Automated Spectrum Simulation Methods for Carbon-13 Nuclear Magnetic Resonance Spectroscopy Based on Database Retrieval and Model-Building Strategies

摘要

An automated method for the prediction of carbon-13 nuclear magnetic resonance (~13C NMR) chemical shifts which involves the combined use of database retrieval and multivariate calibration methods is described. A commercial database of chemical structures and experimentally measured and assigned ~13C NMR spectra is used to implement this methodology. The chemical environment of each of the carbons in the database is encoded as a vector, and Euclidean distance comparisons are made between these vectors and the similarly encoded environment of a target carbon whose chemical shift is to be predicted. This procedure yields a calibration set of carbon atoms with chemical environments similar to that of the target carbon.