Soft matter approaches as enablers for food macroscale simulation

Abstract

Macroscopic deformable multiphase porous media models have been successful in describing many complex food processes. However, the properties needed for such detailed physics-based models are scarce and consist of primarily empirical models obtained from experiment. Likewise, driving forces such as swelling pressure have also been approached empirically, without physics-based explanations or prediction capabilities. Soft matter based prediction of properties will provide an additional avenue to obtaining properties and also provide a deeper and critical understanding of how these properties change with composition, temperature and other process variables.