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Publishing Language: Chinese | Open Access

Quantitative nuclear magnetic resonance: Experimental methods and typical applications

Juan TANGGaoFei HU( )
Analysis and Testing Center, College of Chemistry, Beijing University of Chemical Technology, Beijing 100029, China
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Abstract

Quantitative nuclear magnetic resonance (qNMR) technology is a highly versatile and accurate quantitative analysis approach. Due to its merits, such as simple operation, no requirement for reference standards of the analytes, and the capacity to conduct structural analysis of the analytes and impurities simultaneously during quantitative analysis, it has found extensive applications in the quantitative analysis of materials such as pharmaceuticals, food, natural products, and metabolomics. The fundamental principle of quantitative nuclear magnetic resonance is that the number of atoms generating a specific resonance signal in different chemical environments is proportional to the intensity of the nuclear magnetic response signal, and the signal response of the same atomic nucleus in different molecules shows no discrepancy under optimized conditions. In this paper, we review the sample preparation procedures, experimental parameter optimization and data processing methods required in order to obtain accurate signal intensities and, hence, accurate quantitative results. Taking the two currently most typical 1H qNMR applications, namely hydrogen quantitative NMR (1H qNMR) analysis of low-abundance (concentration) substances and purity determination of high-purity substances (reference materials, etc.), as examples, we have highlighted relevant experimental methods and provide a general overview of the use of NMR quantitative analysis in various fields.

CLC number: O482.53+2

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Journal of Beijing University of Chemical Technology (Natural Science Edition)
Pages 1-14

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Cite this article:
TANG J, HU G. Quantitative nuclear magnetic resonance: Experimental methods and typical applications. Journal of Beijing University of Chemical Technology (Natural Science Edition), 2025, 52(2): 1-14. https://doi.org/10.13543/j.bhxbzr.2025.02.001

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Received: 12 November 2024
Published: 20 March 2025
© 2025 The Authors.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).