Screening of Metal–Organic Frameworks for Membrane-Based CO(2)/N(2)/H(2)O Separations: Best Materials for Flue Gas Separation |
title | Computational Screening of Metal–Organic Frameworks
for Membrane-Based CO(2)/N(2)/H(2)O Separations:
Best Materials for Flue Gas Separation |
title_full | Computational Screening of Metal–Organic Frameworks
for Membrane-Based CO(2)/N(2)/H(2)O Separations:
Best Materials for Flue Gas Separation |
title_fullStr | Computational Screening of Metal–Organic Frameworks
for Membrane-Based CO(2)/N(2)/H(2)O Separations:
Best Materials for Flue Gas Separation |
title_full_unstemmed | Computational Screening of Metal–Organic Frameworks
for Membrane-Based CO(2)/N(2)/H(2)O Separations:
Best Materials for Flue Gas Separation |
title_short | Computational Screening of Metal–Organic Frameworks
for Membrane-Based CO(2)/N(2)/H(2)O Separations:
Best Materials for Flue Gas Separation |
title_sort | computational screening of metal–organic frameworks
for membrane-based co(2)/n(2)/h(2)o separations:
best materials for flue gas separation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6077770/ https://www.ncbi.nlm.nih.gov/pubmed/30093931 http://dx.doi.org/10.1021/acs.jpcc.8b05416 |
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