Improving resolution in multidimensional NMR using random quadrature detection with compressed sensing reconstruction.

ABSTRACT: NMR spectroscopy is central to atomic resolution studies in biology and chemistry. Key to this approach are multidimensional experiments. Obtaining such experiments with sufficient resolution, however, is a slow process, in part since each time increment in every indirect dimension needs to be recorded twice, in quadrature. We introduce a modified compressed sensing (CS) algorithm enabling reconstruction of data acquired with random acquisition of quadrature components in gradient-selection NMR. We name this approach random quadrature detection (RQD). Gradient-selection experiments are essential to the success of modern NMR and with RQD, a 50 % reduction in the number of data points per indirect dimension is possible, by only acquiring one quadrature component per time point. Using our alg

SUBMITTER: Bostock MJ 

PROVIDER: S-EPMC5504140 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature