Innovative Application of Multiple Linear Regression for Analysis of Interactions of Divalent Metal Ions With Anionic Surfactant

ABSTRACT The properties and aggregations of anionic surfactants change strongly in the presence of multivalent cations. Therefore, the knowledge of the binding of multivalent metal ions to the headgroups of anionic surfactants can be helpful for the applications of surfactants in various fields. This paper presents an analysis of the interactions of 14 divalent metal ions (Me 2+ ) with headgroups of dodecyl sulphate (DS) trimers. The mathematical analysis was performed on the experimental data obtained from the tandem mass spectrometric measurements. In the experiment, an aqueous surfactant solution containing a given electrolyte is infused into a Q‐ToF mass spectrometer, water is removed from the sample at 300°C, and next, fragmentation of [Me(DS) 3 ] − ions occurs. The multiple linear regression (MLR) analysis was applied to the data sets comprising the values of the molecular ion survival yield ( Y ) and mass peak intensities of the precursor (i.e., [Me(DS) 3 ] − ) and fragment (i.e., DS − ) ions determined at different collision energies. The Y quantity is a measure of both the stability of [Me(DS) 3 ] − ions and the strength of Me 2+ binding to the DS trimer. In the MLR equation used, the regression coefficients ( b i ) address the share of the precursor and fragment ions in the survival yield of the decomposable [Me(DS) 3 ] − ion. The b i values together with a high coefficient of determination ( R 2 > 0.95) prove that the MLR model describes well the results obtained in this study by mass spectrometry. Only after application of the MLR method, linear correlations were found between the water‐structural properties of Me 2+ cations and the mass spectrometric data.