Off-campus UMass Amherst users: To download campus access dissertations, please use the following link to log into our proxy server with your UMass Amherst user name and password.

Non-UMass Amherst users: Please talk to your librarian about requesting this dissertation through interlibrary loan.

Dissertations that have an embargo placed on them will not be available to anyone until the embargo expires.

Document Type

Campus-Only Access for Five (5) Years

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Chemical Engineering

Year Degree Awarded

2015

Month Degree Awarded

February

First Advisor

Michael A. Henson

Subject Categories

Food Processing | Process Control and Systems

Abstract

Oil-in-water emulsions are ubiquitous dispersed phase systems with diverse applications in consumer products, processed foods, and the pharmaceutical industry. Emulsion formulation variables and process operating conditions both impact the drop size distribution, a key property that influences emulsion rheology, stability, texture, and appearance. A typical emulsified product requires the drop size distribution to be maintained within acceptable limits. Due to a lack of quantitative understanding, emulsified products are currently manufactured by combining a broad knowledge of previous product formulations with empirical scientific experimentation. An alternative to trial-and-error experimentation is to utilize a suitable mathematical model to predict the drop size distribution. The population balance equation (PBE) modeling framework particularly is well suited for this problem as size distribution dynamics can be captured using mechanistic functions for drop breakage and coalescence phenomena which occur during emulsification. This thesis presents a PBE modeling framework for high intensity emulsification processes including high pressure homogenizers and colloid mills. It is demonstrated that by incorporating coalescence phenomenon into PBE model with only breakage functions significantly improves model predictions of emulsion drop size distributions at high oil-to-surfactant ratios. To make the model more realistic, the effect of surface coverage of surfactant molecules is added to the coalescence function which improves the extensibility of the model over different surfactant types. To extend model predictability over a large range of surfactant and oil concentrations, a new drop breakage model is formulated; and to capture the change in emulsion viscosity due to changes in oil and surfactant concentrations, the PBE model is coupled with an experimentally fitted emulsion viscosity model. Furthermore, it is demonstrated that use of a dynamic surface coverage model over an equilibrium model, improves the predictions of drop size distribution in both “surfactant rich” and “surfactant limited” regimes. In this thesis, the PBE model is also utilized to optimally achieve target emulsion drop size distributions by controlling the number of homogenization passes and the pressure of each pass. The model predictions are successfully validated by performing homogenization experiments using the optimal formulation and homogenization variables. Apart from developing models for the high pressure homogenization, this thesis presents a new model for emulsification in colloid mill obtained by formulating new mechanistic breakage frequency and daughter drop distribution functions. The predictions of the new model are significantly better than predictions obtained using models with conventional daughter drop distribution functions.

Share

COinS