pKa prediction of per- and polyfluoroalkyl acids in water using in silico gas phase stretching vibrational frequencies and infrared intensities

Abstract

To successfully understand and model the environmental fate of per- and polyfluoroalkyl substances (PFAS), it is necessary to know key physicochemical properties (PChPs) such as pK_a; however, measured PChPs of PFAS are scarce and of uncertain reliability. In this study, quantitative structure–activity relationships (QSARs) were developed by correlating calculated (M062-X/aug-cc-pVDZ) vibrational frequencies (VF) and corresponding infrared intensities (IR_Int) to the pK_a of carboxylic acids, sulfonic acids, phosphonic acids, sulfonamides, betaines, and alcohols. Antisymmetric stretching VF of the anionic species were used for all subclasses except for alcohols where the OH stretching VF performed better. The individual QSARs predicted the pK_a for each subclass mostly within 0.5 pK_a units from the experimental values. The inclusion of IR_Int as a pK_a predictor for carboxylic acids improved the results by decreasing the root-mean-square error from 0.35 to 0.25 (n > 100). Application of the developed QSARs to estimate the pK_a of PFAS within each subclass revealed that the length of the perfluoroalkyl chain has minimal effect on the pK_a, consistent with other models but in stark contrast with the limited experimental data available.