Abstract
Hypothesis: The formation of transient networks of giant micelles leads to a viscosity peak when salt is added to aqueous solutions of charged surfactants. It is the consequence of an increase of the packing parameter due to charge screening of the surfactant headgroups, leading to a continuous transformation of the aggregates from spherical to wormlike micelles, and finally to branched networks. ...
Abstract
Hypothesis: The formation of transient networks of giant micelles leads to a viscosity peak when salt is added to aqueous solutions of charged surfactants. It is the consequence of an increase of the packing parameter due to charge screening of the surfactant headgroups, leading to a continuous transformation of the aggregates from spherical to wormlike micelles, and finally to branched networks. It should therefore be possible to predict the macroscopic viscosity of entangled giant micelles by modelling the packing parameter at nanoscale. Experiments: A thermodynamic model is presented with a minimum of adjustable parameters, where branched networks are considered to be built from three coexisting microphases: cylinders, endcaps, and junctions. We use spontaneous packing parameters, in which the whole molecular length instead of the commonly used hydrocarbon chain length is considered. Standard reference chemical potentials and subsequently the occurrence of each microphase can be explicitly derived at specific electrolyte concentrations. Effective micellar length of giant micelles can be obtained from the microphase composition and is subsequently used to calculate the viscosity. Findings: The model successfully predicts position and intensity of the viscosity maximum observed in experimental salt curves of sodium laureth sulfate (SLES). The robustness of the model was further investigated for various types of added salts or fragrance oils that affect differently spontaneous packing parameters or interfacial bending energy. An excellent agreement of the simulated salt curves with experimental data was achieved. (C) 2018 Elsevier Inc. All rights reserved.
Altmetric