Suppr超能文献

利用机械压力定制柔性金属有机框架的分离性能。

Tailoring the separation properties of flexible metal-organic frameworks using mechanical pressure.

作者信息

Chanut Nicolas, Ghoufi Aziz, Coulet Marie-Vanessa, Bourrelly Sandrine, Kuchta Bogdan, Maurin Guillaume, Llewellyn Philip L

机构信息

Aix-Marseille University, CNRS Laboratoire MADIREL (UMR7246), Marseille, France.

Massachusetts Institute of Technology, MultiScale Materials Science for Energy & Environment <MSE 2>, MIT-CNRS-AMU joint laboratory/MIT Energy Initiative, Cambridge, 02139, MA, USA.

出版信息

Nat Commun. 2020 Mar 5;11(1):1216. doi: 10.1038/s41467-020-15036-y.

Abstract

Metal-organic frameworks are widely considered for the separation of chemical mixtures due to their adjustable physical and chemical properties. However, while much effort is currently devoted to developing new adsorbents for a given separation, an ideal scenario would involve a single adsorbent for multiple separations. Porous materials exhibiting framework flexibility offer unique opportunities to tune these properties since the pore size and shape can be controlled by the application of external stimuli. Here, we establish a proof-of-concept for the molecular sieving separation of species with similar sizes (CO/N and CO/CH), via precise mechanical control of the pore size aperture in a flexible metal-organic framework. Besides its infinite selectivity for the considered gas mixtures, this material shows excellent regeneration capability when releasing the external mechanical constraint. This strategy, combining an external stimulus applied to a structurally compliant adsorbent, offers a promising avenue for addressing some of the most challenging gas separations.

摘要

金属有机框架因其可调节的物理和化学性质而被广泛用于化学混合物的分离。然而,尽管目前人们致力于开发用于特定分离的新型吸附剂,但理想的情况是一种吸附剂能用于多种分离。具有框架灵活性的多孔材料提供了独特的机会来调节这些性质,因为孔径和形状可以通过施加外部刺激来控制。在这里,我们通过对柔性金属有机框架中孔径的精确机械控制,建立了一种用于筛分分离尺寸相似的物种(CO/N和CO/CH)的概念验证。除了对所考虑的气体混合物具有无限选择性外,这种材料在解除外部机械约束时还表现出优异的再生能力。这种将外部刺激应用于结构柔顺吸附剂的策略,为解决一些最具挑战性的气体分离问题提供了一条有前途的途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abf6/7058087/93edce4df78f/41467_2020_15036_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验