Nanoparticle processes modelling: The role of key parameters for population balances for on-line crystallization processes applications

The nanoparticle production with well defined properties is of great scientific and technological interest due to the increasing number of applications of such material. Crystallization may be a suitable unit operation for producing nanoparticles, since it may be conceptually designed to be an intensified process. The mean particle size, the particle morphology, the modality and the broadness of the particle size distribution (PSD) are important indications of the quality of a particulate product. By synthesizing nanocrystals with narrow PSD, it is possible to produce advanced nanomaterials with tailored properties. There are possible interaction effects that may be unique to nanoparticles due to the size dependence of properties. These effects must be accounted for in predictive models, which are useful either for exploratory investigations or as a tool for computer operated procedures. For on-line process control, time calculations should not be greater than a few seconds, and, therefore, a population balance model should be more appropriate than stochastic methods. However, at present there is no consensus and complete knowledge by the scientific community of all needed parameters and which are the computer tools for a workable framework for dealing with nanoparticles reliable process design and on-line applications. This paper proposes to discuss important aspects of nanoparticle crystallization processes in order to bring light to nanoparticle modelling. In order to do so, the key factors influencing nanoparticulate processes and how they can be accounted for, going from a molecular to a process engineering approach, are discussed.

This paper proposes to discuss important aspects of nanoparticle crystallization processes in order to bring light to nanoparticle modelling. In order to do so, the key factors influencing nanoparticles processes and how they can be accounted for, going from a molecular to a process engineering approach, are discussed.Figure optionsDownload as PowerPoint slide