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High resolution in heteronuclear 1H-13C NMR experiments by optimizing spectral aliasing with one-dimensional carbon data

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Published in Magnetic Resonance in Chemistry. 2003, vol. 41, no. 1, p. 3-17
Abstract In the chemistry literature it is common to provide NMR data on both proton and carbon spectra based on one-dimensional experiments, but often only proton spectra are assigned. The absence of a complete attribution of the carbons is in good part due to the difficulty in reaching the necessary resolution in the carbon dimension of two-dimensional experiments. It has already been shown that high-resolution heteronuclear spectra can be acquired within nearly the same acquisition time using a violation of the Nyquist condition. For a spectral width reduction by a given factor k, the resolution increases by the same factor as long as it is not limited by relaxation. The price to pay for such an improvement is a k-fold ambiguity in the chemical shift of the signal along the folded or aliased dimension. The computer algorithm presented in this paper takes advantage of the peak list stemming from one-dimensional spectra in order to calculate spectral widths for which the ambiguities in the aliased dimension of heteronuclear experiments are eliminated or at least minimized. The resolution improvement factor is only limited by the natural lineshape and reaches a typical value higher than 100. The program may be set to run automatically on spectrometers equipped with automatic sample changers. Applications to short-range HSQC experiments and long-range HMBC spectra of steroids, carbohydrates, a peptide and a mixture of isomers are shown as examples.
Keywords NMR1H NMR13C NMRHigh resolutionTwo-dimensional spectraAliasingFoldingSteroidsPeptidesCarbohydrates
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JEANNERAT, Damien. High resolution in heteronuclear 1H-13C NMR experiments by optimizing spectral aliasing with one-dimensional carbon data. In: Magnetic Resonance in Chemistry, 2003, vol. 41, n° 1, p. 3-17. https://archive-ouverte.unige.ch/unige:7893

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Deposited on : 2010-06-21

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