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REAL‐ t 1 , an Effective Approach for t 1 ‐Noise Suppression in NMR Spectroscopy Based on Resampling Algorithm
Author(s) -
Song Linhong,
Wang Jiannan,
Su Xuncheng,
Zhang Xu,
Li Conggang,
Zhou Xin,
Yang Daiwen,
Jiang Bin,
Liu Maili
Publication year - 2020
Publication title -
chinese journal of chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.28
H-Index - 41
eISSN - 1614-7065
pISSN - 1001-604X
DOI - 10.1002/cjoc.201900389
Subject(s) - resampling , noise (video) , chemistry , algorithm , spectral line , amplitude , fourier transform , analytical chemistry (journal) , random noise , spectroscopy , two dimensional nuclear magnetic resonance spectroscopy , nuclear magnetic resonance , biological system , artificial intelligence , computer science , mathematics , optics , physics , mathematical analysis , stereochemistry , chromatography , quantum mechanics , image (mathematics) , biology
Summary of main observation and conclusion In multidimensional ( n D) NMR spectroscopy, t 1 noise usually appears as ridges along indirect dimensions, and affects observation of weak signals. The main source of t 1 noise is instrumental instability, which causes random variation of FID amplitude during data acquisitions and introduces random noise‐like peaks into spectrum after Fourier transformation. A number of efforts have been devoted, in order to develop new method or to improve existing approaches for suppressing t 1 noise. Herein, we propose a novel t 1 noise suppression method based on resampling algorithm for data processing, shortened as REAL‐ t 1 . The method was verified using simulated 2D spectra, and NOESY spectra of sucrose and protein GB1, showing that the spectral quality was improved in all cases. The performance of REAL‐ t 1 was also compared with another recently proposed method, which showed that these two methods provided similar performance while REAL‐ t 1 cost much shorter experimental time.