Spectroscopically probing the effects of Holmium(III) based complex counterion on the dye-cationic surfactant interactions

Steady State and Time-Resolved Fluorescence Spectroscopy of Cinchonine Dication in Sodium Dodecylsulphate Micellar System

This paper reports the influence of surface charge of the micelles on to the photophysical properties of a cinchonine dication (C2+) fluorophore in anionic, sodium dodecylsulphate (SDS), surfactant at premicellar, micellar and post-micellar concentrations in aqueous phase at room temperature. The magnitude of edge excitation red shift (EERS) in the fluorescence maximum of C2+ in bulk water solution is 1897 cm- 1 whereas, in the case of SDS it is observed to be 1984 cm- 1. The fluorescence decay curve of C2+ fits with multi exponential functions in the micellar system. The increase in lifetime of C2+ in SDS has been attributed to the increase in radiative rate due to the incorporation of C2+ at the micelle -water interface. The value of dynamic quenching constant determined is 16.9 M- 1. The location of the probe molecule in micellar systems has been justified by a variety of spectral parameters such as dielectric constant, ET (30), viscosity, EERS, average fluorescence decay time, radiative and non-radiative rate constants. All experimental results suggest that the C2+ molecule binds strongly with the SDS micelles and resides at micellar-water interface. The binding constant (Kb) calculated (3.85 × 105 M- 1) for C2+ in SDS revealed that the electrostatic forces mediate charge probe-micelle association.

Collection of Partition Coefficients in Hexadecyltrimethylammonium Bromide, Sodium Cholate, and Lithium Perfluorooctanesulfonate Micellar Solutions: Experimental Determination and Computational Predictions

This study focuses on determining the partition coefficients (logP) of a diverse set of 63 molecules in three distinct micellar systems: hexadecyltrimethylammonium bromide (HTAB), sodium cholate (SC), and lithium perfluorooctanesulfonate (LPFOS). The experimental log p values were obtained through micellar electrokinetic chromatography (MEKC) experiments, conducted under controlled pH conditions. Then, Quantum Mechanics (QM) and machine learning approaches are proposed for the prediction of the partition coefficients in these three micellar systems. In the applied QM approach, the experimentally obtained partition coefficients were correlated with the calculated values for the case of the 15 solvent mixtures. Using Density Function Theory (DFT) with the B3LYP functional, we calculated the solvation free energies of 63 molecules in these 16 solvents. The combined data from the experimental partition coefficients in the three micellar formulations showed that the 1-propanol/water combination demonstrated the best agreement with the experimental partition coefficients for the SC and HTAB micelles. Moreover, we employed the SVM approach and k-means clustering based on the generation of the chemical descriptor space. The analysis revealed distinct partitioning patterns associated with specific characteristic features within each identified class. These results indicate the utility of the combined techniques when we want an efficient and quicker model for predicting partition coefficients in diverse micelles.