Grants and Contributions:

Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023)

This proposed research program is part of the ongoing research that the applicant is pursuing on phase separation (spinodal decomposition) in polymer solutions and blends through mathematical modeling and computer simulation. Applications of phase separated polymer solutions and blends are found in: (1) polymeric membranes for separation processes, (2) polymer dispersed liquid crystal films for electro-optical devices and smart windows, (3) engineering polymer composite materials for purposes that require superior mechanical properties, and (4) polymeric microelectronic circuits and resists. The overall objective of this proposed research program is to develop a fundamental understanding of the morphological evolution of polymer solutions and blends undergoing phase separation (spinodal decomposition) to fabricate functional polymeric materials. The specific objectives are of this research proposal: (1) to model, simulate and characterize the morphology of polymer solutions and blends undergoing surface-induced phase separation in the presence of temperature and concentration gradients, (2) to model, simulate and characterize the morphology of polymer solutions and blends undergoing sequential quenching into the metastable and unstable regions of the phase diagram, and (3) to model, simulate and characterize the morphology of polymer solutions and blends undergoing pressure-induced phase separation in the presence of temperature and concentration gradients. Temperature and concentration gradients typically occur during polymer solutions and blends processing to fabricate functional polymeric materials.

The model will consist of the Cahn-Hilliard theory for phase separation and Flory-Huggins-de Gennes theory for polymer thermodynamics. The model will be solved using the finite difference and Galerkin finite element methods. The numerical results will be processed using scientific visualization software so that the models and numerical results can be validated with published experimental results. The morphology will be characterized by computing the structure factor and using scientific visualization in conjunction with digital image analysis.