Abstract
A quantitative structure property relationship approach was performed to find the relation between the surfactant structure and its effect on water–oil interfacial tension. As a result, a new database has been developed measuring the interfacial tension between n-decane as the model oil and different aqueous solutions of some ionic compounds. In spite of other reports we selected surfactants by a scientific method that covers all structural information. Twenty four different compounds were selected by the principle component analysis method and their interfacial tensions were measured at their critical micelle concentrations. The geometrical optimization of surfactants was performed at the B3LYP/6-311G** level and quantum chemical and structural descriptors were calculated using relevant computer software programs. The best fitted descriptors were selected using the variable selection of the genetic algorithm (GA-MLR). The predictive test was performed for an external prediction set of 6 compounds, chosen out of 24 compounds. The resulted GA-MLR model can reasonably predict the interfacial tension using only three selected descriptors. The deviation between predicted and measured values was found to be <7%.
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Abbreviations
- QSPR:
-
Quantitative structure property relationship
- PCA:
-
Principal component analysis
- GA:
-
Genetic algorithm
- MLR:
-
Multiple linear regression
- CMC:
-
Critical micelle concentration
- PC:
-
Principle component
- SVD:
-
Singular value decomposition
- DFT:
-
Density functional theory
- Jhetv:
-
Van der Waals’ weighted distance matrix
- RDF:
-
Radial distribution function
- ASDA:
-
Axisymmetric drop shape analysis
- ME:
-
Mean effect
- LMO:
-
Leave many out
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Fallah Fini, M., Riahi, S. & Bahramian, A. Experimental and QSPR Studies on the Effect of Ionic Surfactants on n-Decane–Water Interfacial Tension. J Surfact Deterg 15, 477–484 (2012). https://doi.org/10.1007/s11743-012-1330-7
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DOI: https://doi.org/10.1007/s11743-012-1330-7