Non-ionic surfactant phase diagram prediction by recursive partitioning

Abstract

A model has been designed to predict the phase which forms in water for a non-ionic surfactant, at a given concentration and temperature. The full phase diagram is generated by selecting enough data points to cover the region of interest. The model estimates the probability for each one of 10 possible phases and selects the one with the highest likelihood. The probabilities are based on the recursive partitioning of a dataset of 10 000 known observations. The model covers alkyl chain length and branching, ethoxylate head length and number, and end capping of one or more of the ethoxylate chains. The relationship between chemical structure, shape and phase behaviour is discussed. This article is part of the themed issue 'Soft interfacial materials: from fundamentals to formulation'.