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Prediction of Cloud Point Curves of Alkyl Ethoxylates with the Hydrophilic–Lipophilic‐Difference and Net‐Average‐Curvature (HLD‐NAC) Framework
Author(s) -
Choi Francis,
ZarateMuñoz Silvia,
Acosta Edgar J.
Publication year - 2019
Publication title -
journal of surfactants and detergents
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.349
H-Index - 48
eISSN - 1558-9293
pISSN - 1097-3958
DOI - 10.1002/jsde.12304
Subject(s) - cloud point , chemistry , pulmonary surfactant , curvature , thermodynamics , work (physics) , cloud computing , alkyl , point cloud , biological system , chromatography , organic chemistry , mathematics , computer science , physics , biochemistry , geometry , biology , computer vision , operating system
Understanding and predicting cloud point phenomena is important for the formulation of nonionic surfactant systems, and the design of cloud‐phenomena‐associated separation processes. There have been several approaches to fit and predict the cloud point phenomena, in most cases using bulk thermodynamic approaches. In this work, we introduced the hydrophilic–lipophilic‐difference and net‐average‐curvature (HLD‐NAC) as an interfacial (curvature) approach to predict cloud point values at different surfactant concentrations (cloud point curve). The HLD‐NAC method could fully predict the cloud point of alkyl ethoxylate of pure surfactants, typically within 4 °C of the experimental values, using published HLD constants, and the molecular structure of the surfactants. For commercial (polydispersed) surfactants, the same level of accuracy can be achieved if the experimental cloud point at 1 wt.% is used to adjust the HLD values. One additional benefit of using the HLD framework is the ability to predict changes in the cloud point curve with the introduction of electrolytes. While other models can fit the experimental data within 1 °C, the greater uncertainty of the HLD‐NAC (~4 °C) is a reasonable compromise given the simplicity of the approach.