An experimental rheological phase diagram of a tri-block co-polymer in water validated against dissipative particle dynamics simulations.

Aqueous solutions of tri-block co-polymer surfactants are able to aggregate into a rich variety of microstructures, which can exhibit different rheological behaviors. In this work, we study the diversity of structures detected in aqueous solutions of Pluronic L64 at various concentrations and temperatures by experimental rheometry and dissipative particle dynamics (DPD) simulations. Mixtures of Pluronic L64 in water (ranging from 0 to 90 wt% Pluronic L64) have been studied in both linear and non-linear regimes by oscillatory and steady shear flow. The measurements allowed for the determination of a complete rheological phase diagram of the Pluronic L64-water system. The linear and non-linear regimes have been compared to equilibrium and non-equilibrium DPD bulk simulations of similar systems obtained by using the software LAMMPS. The molecular results are capable of reproducing the equilibrium structures, which are in complete agreement with the ones predicted through experimental linear rheology. The simulations also depict micellar microstructures after long time periods when a strong flow is applied. These structures are directly compared, from a qualitative point of view, with the corresponding experimental results and differences between the equilibrium and non-equilibrium phase diagrams are highlighted, proving the capability of detecting morphological changes caused by deformation in both experiments and DPD simulations. The effect of temperature on the rheology of the systems has been eventually investigated and compared with the already existing non-rheological phase diagram.

Dissipative particle dynamics simulations of tri-block co-polymer and water: Phase diagram validation and microstructure identification.

In this study, the phase diagram of Pluronic L64 and water is simulated via dissipative particle dynamics (DPD). The peculiar structures that form when the concentration varies from dilute to dense (i.e., spherical and rod-like micelles, hexagonal and lamellar phases, as well as reverse micelles) are recognized, and predictions are found to be in good agreement with experiments. A novel clustering algorithm is used to identify the structures formed, characterize them in terms of radius of gyration and aggregation number and cluster mass distributions. Non-equilibrium simulations are also performed, in order to predict how structures are affected by shear, both via qualitative and quantitative analyses. Despite the well-known scaling problem that results in unrealistic shear rates in real units, results show that non-Newtonian behaviors can be predicted by DPD and associated with variations of the observed microstructures.