Leveraging molecular simulations and machine learning to assess CO2, O2, and N2 adsorption and separation performances of diverse MOF databases

We integrated molecular simulations and machine learning (ML) to comprehensively explore the gas adsorption and separation performances of both synthesized and hypothetical metal-organic frameworks (MOFs) available in five different MOF databases. Following the generation of CO2, O2, and N2 adsorpti...

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Autori principali:	Hasan Can Gulbalkan, Seda Keskin
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2026-03-01
Serie:	Chemical Engineering Journal Advances
Soggetti:	Metal-organic framework (MOF) Gas adsorption Molecular simulations Machine learning (ML)
Accesso online:	http://www.sciencedirect.com/science/article/pii/S2666821125002789
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