13C NMR spectra provide wide range chemical shift, and it suggests that can easily distinguish each signals. But carbon resolution of 2D spectra such as HSQC and HMBC is worse than 1D 13C spectra due to small data points. In order to analyze a compound with close 13C chemical shifts, a high resolution 2D spectrum is required frequently. In this document, some improvements to distinguish each signals on 13C axis of 2D hetero nuclear experiments are presented.
Reducing spectral width
In order to improve the resolution on the indirect dimension, 13C spectral width for 2D experiments should be set to the actual signal region. (Fig.1)
When limited region spectra would be enough to analysis, the higher resolution spectra will be available with the smaller spectra width parameter. However many signals come from the outside of the required region for the indirect dimension (fold), and it makes complicated and/or overlapping spectra frequently (Fig.2 red boxes).
In that case, by using selective pulse for 2D NMR experiments, simple high resolution spectra without folded signals will be collected (Fig.3).
Pulse sequence of 13C band-selective HMBC
Fig.4 Pulse sequence of 13C band-selective HMBC
We can get only limited range’s correlation by using 13C selective pulse. (Fig.4)
Increasing data points
If data points increase 2 or 4 times for indirect axis (13C axis), digital resolution also improves 2 and 4 times. But experiment time also increases 2 and 4 times. Moreover, if carbon FID is short-lived then signal to noise ratio would be poor.
The Non-Uniform-Sampling (NUS) is an effective technique to shorten experiment time for samples in adequate concentration. Fig.7 shows NUS version of the same experiment as in Fig.1 and Fig.3 but with 4 times more total points in carbon dimension and 25% NUS sampling. As a result, NUS spectrum shows 4 times higher resolution than spectrum in Fig.3 for the same experiment time.
Quinine has two 13C signals with chemical shifts at 147.63ppm and 147.83ppm. It is difficult to distinguish them in HMBC spectrum of Fig.5. By contrast, it becomes easy to distinguish them due to improved resolution in spectra of Fig.6 and Fig.7.
NUS is the sampling method which reduces the indirect dimension data points by collecting data points inhomogeneously. This data collection method would reduce experiment time, and it would give higher resolution spectrum for the same experiment time as indicated in this document. Not collected data points are reconstructed after data acquisition. Reconstructed FID data is available for the conventional data processing.
Fig.8 (Uniform sampling) and Fig.9 (NUS + reconstruction) are diagrams of FID in indirect dimension. The collected data points are the same each other, and measurement times are also the same. But NUS data points increase by 4 times due to reconstruction. Because resolution is proportional to data points, NUS data show 4 times higher resolution than conventional data.
Fig.8 Uniform sampling
Fig.9 NUS + reconstruction (25% data collection)
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