Markov Chain Modeling of Surfactant Critical Micelle Concentration and Surface Composition.

Abstract

A Markov chain (MC) model has been used to model the following binary surfactant mixtures: linear alkylbenzenesulfonate (LAS4)/octaethylene glycol monododecyl ether (C12E8) at 10 and 25 °C, LAS6/acidic sophorolipid (AS), C12Betaine/C12Maltoside, sodium lauryl ether sulfate (SLES2)/C12E8, and rhamnolipid (R1)/LAS6. The critical micellar concentration and the composition of the adsorbed layer, for each system, can be modeled using the same monomer reactivity ratio values, g1 and g2. This implies that the interactions between the surfactants in the bulk solution and at the interface are the same, within error. For the LAS4/C12E8 system at 25 °C, the ranges of g1 and g2 values which can model both sets of data are within 0.03-0.05 and 1.55-2.10, respectively; g1 ≪ g2 implies that C12E8 is significantly more surface active than LAS4. The MC model indicates a negative change in the free energy upon mixing for all of the surfactant systems, consistent with the literature. The interfacial mixing behavior of LAS4/SLES2 is inferred from the results of the MC analysis of the LAS4/C12E8 and SLES2/C12E8 systems, which share a common surfactant partner in C12E8, and the prediction is in line with the published data.