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Combining molecular simulations and machine learning to unlock gas separation performances of MOFs and MOF-based composites

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dc.contributor.advisorKeskin, Seda
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorHarman, Hilal Dağlar
dc.contributor.programChemical and Biological Engineering
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.coverage.spatialİstanbul
dc.date.accessioned2024-11-09T22:02:50Z
dc.date.issued2024
dc.format.extentxix, 236 leaves : illustrations ; 30 cm.
dc.identifier.urihttps://hdl.handle.net/20.500.14288/4575
dc.language.isoeng
dc.publisherKoç University
dc.relation.collectionKU Theses and Dissertations
dc.rightsrestrictedAccess
dc.rights.copyrightsnote© All Rights Reserved. Accessible to Koç University Affiliated Users Only!
dc.subjectPorous materials
dc.subjectGases, Separation
dc.subjectComposite materials
dc.titleCombining molecular simulations and machine learning to unlock gas separation performances of MOFs and MOF-based composites
dc.typeDissertation
dspace.entity.typePublication
local.contributor.kuauthorHarman, Hilal Dağlar
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