Prediction and manipulation of drop size distribution of emulsions using population balance equation models for high-pressure homogenization

Emulsions constitute a wide range of natural as well as processed products. Pharmaceutical applications of emulsions include oral administration, parenteral delivery, ophthalmic medicine, topical and transdermal creams, and fluorocarbon-in-water emulsions for blood oxygenation. In the foods area many of the products like mayonnaise, margarine, ice-creams are emulsions by nature and some products can also be used for delivery of active ingredients (e.g. nutraceuticals) with potential health benefits. Emulsions are also encountered at many stages of petroleum recovery, transportation, and processing. Typically, emulsions are manufactured in a two-step process. First a coarse emulsion called a premix is made which is passed through a high-pressure homogenizer. Intense energy supplied in the high pressure homogenizer causes breakage of the coarse emulsion to a fine one with a tighter distribution. Population balance equation (PBE) models are useful for emulsions since they allow prediction of the evolution of the drop size distribution on specification of the two rate processes i.e., breakage of drops due to the flow field and coalescence of colliding drops. In our work, we developed a PBE model to describe emulsion breakage in a high pressure homogenizer. The focus of the work was breakage and conditions to keep coalescence to minimum were implemented. Two breakage rates representing two mechanisms i.e., turbulent inertial and turbulent viscous breakage were necessary for reproducing the bimodal nature of the distributions. We used mechanistic functions in the PBE model to develop a predictive model which could be extended to changes in formulation variables as well as process variables. Starting with the assumption of binary breakage, the model was refined to include multiple drop breakage. The developed model was found to be extensible to reasonable changes in oil concentration, surfactant concentration, continuous phase viscosity and constant ratio of oil to surfactant. Anomalies in pressure prediction encountered earlier were also corrected for by including some additional features like heating, maximum stable diameter, and number of daughter drops. A preliminary attempt was also made to use the developed model for designing experiments for making target emulsions with pre-specified properties