UC Santa Barbara

Understanding the solution behavior of complex soft materials is crucial for designing and optimizing formulations that are relevant in everyday consumer products, including processed foods, detergents, hair care products, and various industrial applications such as lubricants, pesticides, and coatings. These formulations are highly multi-component and involve a wide range of charged molecules, such as polyelectrolytes, surfactants, and colloids, often in the presence of salt and other non-ionic (macro)molecules. While experimental investigations provide valuable insights, they are often limited in their ability to directly observe molecular-level interactions and explore the vast design space, encompassing numerous parameters such as composition, specific chemical species, macromolecule architecture, molecular weight, temperature, pH, and more. Computational simulations offer a powerful tool to complement experimental studies, providing a high-throughput screening approach to deepen our understanding of the underlying molecular interactions and the behavior of complex formulations.

In this thesis, we present a multi-scale simulation approach that parameterizes mesoscopic models of the field theory based on information obtained from small-scale atomistic simulations. We employ the relative entropy minimization framework to derive chemically-sensitive coarse-grained interaction parameters from all-atom simulations. Subsequently, we utilize the exact transformation to convert the coarse-grained particle-based model into field-theoretic form, facilitating the prediction of solution phase behavior. The overall workflow preserves the chemical specificity in complex mixtures of interest, enabling de novo studies of solution phase behavior in the field theory without the need for any experimental input.

The simulation framework is highly adaptable and can be applied to investigate a wide range of soft-matter formulations. This thesis focuses on formulations that rely on the complexation of charged macromolecules. The presence of charged assemblies, such as micelles, in typical formulations introduces further complexity, including long-length and time-scale phenomena that are intractable with other high-resolution simulation techniques. Through the exploration of various complex formulations, we demonstrate the predictive capability of this simulation workflow in exploring the thermodynamics and complex structures arising in such formulations. By integrating atomistic and mesoscopic simulation techniques, this work contributes to a fundamental understanding of the underlying mechanisms governing solution behavior in complex formulations. It offers valuable insights for the rational design and optimization of soft matter formulations, thereby contributing to advancements in various industries and sustainable chemical product development.