Title: Bridging Length Scales in Complex Soft Matter Formulations using Integrated Particle and Field-Theoretic Simulations
Abstract: Cosmetics, shampoos, lubricants, detergents, drug delivery, pesticides, ceramics, coatings, among many more, are all examples of complex soft matter formulations comprised of a multitude of (macro)molecular ingredients: ions, solvents, surfactants, polymers, biologics, and colloids. Critically, the design landscape in these formulations is formidable with a nearly limitless number of options: polymer architecture, chemistry, molecular weight; solvent chemistry; ionic or nonionic surfactants; colloid chemistry, size, and shape; temperature, pressure, pH, and ionic strength. Each design decision has molecular-scale implications that influence the formulation’s macroscopic properties, such as rheology, microstructure, foaming, phase behavior, ductility, etc. However, connecting (macro)molecular chemistry and architecture to bulk material properties is a significant challenge in computational soft matter, which is hampering our ability to explore in silico the formulation design space.
In this dissertation, we outline a systematic computational framework to overcome the challenges inherent to soft matter by utilizing all-atom molecular dynamics simulations to molecularly-inform mesoscale field theories. We leverage the strengths of both particle and field representations, enabling the investigation of equilibrium properties and phase behavior in complex soft matter formulations while maintaining a direct connection to the underlying molecular-scale chemistry. Relative entropy coarse-graining is our causeway between particles and fields, which is an information-theoretic framework to systematic, bottom-up coarse-graining. Furthermore, we detail how molecularly-informed field theories can generate effective-colloidal interactions in complex macromolecular solutions, whereby molecular-scale chemistry is systematically connected to the collective behavior of colloidal assembly and phase behavior.
Overall, a computational workflow is outlined which enables extensive and rapid computational exploration of the soft matter formulation design landscape at varying resolutions. The aim is to equip the synthetic chemist and material scientist with a tool capable of accelerating the discovery of next-generation materials that are sustainable economically, environmentally, and socially
Chairs: Professors Glenn Fredrickson and Scott Shell