SUMMARY

The objective of this dissertation is to evaluate the use of high-fidelity material models of polymeric materials for applications in active materials and additive manufacturing settings. Specifically, the problems that will be considered are the dissolution of polymeric materials, material property evolution of photopolymers during curing in digital light processing (DLP) 3D printing, and design of active structures for 4D printing. For the case of dissolution in polymers, a reaction-diffusion model will be presented and its effectiveness at predicting the dissolution process and will be applied to specialty grade as well as industrial thermosetting polymers. In the case of material property evolution of photopolymers in the DLP process a reaction-diffusion model will be presented that can assess the evolution of functional groups at the pixel level and can directly predict thermo-mechanical properties such as the modulus and glass transition temperature. Design of active structures for 4D printing utilizes a thermo-viscoelastic constitutive model coupled with machine learning techniques to determine an ideal material distribution to achieve a pre-defined target shape upon activation from an environmental stimulus.