New chemometric strategies in the spectrophotometric determination of pKa

Abstract

In this work, principal component regression and partial least squares regression were used for the estimation of acid dissociation constants through UV-Vis spectrophotometric measurements, considering five well-known acid-base indicators as well as two herbicides as analytes. In each case, an acid-base titration was carried out. Then, the multivariate calibration model was constructed with a few absorption spectra of the series at extreme pH values, to which values of the dissociation fraction (α) of 1 or 0 were assigned, in the case of HA or Aspecies. After that, the prediction step consisted in the estimation of α for the rest of the series. Then, distribution diagrams were built up with α vs pH, to find α = 0.5 where pH = pK_a. The results were compared with those obtained through multivariate curve resolution-alternating least squares and program stability quotients from absorbance data (SQUAD), which showed an excellent correspondence.