Publication:
A new approach for predicting gas separation performances of MOF membranes

dc.contributor.departmentN/A
dc.contributor.departmentDepartment of Chemical and Biological Engineering
dc.contributor.kuauthorGürdal, Yeliz
dc.contributor.kuauthorKeskin, Seda
dc.contributor.kuprofileMaster Student
dc.contributor.kuprofileFaculty Member
dc.contributor.otherDepartment of Chemical and Biological Engineering
dc.contributor.schoolcollegeinstituteGraduate School of Sciences and Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.yokidN/A
dc.contributor.yokid40548
dc.date.accessioned2024-11-09T23:49:02Z
dc.date.issued2016
dc.description.abstractMetal organic framework (MOF) membranes are widely used for gas separations. Permeability and selectivity of MOF membranes can be accurately calculated using 'the detailed method' which computes transport diffusivities of gases in MOFs' pores. However, this method is computationally demanding therefore not suitable to screen large numbers of MOFs. Another approach is to use the approximate method' which uses self-diffusivities of gases to predict gas permeabilities of MOF membranes. The approximate method requires fewer amounts of time compared to the detailed method but significantly underestimates gas permeabilities since mixture correlation effects are ignored in this method. In this work, we first used computationally demanding detailed method to calculate permeabilities and selectivities of 8 different MOF membranes for Xe/Kr and Xe/Ar separations. We then compared these results with the predictions of the approximate method. After observing significant underestimation of the gas permeabilities by the approximate method, we proposed a new computational method to accurately predict gas separation properties of MOF membranes. This new method requires the same computational time and resources with the approximate method but makes much more accurate predictions for gas permeabilities. The new method that we proposed in this work will be very useful for large-scale screening of MOFs to identify the most promising membrane materials prior to extensive computational calculations and experimental efforts. (C) 2016 Elsevier B.V. All rights reserved.
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.volume519
dc.identifier.doi10.1016/j.memsci.2016.07.039
dc.identifier.eissn1873-3123
dc.identifier.issn0376-7388
dc.identifier.scopus2-s2.0-84979917835
dc.identifier.urihttp://dx.doi.org/10.1016/j.memsci.2016.07.039
dc.identifier.urihttps://hdl.handle.net/20.500.14288/14290
dc.identifier.wos382255000005
dc.keywordsMetal organic framework
dc.keywordsGas separation
dc.keywordsMembrane
dc.keywordsSelectivity
dc.keywordsPermeability metal-organic frameworks
dc.keywordsMolecular-dynamics simulations
dc.keywordsIrreversible-processes
dc.keywordsReciprocal relations
dc.keywordsBinary-mixtures
dc.keywordsSelf-diffusion
dc.keywordsForce-field
dc.keywordsN-alkanes
dc.keywordsPore-size
dc.keywordsFaujasite
dc.languageEnglish
dc.publisherElsevier Science Bv
dc.sourceJournal of Membrane Science
dc.subjectEngineering
dc.subjectChemical engineering
dc.subjectPolymer science
dc.titleA new approach for predicting gas separation performances of MOF membranes
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.authorid0000-0002-6245-891X
local.contributor.authorid0000-0001-5968-0336
local.contributor.kuauthorGürdal, Yeliz
local.contributor.kuauthorKeskin, Seda
relation.isOrgUnitOfPublicationc747a256-6e0c-4969-b1bf-3b9f2f674289
relation.isOrgUnitOfPublication.latestForDiscoveryc747a256-6e0c-4969-b1bf-3b9f2f674289

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