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

Authors :
SONG Linhong
CHAI Xin
ZHANG Xu
JIANG Bin
LIU Maili
Source :
Chinese Journal of Magnetic Resonance, Vol 40, Iss 4, Pp 365-375 (2023)
Publication Year :
2023
Publisher :
Science Press, 2023.

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.

Details

Language :
Chinese
ISSN :
10004556
Volume :
40
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Chinese Journal of Magnetic Resonance
Publication Type :
Academic Journal
Accession number :
edsdoj.b021584164d47adae8466e5f1300807
Document Type :
article
Full Text :
https://doi.org/10.11938/cjmr20233057