A rheological phase diagram of aqueous solutions based on Pluronic L64 was experimentally evaluated and validated via DPD simulations.

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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.

Summary This study is aimed to formulate a numerical modeling recipe for polyurethane foams. The model is capable of simulating the foam principal characteristics during mold filling. The model is formulated upon coupling of Computational Fluid Dynamics (CFD) and Population Balance Equation (PBE) to predict and simulate the evolution of foam features including apparent density and viscosity, bubble (or cell) size distribution (BSD) during the polymerization, as well as its kinetics. The solution of PBE inside the CFD code is performed with Quadrature Method of Moments (QMOM). The foam, constituted by a liquid polymer and gas bubbles, is simulated as a pseudo‐single‐phase system, while the interface between the foam and the surrounding air is tracked by a Volume‐of‐Fluid (VOF) solver within the open‐source CFD code OpenFOAM. The modeling is applied for a simple foaming experiment and attention is paid to the effect of the rheological model on the predictions.