Literature DB >> 20540140

New microporous materials for acetylene storage and C(2)H(2)/CO(2) separation: insights from molecular simulations.

Michael Fischer1, Frank Hoffmann, Michael Fröba.   

Abstract

Force-field based grand-canonical Monte Carlo simulations are used to investigate the acetylene and carbon dioxide uptake capacity, as well as the C(2)H(2)/CO(2) adsorption selectivity of three novel microporous materials: Magnesium formate, Cu(3)(btc)(2), and cucurbit[6]uril. Because no comparable computational studies of acetylene adsorption have been reported so far, the study focuses on systems for which experimental data are available to permit a thorough validation of the simulation results. The results for magnesium formate are in excellent agreement with experiment. The simulation predicts a high selectivity for acetylene over CO(2), which can be understood from a detailed analysis of the structural features that determine the affinity of Mg-formate towards C(2)H(2). For Cu(3)(btc)(2), preliminary calculations reveal the necessity to include the interaction of the sorbate molecules with the unsaturated metal sites, which is done by means of a parameter adjustment based on ab-initio calculations. In spite of the high C(2)H(2) storage capacity, the C(2)H(2)/CO(2) selectivity of this material is very modest. The simulation results for the porous organic crystal cucurbit[6]uril show that the adsorption characteristics that have been observed experimentally, particularly the very high isosteric heat of adsorption, cannot be understood when an ideal structure is assumed. It is postulated that structural imperfections play a key role in determining the C(2)H(2) adsorption behavior of this material, and this proposition is supported by additional calculations.

Entities:  

Year:  2010        PMID: 20540140     DOI: 10.1002/cphc.201000126

Source DB:  PubMed          Journal:  Chemphyschem        ISSN: 1439-4235            Impact factor:   3.102


  8 in total

1.  The role of molecular modelling and simulation in the discovery and deployment of metal-organic frameworks for gas storage and separation.

Authors:  Arni Sturluson; Melanie T Huynh; Alec R Kaija; Caleb Laird; Sunghyun Yoon; Feier Hou; Zhenxing Feng; Christopher E Wilmer; Yamil J Colón; Yongchul G Chung; Daniel W Siderius; Cory M Simon
Journal:  Mol Simul       Date:  2019       Impact factor: 2.178

2.  Gas detection by structural variations of fluorescent guest molecules in a flexible porous coordination polymer.

Authors:  Nobuhiro Yanai; Koji Kitayama; Yuh Hijikata; Hiroshi Sato; Ryotaro Matsuda; Yoshiki Kubota; Masaki Takata; Motohiro Mizuno; Takashi Uemura; Susumu Kitagawa
Journal:  Nat Mater       Date:  2011-10       Impact factor: 43.841

3.  A porous metal-organic framework with ultrahigh acetylene uptake capacity under ambient conditions.

Authors:  Jiandong Pang; Feilong Jiang; Mingyan Wu; Caiping Liu; Kongzhao Su; Weigang Lu; Daqiang Yuan; Maochun Hong
Journal:  Nat Commun       Date:  2015-06-30       Impact factor: 14.919

4.  Computational Screening of MOFs for Acetylene Separation.

Authors:  Ayda Nemati Vesali Azar; Seda Keskin
Journal:  Front Chem       Date:  2018-02-27       Impact factor: 5.221

Review 5.  Metrics for Evaluation and Screening of Metal-Organic Frameworks for Applications in Mixture Separations.

Authors:  Rajamani Krishna
Journal:  ACS Omega       Date:  2020-07-10

6.  Fine-Tuning the Pore Environment of the Microporous Cu-MOF for High Propylene Storage and Efficient Separation of Light Hydrocarbons.

Authors:  Weidong Fan; Xia Wang; Xiurong Zhang; Xiuping Liu; Yutong Wang; Zixi Kang; Fangna Dai; Ben Xu; Rongming Wang; Daofeng Sun
Journal:  ACS Cent Sci       Date:  2019-06-24       Impact factor: 14.553

7.  Computational Screening of Metal-Organic Frameworks for Ethylene Purification from Ethane/Ethylene/Acetylene Mixture.

Authors:  Yageng Zhou; Xiang Zhang; Teng Zhou; Kai Sundmacher
Journal:  Nanomaterials (Basel)       Date:  2022-03-04       Impact factor: 5.076

8.  Accelerating the Selection of Covalent Organic Frameworks with Automated Machine Learning.

Authors:  Peisong Yang; Huan Zhang; Xin Lai; Kunfeng Wang; Qingyuan Yang; Duli Yu
Journal:  ACS Omega       Date:  2021-06-25
  8 in total

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