Monodisperse model to predict the growth of inorganic nanostructured particles in supercritical fluids through a coalescence and aggregation mechanism

Today material processing in supercritical fluids represents one of the main applications of the supercritical fluid technology within the Nanoscience and Nanotechnology research activities. A wide range of materials can be produced from organic to inorganic NPs with a fine control of their characteristics playing with the process operating parameters. However, there is a crucial need of numerical tools to develop the material processing technology in supercritical fluids at a larger scale. s particularly the case for the growth of inorganic NPs with processes based on a chemical transformation in supercritical fluids. This paper is focused on the development and validation of a monodisperse model that predicts the growth of inorganic nanostructured particles through a two steps mechanism: coalescence and aggregation. This model can predict the evolution of particle size as a function of the process operating parameters. The numerical tool is validated with the growth of nanostructured copper metal particles in a supercritical CO2/EtOH mixture.