Chinese Journal of Magnetic Resonance >

2023 , Vol. 40 >Issue 4: 365 - 375

DOI: https://doi.org/10.11938/cjmr20233057

Articles

Optimizing Sensitivity-enhanced Quantitative 13C NMR Experiment by Genetic Algorithm

  • Linhong SONG ,
  • Xin CHAI ,
  • Xu ZHANG ,
  • Bin JIANG ,
  • Maili LIU
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  • 1. State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan (Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences), Wuhan 430071, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2023-03-03

  Online published: 2023-04-21

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Abstract

Quantitative NMR experiments are an essential part of NMR analysis, which play a critical role in component analysis and compound structure identification. Carbon atoms form the framework of organic compounds, and 13C NMR has unique advantages in organic analysis due to its wide chemical shift range, narrow spectral peaks, and broadband decoupling capability. However, the low natural abundance, low gyromagnetic ratio, and long longitudinal relaxation time of 13C nuclei hinder its wider application in quantitative experiments. In our previous work, we proposed the Q-DEPT+ pulse sequence and designed a double loop of pulse flip angle and polarization transfer time, which allows for uniform sensitivity enhancement for the three types of carbon nuclei, CH, CH2, and CH3, within a wide 1JCH range, making it suitable for quantitative 13C NMR. In this study, we further optimized the polarization transfer time and read pulse width of the Q-DEPT+ experiment by using a genetic algorithm, and replaced the 180° hard pulse in the 13C channel with a G5 composite pulse that compensates for the frequency offset effect. The optimized pulse sequence was named Q-DEPT ++. Quantitative experiments were performed on cholesterol acetate in CDCl3 by using the reverse-gated decoupling pulse sequence (zgig), Q-DEPT+, and Q-DEPT++ respectively, and the quantification accuracy and sensitivity of the three pulse sequences were compared. The results showed that Q-DEPT++ has obvious improvement in both quantification accuracy and sensitivity.

Key words： liquid-state NMR; quantitative NMR; 13C NMR; DEPT; genetic algorithm; sensitivity enhancement

Cite this article

Linhong SONG , Xin CHAI , Xu ZHANG , Bin JIANG , Maili LIU . Optimizing Sensitivity-enhanced Quantitative 13C NMR Experiment by Genetic Algorithm[J]. Chinese Journal of Magnetic Resonance, 2023 , 40(4) : 365 -375 . DOI: 10.11938/cjmr20233057

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