Property Prediction on Surfactant by Quantitative Structure‐Property Relationship: Krafft Point and Cloud Point

Abstract

General empirical relationships have been developed for estimating the Krafft point of anionic surfactants and cloud point of nonionic surfactants using the quantitative structure‐property relationship (QSPR) method. For the Krafft point, a six‐parameter structure‐property relationship (R²=0.941) was obtained for a diverse set of 46 anionic hydrocarbon surfactants and a three‐parameter relationship (R²=0.864) for 19 linear fluorocarbon anionic surfactants by employing topological, thermodynamic, and structural descriptors. For the cloud point of 64 nonionic surfactants with six representative structures, the best multiple linear regression model involved five parameters and had a correlation coefficient of R²=0.921. From these relations Krafft point or cloud point of surfactants can be estimated based on their molecular structure.

Keywords:

• Krafft point, cloud point, quantitative structure‐property relationship, anionic surfactants, nonionic surfactants

acknowledgment

The authors gratefully acknowledge financial support from the National Key Project of China (2004BA313B20), the National Natural Science Foundation (20303011), and the Natural Science Foundation (Y2004B06) of Shandong Province in China.