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Publication:
Unveiling the SF6/N2 and CH4/H2 separation potential of MOFs via integrated molecular simulations and machine learning

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dc.contributor.advisorKeskin, Seda
dc.contributor.kuauthorSezgin, Pelin
dc.contributor.programChemical and Bological Engineering
dc.contributor.refereeFındıkçı, İlknur Eruçar
dc.contributor.refereeÖzkaya, Özlem Keskin
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.coverage.spatialİstanbul
dc.date.accessioned2026-09-10T10:13:17Z
dc.date.issued2025
dc.description.fulltextYes
dc.format.extentxv, 103 leaves :; illustrations ;; 30 cm.
dc.identifier.embargoNo
dc.identifier.endpage118
dc.identifier.filenameinventorynoT_2025_121_GSSE
dc.identifier.urihttps://hdl.handle.net/20.500.14288/35266
dc.keywordsMetal-organic frameworks (MOFs), Gas separation, SF6/N2 separation, Molecular simulations, Machine learning
dc.keywordsAnahtar kelimeler: Metal-organik kafesler (MOF’lar), Gaz ayrıştırma, SF6/N2 ayrıştırması, CH4/H2 ayrıştırması, Moleküler simülasyonlar, Makine öğrenmesi.;
dc.languageeng
dc.publisherKoç University
dc.relation.collectionKoç University Theses & Dissertations Collection
dc.rightsrestrictedAccess
dc.rights.copyrightsnote© All Rights Reserved. Accessible to Koç University Affiliated Users Only!
dc.subjectGases, Separation
dc.subjectMetal organic frameworks (MOF)
dc.titleUnveiling the SF6/N2 and CH4/H2 separation potential of MOFs via integrated molecular simulations and machine learning
dc.title.alternativeMOF'ların SF6/N2 ve CH4/H2 ayrım potansiyelinin entegre moleküler simülasyonlar ve makine öğrenmesi ile ortaya konması
dc.typeThesis
dspace.entity.typePublication
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relation.isAdvisorOfThesis.latestForDiscovery8cf1edd5-df6e-424d-82cd-98cb2a079858
relation.isParentOrgUnitOfPublication434c9663-2b11-4e66-9399-c863e2ebae43
relation.isParentOrgUnitOfPublication.latestForDiscovery434c9663-2b11-4e66-9399-c863e2ebae43

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