title: 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.
authors.affiliation: Riley Robb Hall, Cornell Univ., Ithaca, NY, USA. akdl@cornell.edu
authors.forename: Ashim K
authors.initials: AK
authors.lastname: Datta
authors.forename: Ruud
authors.initials: R
authors.lastname: van der Sman
authors.forename: Tushar
authors.initials: T
authors.lastname: Gulati
authors.forename: Alexander
authors.initials: A
authors.lastname: Warning
mesh_terms: D003198:Computer Simulation; D003890:Desiccation; D005502:Food; D005511:Food Handling; D005612:Freeze Drying; D006813:Humidity; D007700:Kinetics; D008956:Models, Chemical; D016062:Porosity; D013314:Stress, Mechanical; D013816:Thermodynamics; D014867:Water / Q000737:chemistry*
chemical_list: D014867:Water