Introducing ambiguity of data interpretation can provide better answers for interpreting NMR data
What is it about?
Our studies have shown that about 1/2 of structure elucidation studied actually contain some long range correlations of 4-6 bonds, so-called "nonstandard" correlations. Correct solutions are not easily attainable. Unfortunately nonstandard correlations and the number of intervening bonds usually cannot be identified experimentally. In this work we suggest a new approach that we term Fuzzy Structure Generation.
Why is it important?
Using Fuzzy generation allows the solution of structural problems whose 2D NMR data contain an unknown number of nonstandard correlations having different and unknown lengths using Computer-Assisted Structure Elucidation
The following have contributed to this page: Dr Antony John Williams, Kirill Blinov, and Prof. Dr. Mikhail Elyashberg
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