Quantitative Structure-Property Relationship on Prediction of Cloud Point of Surfactants

Abstract

The quantitative structure-property relationship (QSPR) is used to predict the cloud point of surfactants. Several structural, electronic, spatial, and thermodynamic properties are selected as descriptors to build the relationship between cloud point and the microscopic structures. These descriptors include the octanol/water partition coefficient AlogP, the total energy, the molecular density, the highest occupied orbital energy EHOMO, Dipole-y and the Dipole-z. Two methods, the multiple linear regression (MLR) and partial least squares (PLS) analysis, were chosen to model the structure-properties relationships. The result showed that MLR analysis is better to predict the cloud point of nonionic surfactant than PLS analysis.