Using mathematical processing techniques to build molecular skeletons from NMR data
What is it about?
Long-range 1H-15N heteronuclear shift correlation methods at natural abundance to facilitate the elucidation of small molecule structures have assumed a role of growing importance over the past decade. We show that mathematical processing techniques, called unsymmetrical indirect covariance methods, can be employed to indirectly determine several types of hyphenated 2D NMR data from higher sensitivity experiments.
Why is it important?
Some experiments are highly improbable if not impossible to run as direct NMR experiments. But OTHER experiments can be processed mathematically and combined to give access to "synthetic forms" of experimental data. THis paper shows some of the approaches for C13 and N15 2D NMR data
The following have contributed to this page: Dr Antony John Williams, Kirill Blinov, and Gary Martin
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