High-resolution NMR spectroscopy for measuring complex samples based on chemical-shift-difference selection

Literature Information

Publication Date 2022-12-02
DOI 10.1039/D2CP04279G
Impact Factor 3.676
Authors

Ziqiao Chen, Xueting Li, Yuqing Huang, Shuohui Cao, Zhong Chen, Yulan Lin


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Abstract

NMR spectroscopy serves as an immensely powerful tool for component assignments and molecular structure elucidations. However, proton NMR spectra are generally trapped with spectral congestion caused by limited frequency differences and complex multiplets. 2D NMR can effectively relieve spectral congestion, but its resolution and acquisition efficiency are restricted by the broad spectral bandwidth. Herein, we introduce an NMR method based on chemical-shift-difference selection by chirp excitation to record high-resolution 2D NMR spectra for extracting coupling correlation networks and multiplet structures, suitable for measurements on complex samples. The performance of the proposed method is illustrated in determining diastereotopic methylene protons, small frequency-difference coupled proton pairs of furanose, pyranose and benzene rings. This study is expected to benefit molecular structure elucidation and composition analysis of complex samples in chemistry, biochemistry and metabonomics.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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