Literature DB >> 34115080

Solid-state NMR studies of internuclear correlations for characterizing catalytic materials.

Guodong Qi1, Qiang Wang1, Jun Xu1, Feng Deng1.   

Abstract

Understanding the nature of heterogeneous catalysts is critical for the rational design of highly active catalysts, which necessitates in-depth characterization of the structure and properties of catalysts as well as reaction mechanisms. Solid-state NMR correlation spectroscopy is becoming increasingly recognized as a powerful tool in the study of catalysts and catalytic reactions because of its capability to provide atomic-level insights into the structure, interaction and dynamics of molecules by establishing connectivity and proximity between the same or distinct nuclei. This tutorial review focuses on the fundamentals and state-of-the-art applications of solid-state NMR correlation techniques to structural characterization of catalytic materials including zeolites, metal oxides, organometallic complexes and MOFs as well as relevant studies regarding synthesis, synergistic catalysis, host-guest interactions and reaction mechanisms. Various correlation NMR methods that have been employed to address the challenging issues in heterogeneous catalysis are highlighted. This review concludes with outlooks on the promising applications and potential developments of solid-state NMR correlation spectroscopy in catalytic materials.

Entities:  

Year:  2021        PMID: 34115080     DOI: 10.1039/d0cs01130d

Source DB:  PubMed          Journal:  Chem Soc Rev        ISSN: 0306-0012            Impact factor:   54.564


  3 in total

Review 1.  Emerging analytical methods to characterize zeolite-based materials.

Authors:  Sophie H van Vreeswijk; Bert M Weckhuysen
Journal:  Natl Sci Rev       Date:  2022-03-12       Impact factor: 23.178

Review 2.  Recent advances in solid-state NMR of zeolite catalysts.

Authors:  Weiyu Wang; Jun Xu; Feng Deng
Journal:  Natl Sci Rev       Date:  2022-08-08       Impact factor: 23.178

3.  High-Field NMR, Reactivity, and DFT Modeling Reveal the γ-Al2 O3 Surface Hydroxyl Network.

Authors:  Nicolas Merle; Tarnuma Tabassum; Susannah L Scott; Alessandro Motta; Kai Szeto; Mostafa Taoufik; Régis Michaël Gauvin; Laurent Delevoye
Journal:  Angew Chem Int Ed Engl       Date:  2022-08-03       Impact factor: 16.823

  3 in total

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