固体核磁共振技术在金属有机骨架结构表征中的应用

IF 1.8 3区 化学 Q4 CHEMISTRY, PHYSICAL Solid state nuclear magnetic resonance Pub Date : 2022-02-01 DOI:10.1016/j.ssnmr.2022.101772
Caiyan He , Shenhui Li , Yuqing Xiao , Jun Xu , Feng Deng
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引用次数: 6

摘要

固体核磁共振可以在原子水平上提供化学组成、局部环境和空间配位等结构信息,已广泛应用于表征金属有机框架(MOFs)的详细结构和主客体相互作用。本文简要介绍了多功能固态核磁共振技术在mof结构表征方面的最新进展。高场灵敏度增强的固态核磁共振方法可以直接观察到含有低-γ核的mof中的金属中心。二维(2D)同核和异核相关的MAS NMR实验提供了连接体、金属簇和引入的客体分子之间的空间接近性。此外,使用固态核磁共振定量测量核间距离提供了有关mof内连接几何形状以及主-客体相互作用的有价值的结构信息。此外,固态核磁共振在揭示含有顺磁性金属中心的mof的结构特性方面显示出巨大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Application of solid-state NMR techniques for structural characterization of metal-organic frameworks

Solid-state NMR can afford the structural information about the chemical composition, local environment, and spatial coordination at the atomic level, which has been extensively applied to characterize the detailed structure and host-guest interactions in metal-organic frameworks (MOFs). In this review, recent advances for the structural characterizations of MOFs using versatile solid-state NMR techniques were briefly introduced. High-field sensitivity-enhanced solid-state NMR method enabled the direct observation of metal centers in MOFs containing low-γ nuclei. Two-dimensional (2D) homo- and hetero-nuclear correlation MAS NMR experiments provided the spatial proximity among linkers, metal clusters and the introduced guest molecules. Moreover, quantitative measurement of inter-nuclear distances using solid-state NMR provided valuable structural information about the connectivity geometry as well as the host-guest interactions within MOFs. Furthermore, solid-state NMR has exhibited great potential for unraveling the structure property of MOFs containing paramagnetic metal centers.

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来源期刊
CiteScore
5.30
自引率
9.40%
发文量
42
审稿时长
72 days
期刊介绍: The journal Solid State Nuclear Magnetic Resonance publishes original manuscripts of high scientific quality dealing with all experimental and theoretical aspects of solid state NMR. This includes advances in instrumentation, development of new experimental techniques and methodology, new theoretical insights, new data processing and simulation methods, and original applications of established or novel methods to scientific problems.
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