Effect of precipitation chamber geometry on the production of microparticles by antisolvent process

• Published in: The Journal of supercritical fluids 2018-03, Vol.133, p.357-366
• Main Authors: Cardoso, F.A.R., Rezende, R.V.P., Almeida, R.A., Meier, H.F., Cardozo-Filho, L.
• Format: Article
• Language: English
• Subjects: Antisolvent process; Computational fluid dynamics; Microparticle size distribution; Population balance equation
• ISSN: 0896-8446; 1872-8162
• DOI: 10.1016/j.supflu.2017.09.015

[Display omitted] •An effective 3D CFD-PBE model is proposed to analyze the antisolvent process.•Changes in transport parameters are accounted for through a set of closure models.•The flow field behavior influences the particle size distribution.•Low computational effort required to deal with particle size distribution.•Scale-up criterion application. Supercritical antisolvent processes (SAS and SEDS) are employed for the precipitation of the microparticles/nanoparticles of a wide variety of pharmaceutical and food compounds under supercritical conditions. The scalability of this effective method for the production of microparticles and nanoparticles still represents technological challenge due to the large number of operational parameters involved in the production of particles under supercritical conditions. A computational fluid dynamics (CFD) model coupled to a population balance equation (PBE) has been shown to be an efficient approach to gaining a better understanding of the production of microparticles and nanoparticles through the supercritical antisolvent method. In this study, taking into account the non-ideal behavior of CO2 under supercritical conditions, the influence of the precipitation chamber volume on the precipitated PHBV particle size was evaluated applying CFD-based modeling coupled with PBE and using experimental data from the literature obtained with chambers with different geometries. The physical properties (density, thermal conductivity, viscosity and mass diffusivity) were calculated through Peng-Robinson’s equation of state (EOS) and the squared mixing rule of the Van der Walls, Chung and Riazi and Whitson methods, respectively. Simulations carried out at a pressure of 85bar and temperature of 313K. The model was able to predict the mean PHBV nanoparticle diameter with an error of 7%. A geometry with a larger axial length and smaller chamber diameter led to larger particles being precipitated due to the flow pattern promoted by the jet interaction.