Spectral restoration from low signal-to-noise, distorted NMR signals: Application to hyphenated capillary electrophoresis-NMR

In capillary electrophoresis separations coupled to NMR signal detection using small solenoidal coils, electrophoretic currents cause substantial distortion in the NMR spectral linewidths and peak heights, distortions which cannot be fully counteracted through shimming. The NMR spectra also have a low signal-to-noise ratio due to the small amounts of material, typically <1 nmol, associated with such microseparations. This study proposes a two-step, signal processing method to restore spectral lines from the distorted NMR spectrum. First, a reference signal is acquired to estimate the broadening function, as a combination of several Lorentzian functions, using a gradient descent method. Then multi-resolution wavelet analysis is applied to the distorted spectrum to determine an initial estimate of the frequencies of the spectral lines. Convergence to the final spectrum, a second set of Lorentzians, involves deconvolution with the estimated broadening function using a gradient descent method. Experimental CE-NMR data show that considerable improvements in spectral quality are possible using this approach, although fine splittings can not be resolved if the broadening function is large.