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首页> 外文期刊>ACS applied materials & interfaces >Effects of Intrinsic Flexibility on Adsorption Properties of Metal-Organic Frameworks at Dilute and Nondilute Loadings
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Effects of Intrinsic Flexibility on Adsorption Properties of Metal-Organic Frameworks at Dilute and Nondilute Loadings

机译：内在柔韧性对稀释和抗冲突载体金属 - 有机骨架吸附性能的影响

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摘要

Molecular simulation of adsorption in nanoporous materials has become a valuable complement to experimental studies of these materials. In almost all cases, these simulations treat the adsorbing material as rigid. We use molecular simulations to examine the validity of this approximation for the adsorption in metal-organic frameworks (MOFs) that have framework flexibility without change in their unit cells because of thermal vibrations. All nanoporous materials are subject to this kind of framework flexibility. We examine the adsorption of nine molecules (CO2, CH4, ethane, ethene, propane, propene, butane, Xe, and Kr) and four molecular mixtures (CO2/CH4, ethane/ethene, propane/propene/butane, and Xe/Kr) in 100 MOFs at dilute and nondilute adsorption conditions. Our results show that single-component adsorption uptakes at nondilute conditions are only weakly affected by framework flexibility, but adsorption selectivities at both dilute and nondilute conditions can be significantly affected by flexibility. The most dramatic impacts of framework flexibility occur for adsorption uptake in the limit of dilute adsorption. These results suggest that the importance of including framework flexibility when attempting to make quantitative predictions of adsorption selectivity in MOFs and similar materials may have been underestimated in the past.
机译：纳米多孔材料中吸附的分子模拟已成为对这些材料的实验研究的有价值的补充。在几乎所有情况下，这些模拟将吸附材料视为刚性。我们使用分子模拟来检查金属有机框架（MOF）中吸附的这种近似的有效性，由于热振动而没有改变其单位细胞的框架灵活性。所有纳米多孔材料都受此种框架灵活性。我们检查九分子（CO2，CH4，乙烷，乙烯，丙烷，丙烯，丁烷，XE和KR）的吸附）和四种分子混合物（CO 2 / CH 4，乙烷/乙烯，丙烯/丙烯/丁烷，以及XE / KR ）在100 mof时，在稀释和裸菌吸附条件下。我们的研究结果表明，非统计条件下的单组分吸附摄取仅受框架灵活性的弱影响，但稀释和非统计条件下的吸附选择性可能受到灵活性的显着影响。骨架灵活性最大的影响在稀释吸附极限下发生吸附吸收。这些结果表明，过去，在尝试进行MOF和类似材料中进行吸附选择性的定量预测时，包括框架灵活性的重要性可能已经低估了。

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