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    Outstanding methane gravimetric working capacity of computationally designed rhr-MOFs

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    paper.pdf
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    Description:
    Accepted Manuscript
    Embargo End Date:
    2021-07-29
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    Type
    Article
    Authors
    Suetin, Mikhail cc
    Peskov, Maxim cc
    Schwingenschlögl, Udo cc
    KAUST Department
    Advanced Membranes and Porous Materials Research Center
    Computational Physics and Materials Science (CPMS)
    Material Science and Engineering Program
    Physical Science and Engineering (PSE) Division
    Date
    2019-07-29
    Online Publication Date
    2019-07-29
    Print Publication Date
    2019-12
    Embargo End Date
    2021-07-29
    Permanent link to this record
    http://hdl.handle.net/10754/656825
    
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    Abstract
    A multi-scale approach is employed to design metal-organic frameworks (MOFs). The methane sorption properties are studied by grand canonical Monte Carlo simulations to reveal the structure-property relationship with respect to the methane total uptake and working capacity at different temperatures and pressures. We identify rhr-MOFs with outstanding gravimetric working capacity. For example, the BBB MOF (largest studied pore size) achieves a value of 60.7 wt% at 298 K and 5–65 bar.
    Citation
    Suyetin, M., Peskov, M. V., & Schwingenschlögl, U. (2019). Outstanding methane gravimetric working capacity of computationally designed rhr-MOFs. Microporous and Mesoporous Materials, 290, 109621. doi:10.1016/j.micromeso.2019.109621
    Sponsors
    The research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST).
    Publisher
    Elsevier BV
    Journal
    Microporous and Mesoporous Materials
    DOI
    10.1016/j.micromeso.2019.109621
    Additional Links
    https://linkinghub.elsevier.com/retrieve/pii/S1387181119304780
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.micromeso.2019.109621
    Scopus Count
    Collections
    Articles; Advanced Membranes and Porous Materials Research Center; Physical Science and Engineering (PSE) Division; Material Science and Engineering Program; Computational Physics and Materials Science (CPMS)

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