| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 155412 | Chemical Engineering Science | 2013 | 11 Pages |
In this study, quantitative structure-property relationship (QSPR) models have been developed to establish the relationship between the molecular structures and the critical micelle concentration (CMC) of 37 anionic surfactants using extended topochemical atom (ETA) indices along with computed hydrophobicity descriptors. The ETA models have also been compared to those developed with non-ETA topological descriptors along with hydrophobicity terms. The selection of the training and test compounds (n=28 and 9, respectively) was done by using a principle component analysis (PCA) score plot. The best ETA model (Q2=0.938; Rpred2=0.923) could outperform in statistical quality and predictive ability the models developed with non-ETA (Q2=0.910; Rpred2=0.885) and combined set (ETA and non-ETA) of descriptors (Q2=0.926; Rpred2=0.915). In this study, it is observed that hydrophobicity plays a major role in the model development for CMC of anionic surfactants while the branching character and electronic nature of the surfactants are also important as evidenced from different ETA parameters.
Graphical abstractFigure optionsDownload full-size imageDownload high-quality image (67 K)Download as PowerPoint slideHighlights► The ETA indices have been used for modeling of logCMC values of 37 anionic surfactants. ► The ETA indices can be easily calculated from 2D representation of chemical structure. ► The statistical quality of the best ETA model is better than the corresponding non-ETA model. ► The use of ETA descriptors along with the non-ETA ones improves the statistical quality of the models. ► The models can be used for prediction of logCMC values of anionic surfactants.
