Structurally diverse quantitative structure--property relationship correlations of technologically relevant physical properties
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Biomedical subjects
AR Katritzky
Publications and source records attributed to AR Katritzky.
Predicting Surfactant Cloud Point from Molecular Structure
A general empirical relationship has been developed for estimating the cloud point of pure nonionic surfactants of the alkyl ethoxylate class. For a set of 62 structures, composed of linear alkyl, branched alkyl, cyclic alkyl, and alkylphenyl ethoxylates, cloud points can be estimated to an accuracy of ±6.3°C (3.7°C median error) using the logarithm of the number of ethylene oxide residues and three topological descriptors that account for hydrophobic domain variation. Copyright 1997Academic Press
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Prediction of Critical Micelle Concentration Using a Quantitative Structure-Property Relationship Approach
Relationships between the molecular structure and the critical micelle concentration (cmc) of anionic surfactants were investigated using a quantitative structure-property relationship approach. Measured cmc values for 119 anionic structures, representing sodium alkyl sulfates and sodium sulfonates with a wide variety of hydrophobic and hydrophilic structures, were considered. The best multiple linear regression model involved three terms (descriptors) and had a correlation coefficient of R2 = 0.940. Very good correlations (R2 = 0.988) were obtained using three descriptors for a subset of 68 structures, with structural variation only in the hydrophobic domain. From the descriptors used in these regressions, one can conclude that the cmc is primarily dependent on the size (volume or surface area) of the hydrophobic domain and to a lesser extent on the structural complexity of the surfactant molecule.
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