Publication: Computational simulations of metal–organic frameworks to enhance adsorption applications
dc.contributor.department | Department of Chemical and Biological Engineering | |
dc.contributor.kuauthor | Harman, Hilal Dağlar | |
dc.contributor.kuauthor | Gülbalkan, Hasan Can | |
dc.contributor.kuauthor | Aksu, Gökhan Önder | |
dc.contributor.kuauthor | Keskin, Seda | |
dc.contributor.other | Department of Chemical and Biological Engineering | |
dc.contributor.schoolcollegeinstitute | Graduate School of Sciences and Engineering | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.date.accessioned | 2024-12-29T09:36:08Z | |
dc.date.issued | 2024 | |
dc.description.abstract | Metal–organic frameworks (MOFs), renowned for their exceptional porosity and crystalline structure, stand at the forefront of gas adsorption and separation applications. Shortly after their discovery through experimental synthesis, computational simulations quickly become an important method in broadening the use of MOFs by offering deep insights into their structural, functional, and performance properties. This review specifically addresses the pivotal role of molecular simulations in enlarging the molecular understanding of MOFs and enhancing their applications, particularly for gas adsorption. After reviewing the historical development and implementation of molecular simulation methods in the field of MOFs, high-throughput computational screening (HTCS) studies used to unlock the potential of MOFs in CO2 capture, CH4 storage, H2 storage, and water harvesting are visited and recent advancements in these adsorption applications are highlighted. The transformative impact of integrating artificial intelligence with HTCS on the prediction of MOFs’ performance and directing the experimental efforts on promising materials is addressed. An outlook on current opportunities and challenges in the field to accelerate the adsorption applications of MOFs is finally provided. © 2024 The Author(s). Advanced Materials published by Wiley-VCH GmbH. | |
dc.description.indexedby | WoS | |
dc.description.indexedby | Scopus | |
dc.description.indexedby | PubMed | |
dc.description.openaccess | All Open Access | |
dc.description.openaccess | Hybrid Gold Open Access | |
dc.description.publisherscope | International | |
dc.description.sponsoredbyTubitakEu | EU | |
dc.description.sponsors | H.C.G. and G.O.A. contributed equally to this work. S.K. acknowledges funding by the European Union (ERC, STARLET, 101124002). Views and opinions expressed are, however, those of the authors only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. The authors express sincere gratitude to Goktug Ercakir and Pelin Sezgin for the fruitful discussions. | |
dc.identifier.doi | 10.1002/adma.202405532 | |
dc.identifier.eissn | 1521-4095 | |
dc.identifier.issn | 0935-9648 | |
dc.identifier.quartile | Q1 | |
dc.identifier.scopus | 2-s2.0-85199718307 | |
dc.identifier.uri | https://doi.org/10.1002/adma.202405532 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/21957 | |
dc.identifier.wos | 1284232100001 | |
dc.keywords | Gas adsorption | |
dc.keywords | Metal–organic framework | |
dc.keywords | Molecular simulation | |
dc.language | en | |
dc.publisher | John Wiley and Sons Inc | |
dc.source | Advanced Materials | |
dc.subject | Metal organic framework | |
dc.subject | Adsorption | |
dc.subject | Carbon Dioxide | |
dc.title | Computational simulations of metal–organic frameworks to enhance adsorption applications | |
dc.type | Review | |
dc.type.other | Early access | |
dspace.entity.type | Publication | |
local.contributor.kuauthor | Harman, Hilal Dağlar | |
local.contributor.kuauthor | Gülbalkan, Hasan Can | |
local.contributor.kuauthor | Aksu, Gökhan Önder | |
local.contributor.kuauthor | Keskin, Seda | |
relation.isOrgUnitOfPublication | c747a256-6e0c-4969-b1bf-3b9f2f674289 | |
relation.isOrgUnitOfPublication.latestForDiscovery | c747a256-6e0c-4969-b1bf-3b9f2f674289 |