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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.advisorid0000-0001-5968-0336
dc.contributor.authorHarman, Hilal Dağlar
dc.contributor.instituteKoç University Graduate School of Sciences and Engineering
dc.contributor.programChemical and Biological Engineering
dc.contributor.yokid40548
dc.date.accessioned2024-11-09T22:02:50Z
dc.date.issued2024
dc.descriptionxix, 236 leaves : illustrations ; 30 cm.
dc.identifier.urihttps://hdl.handle.net/20.500.14288/4575
dc.languageEnglish
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.thesis.degreeDoctoral Degree
dc.thesis.grantorİstanbul
dc.titleCombining molecular simulations and machine learning to unlock gas separation performances of MOFs and MOF-based composites
dc.typeDissertation
dspace.entity.typePublication
relation.isAdvisorOfThesis8cf1edd5-df6e-424d-82cd-98cb2a079858
relation.isAdvisorOfThesis.latestForDiscovery8cf1edd5-df6e-424d-82cd-98cb2a079858

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