Pridicting catastrophic phase inversion in emulsion

XI+254hlm.;24c

Predicting Catastrophic Phase Inversion on the Basis of Droplet Coalescence Kinetics

A predictive model for catastrophic phase inversion, based on the kinetics of droplet breakup and coalescence, is presented here. Two inversion mechanisms can be distinguished, depending on the direction of the phase inversion process. With the surfactant predominantly present in the dispersed phase, the coalescence rate is high and "easy" phase inversion takes place at relatively low volume fractions. Going in the other direction, surfactant is predominantly present in the continuous phase. The coalescence rate is dramatically lowered because of the Gibbs-Marangoni effect, and "difficult" inversion will not take place up to relatively high volume fractions. Experiments were carried out in a stirred vessel, where phase inversion was detected by a jump in emulsion conductivity. Easy inversion points were found on the order of 20-50% volume fraction of the dispersed phase. Difficult inversion was not detected up to 97% dispersed phase. The easy inversion point increases with dispersed phase addition rate and is independent of the stirrer speed below a stirrer speed of 1500 rpm. A simple model based on the breakup and coalescence rate of emulsion droplets in the easy inversion regime allows us to calculate the stationary droplet size as a function of the volume fraction of the dispersed phase, as well as the evolution of the droplet size in time under addition of dispersed phase. The stationary droplet size diverges above a critical volume fraction of 26.4%, indicating phase inversion. This model can qualitatively describe hysteresis and the phase inversion point dependence on stirrer speed and dispersed phase addition rate, as found in our experiments

Predicting Catastrophic Phase Inversion on the Basis of Droplet Coalescence Kinetics

A predictive model for catastrophic phase inversion, based on the kinetics of droplet breakup and coalescence, is presented here. Two inversion mechanisms can be distinguished, depending on the direction of the phase inversion process. With the surfactant predominantly present in the dispersed phase, the coalescence rate is high and "easy" phase inversion takes place at relatively low volume fractions. Going in the other direction, surfactant is predominantly present in the continuous phase. The coalescence rate is dramatically lowered because of the Gibbs-Marangoni effect, and "difficult" inversion will not take place up to relatively high volume fractions. Experiments were carried out in a stirred vessel, where phase inversion was detected by a jump in emulsion conductivity. Easy inversion points were found on the order of 20-50% volume fraction of the dispersed phase. Difficult inversion was not detected up to 97% dispersed phase. The easy inversion point increases with dispersed phase addition rate and is independent of the stirrer speed below a stirrer speed of 1500 rpm. A simple model based on the breakup and coalescence rate of emulsion droplets in the easy inversion regime allows us to calculate the stationary droplet size as a function of the volume fraction of the dispersed phase, as well as the evolution of the droplet size in time under addition of dispersed phase. The stationary droplet size diverges above a critical volume fraction of 26.4%, indicating phase inversion. This model can qualitatively describe hysteresis and the phase inversion point dependence on stirrer speed and dispersed phase addition rate, as found in our experiments

Prediction of emulsion particle sizes using a computational fluid dynamics approach

For many food products emulsification processes play an important role. Examples are ice cream, spreads, sauces, etc. As is well known, droplet break-up and coalescence phenomena are the local processes underlying the control of particle size in an emulsion process. Quite a number of studies have generated scaling laws which can be easily applied and which are useful in the design of a process. However, the prediction of particle sizes in an inhomogeneous flow, where the flow velocity is changing spatially in strength and direction and with time, is not yet well established. For one-phase flows computational fluid dynamics (CFD) methodologies are in use to predict details on the flow with quite some success. This methodology has been extended to capture the dispersed phase in an efficient way. The essence is that break-up and coalescence processes determine source terms in a transport equation for the moments of the particle size distribution, while velocity vectors as obtained in the one-phase CFD simulation determine the convective term. This method allows particle size prediction in any equipment. The approach is illustrated for the particle size evolution of an oil-in-water emulsion, for a phase-separated biopolymeric mixture (a so-called water-in-water emulsion) and for the escape of the included oil droplets from a double emulsion of the type oil-in-water-in-oil. In all cases experimental results are compared with simulation results, which match very well. This shows the strength of the method