| abstract |
A new strategy for the quantitative determination of enantiomeric purity that combines guest-host complexation, spectroscopy, and chemometric modeling. Spectral data for samples of known enantiomeric composition is subjected to a type of multivariate regression modeling known as partial least squares ('PLS-1') regression. The PLS-1 regression produces a mathematical model that can be used to predict the enantiomeric composition of a set of samples of unknown enantiomeric purity. |