Model validation for precipitation in solvent-displacement processes

In this work a model for precipitation in solvent-displacement processes is presented and validated. The model is based on computational fluid dynamics and makes use of the Reynolds-averaged Navier-Stokes approach. The standard k-epsilon turbulence model in combination with the enhanced wall treatment approach is used to describe mixing and particle formation in a confined impinging jets reactor. The interaction between turbulent fluctuations and particle formation (i.e., micro-mixing) is modeled with the so-called direct quadrature method of moments coupled with the interaction and exchange with the mean approach, whereas the population balance model is solved by using the quadrature method of moments. The model is validated against comparison with experiments relative to the precipitation of polymer nanoparticles of polycaprolactone via solvent-displacement with acetone and water as solvent and anti-solvent. Particle formation is described with the classical nucleation, molecular growth and aggregation steps. The relevant rates are derived from first principles and most of the parameters appearing in the model are identified through independent measurements or from theory. Results show good agreement with experimental data and prove that the approach is very interesting and is now ready to be used also for other particulate systems. Alternative strategies to assess the value of some missing model parameters via multi-scale modeling are also discussed.