A robust t1 noise suppression method in NMR spectroscopy

Artefacts in high-resolution multidimensional nuclear magnetic resonance (NMR) spectra, known as t(1) noise, can significantly downgrade the spectral quality and remain a significant noise source, limiting the sensitivity of most two-dimensional NMR experiments. In addition to highly sensitive hardware and experimental designs, data post-processing is a relatively simple and cost-effective method for suppressing t(1) noise. In this study, histograms and quantiles were used to obtain a robust estimation of noise level. We constructed a weighted matrix to suppress the t(1) noise. The weighted matrix was calculated from the logistic functions, which were adaptively computed from the spectrum. The proposed method is robust and effective in both simulations and actual experiments. Further, it can maintain the quantitative relationship of the spectrogram and is suitable for various complex peak types.