Sensitivity in HMBC and LR-HSQMBC experiments

Long range correlations are critical for structure elucidation. They are typically identified using HMBC experiments¹, but a relatively recent alternative is the LR-HSQMBC experiment². Recent attempts to confirm the structure of several challenging molecules in the Facility prompted an examination of the sensitivity of these two experiments to determine which is most likely to provide the crucial long range correlations.

Distinguishing chlorine and bromine by 1H-13C HSQC

Natural products often incorporate chlorine or bromine, but less rarely are both halogens found in the same molecule. When they are, the problem becomes how to distinguish them. Typically, chlorinated carbon resonances are assumed to be shifted further downfield than brominated ones. This rule of thumb was of no help to one of our users who recently isolated a compound containing both chlorine and bromine because the two halogenated carbons had very similar chemical shifts. How then could we distinguish the two halogens?

Hadamard NMR

Hadamard NMR is a method for reducing the acquisition time of two-dimensional experiments by only acquiring the rows in the 2D that contain signals. By using a Hadamard matrix, multiple selective one-dimensional spectra can by acquired simultaneously and deconvoluted post-acquisition.

Non uniform sampling

Non uniform sampling (NUS) is a method for collecting a subset of the indirect points typically acquired, thereby reducing experiment time. As little as 10% of an indirect dimension can be collected without reducing spectral quality. NUS offers significant time savings, particularly for higher dimensionality experiments.

Aliasing

Aliasing is the appearance of resonances at somewhere other than their natural chemical shift in the indirect dimension(s) of multi-dimensional spectra. Aliasing can be used to reduce the time taken to acquire spectra without sacrificing resolution or sensitivity.

Processing: linear prediction

Linear prediction is the process of extending an FID by predicting additional points from experimental data points. It is often used in the indirect dimensions of multidimensional experiments where time restrictions prevent full sampling of the decay.

Processing: zero filling

Zero filling is the process of extending an FID with extra points of zero intensity. After fourier transformation the extra points interpolate between the experimental points smoothing the spectrum and often increasing resolution.