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Metal-organic frameworks in separations: A review
Analytica Chimica Acta ( IF 5.7 ) Pub Date : 2022-08-06 , DOI: 10.1016/j.aca.2022.340208
Sepideh Khaki Firooz 1 , Daniel W Armstrong 1
Affiliation  

It is possible to design high permeability and selective metal-organic frameworks (MOFs) with designable functionality. The large number of possible MOF structural permutations arise from the considerable number of possible metal nodes and the great variety of organic ligands used for these materials. Herein, we discuss the applications of MOFs in all manner of separations including gas adsorption/separations, membranes, gas chromatography (GC), liquid chromatography (LC), water harvesting and the computer/machine learning design of MOFs. Each application requires MOFs with specific structural motifs. Relevant properties include polarity, temperature stability, solvent stability, pore size, pore volume, surface area, etc. MOFs used for the adsorption and separation of gases can be quite different from those used in membrane technologies or as chromatographic stationary phases. In the area of chromatography, there are far more reports of GC separations than LC. Also, there has been considerable efforts at developing MOF chiral stationary phases. Hence additional chiral components are added to the MOF support, such as cyclodextrins and various amino acids. MOFs have been used as general adsorbents for both inorganic and organic molecules. A very unique MOF application involves water harvesting. It is shown that potable water can be made in arid environments by selectively adsorbing water vapor from air, even at low humidity. Such MOFs could have important analytical applications, as well. Finally, there is a new focus on automated design of MOFs with desired properties for specific tasks, using computational design and machine learning. This is briefly covered in the final section of this review.



中文翻译:

分离中的金属有机框架:综述

可以设计具有可设计功能的高渗透性和选择性金属有机框架 (MOF)。大量可能的 MOF 结构排列源于大量可能的金属节点和用于这些材料的多种有机配体。在此,我们讨论了 MOF 在各种分离方式中的应用,包括气体吸附/分离、膜、气相色谱 (GC)、液相色谱 (LC)、集水和 MOF 的计算机/机器学习设计。每个应用程序都需要具有特定结构图案的 MOF。相关性能包括极性、温度稳定性、溶剂稳定性、孔径、孔体积、表面积等。用于气体吸附和分离的 MOF 与膜技术或色谱固定相中使用的 MOF 完全不同。在色谱领域,GC 分离的报道远多于 LC。此外,在开发 MOF 手性固定相方面也付出了相当大的努力。因此,额外的手性成分被添加到 MOF 支持物上,例如环糊精和各种氨基酸。MOF 已被用作无机和有机分子的一般吸附剂。一个非常独特的 MOF 应用涉及集水。结果表明,即使在低湿度下,也可以通过选择性地吸附空气中的水蒸气在干旱环境中制造饮用水。这种 MOF 也可能具有重要的分析应用。最后,使用计算设计和机器学习自动设计具有特定任务所需特性的 MOF 成为了新的焦点。本综述的最后部分简要介绍了这一点。

更新日期:2022-08-08
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