Estimation of critical micelle concentration of anionic surfactants with QSPR approach

The hydrophobic–hydrophilic segment geometries of 98 anionic surfactants were fully optimized and calculated by ab initio RHF/6-31G(d), quantum chemical data such as the charge density, the energy of molecular orbital and the dipole moment were obtained. The anionic surfactants employed including sodium alkyl sulfates, sodium alkyl sulfonates, sodium alkyl benzenesulfonates, and potassium alkyl carboxylates with a wide variety of hydrophobic structures. Based on one constitutional descriptor and two quantum chemical descriptors, a significant quantitative structure–property relationship (QSPR) model for the critical micelle concentration of anionic surfactants was obtained by using the multiple linear regression technique. The good correlation coefficient of R2 (0.980) and cross-validation correlation coefficient Rcv2 (0.978) indicate the excellent capability and stability of the regression equation developed. It was found out that the total atom number (NT) in the surfactant hydrophobic–hydrophilic segment plays a major role in the model, the dipole moment (μ) of the surfactant segment and the max net atomic charge on C atom (QC-max) in the surfactant segment are also important. Nine anionic surfactants were employed to test the model developed, the calculated critical micelle concentration was consistent with the experimental one.