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通过高场固态核磁共振光谱法绘制γ -AlO的氧结构。

Mapping the oxygen structure of γ-AlO by high-field solid-state NMR spectroscopy.

作者信息

Wang Qiang, Li Wenzheng, Hung Ivan, Mentink-Vigier Frederic, Wang Xiaoling, Qi Guodong, Wang Xiang, Gan Zhehong, Xu Jun, Deng Feng

机构信息

National Centre for Magnetic Resonance in Wuhan, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Key Laboratory of Magnetic Resonance in Biological Systems, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China.

National High Magnetic Field Laboratory, 1800 East Paul Dirac Drive, Tallahassee, FL, 32310-3706, USA.

出版信息

Nat Commun. 2020 Jul 17;11(1):3620. doi: 10.1038/s41467-020-17470-4.

Abstract

γ-AlO is one of the most widely used catalysts or catalyst supports in numerous industrial catalytic processes. Understanding the structure of γ-AlO is essential to tuning its physicochemical property, which still remains a great challenge. We report a strategy for the observation and determination of oxygen structure of γ-AlO by using two-dimensional (2D) solid-state NMR spectroscopy at high field. 2D O double-quantum single-quantum homonuclear correlation NMR experiment is conducted at an ultra-high magnetic field of 35.2 T to reveal the spatial proximities between different oxygen species from the bulk to surface. Furthermore, 2D proton-detected H-O heteronuclear correlation NMR experiments allow for a rapid identification and differentiation of surface hydroxyl groups and (sub-)surface oxygen species. Our experimental results demonstrate a non-random distribution of oxygen species in γ-AlO.

摘要

γ-AlO是众多工业催化过程中使用最广泛的催化剂或催化剂载体之一。了解γ-AlO的结构对于调节其物理化学性质至关重要,而这仍然是一个巨大的挑战。我们报告了一种通过在高场使用二维(2D)固态核磁共振光谱来观察和确定γ-AlO氧结构的策略。在35.2 T的超高磁场下进行二维氧双量子单量子同核相关核磁共振实验,以揭示从体相到表面不同氧物种之间的空间邻近性。此外,二维质子检测的H-O异核相关核磁共振实验能够快速识别和区分表面羟基和(亚)表面氧物种。我们的实验结果表明γ-AlO中氧物种存在非随机分布。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8241/7367832/54b5a67418b4/41467_2020_17470_Fig2_HTML.jpg

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