Iterative baseline correction algorithm for dead time truncated one-dimensional solid-state MAS NMR spectra

We present an algorithm suitable for automatically correcting rolling baseline coming from time-domain truncation induced by the dead time in pulse-acquire one-dimensional MAS NMR spectra. It relies on an iterative estimation of the baseline restricted in the time-domain by the dead time duration co...

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Bibliographic Details
Published inSolid state nuclear magnetic resonance Vol. 110; p. 101699
Main Authors Yon, Maxime, Fayon, Franck, Massiot, Dominique, Sarou-Kanian, Vincent
Format Journal Article
LanguageEnglish
Published Elsevier Inc 01.12.2020
Elsevier
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Summary:We present an algorithm suitable for automatically correcting rolling baseline coming from time-domain truncation induced by the dead time in pulse-acquire one-dimensional MAS NMR spectra. It relies on an iterative estimation of the baseline restricted in the time-domain by the dead time duration combined with a histogram filter allowing adaptive selection of the baseline points. This method does not make any assumption regarding the NMR resonances line shapes or widths and does not modify the acquired free induction decay points. This makes it suitable for accurate deconvolution and quantification of single-pulse MAS NMR spectra. The baseline correction accuracy is evaluated on synthetic solid-state spectra of 19F, 71Ga, and 23Na by comparing the fitted baseline to the theoretical one. The versatility of the algorithm is also exemplified on three additional solid-state spectra of 23Na and 71Ga. The algorithm is made available to the community through a user-friendly standalone Matlab® application. [Display omitted] •Automatic correction of rolling baseline time in pulse-acquire MAS NMR spectra.•Does not make any assumption regarding the NMR resonances line shapes or widths.•Does not modify the acquired free induction decay points.•Suitable for accurate deconvolution and quantification of single-pulse MAS NMR spectra.•Available to the community through a user-friendly standalone Matlab® application.
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ISSN:0926-2040
1527-3326
DOI:10.1016/j.ssnmr.2020.101699