(148z) Modelling of Nanocapsules Formation: Phase Separation during Mass Transfer Processes | AIChE

(148z) Modelling of Nanocapsules Formation: Phase Separation during Mass Transfer Processes

Authors 

Maria, H. - Presenter, Laboratoire de Génie des Procédés et d'Automatique
le Gorrec, Y., Laboratoire de Génie des Procédés et d'Automatique
Jallut, C., Laboratoire de Génie des Procédés et d'Automatique
Couenne, F., Laboratoire de Génie des Procédés et d'Automatique
Tayakout, M., Laboratoire de Génie des Procédés et d'Automatique


Recently, a large field of industrial applications, principally in the pharmaceutical industry, uses the micro-encapsulation (nano-encapsulation) of solid or liquid by polymer coating. Indeed, this process is considered as an excellent technique for the controlled release of drugs.

To get a better understanding of this process we propose a mathematical model able to describe the formation of nanocapsules by emulsion-diffusion method.

Initial works on nano-encapsulation by emulsion diffusion technique, have shown this process involves the emulsification of a partially water-miscible solvent (previously saturated with water) containing the polymer and oil, in an aqueous phase (previously saturated with the solvent) containing a stabilizer. The subsequent addition of a large volume of water to the system causes the solvent diffusion into the external phase, inducing the polymer's deposition around the droplets and then the formation of the nanocapsules. Indeed, the nanocapsules formation comes from the phase separation due to the solvent displacement; two important phenomena have to be taken into account during this process: mass transport and phase separation.

In this work, we propose a new approach in the modelling of phase separation based on the tangent plane criterion (TPDF). The proposed model is both capable to predict precisely the phase stability and, in the case of instability, to give the exact number of phases. It is based on the expression of a Gibbs excess model representing all the phases supposed to appear during the process.

(TPDF) leads to a highly nonlinear and complex expression to minimize; computations have been done using a global optimization method based on genetic algorithm. Results on phase equilibrium problems show that this model is reliable to find the global minimum for all the cases that we tested. Afterwards this algorithm is coupled with Stephen-Maxwell model to describe the mass transfer process during the nanocapsules formation. Consequently, the proposed model can predict precisely the number of phases as a function of time and space during the diffusion process.

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