All-atom and Coarse-grained Molecular Dynamics Modeling of Various Polymeric and Composite Materials

Abstract

This dissertation leverages molecular dynamics (MD) simulations to reveal the structure-property relationship of various polymeric and composite materials, including polyacrylonitrile-poly(methyl methacrylate) (PAN-b-PMMA) copolymers, polyetherimide (PEI)-graphene composites, and epoxy network polymers, by bridging molecular-level behaviors and macroscopic thermomechanical properties. First, all-atom MD simulations are used to improve the design of porous carbon fibers derived from PAN-b-PMMA copolymers for energy storage applications. A new method is developed to characterize the interfacial area between different domains. Simulation results reveal a molecular mechanism underlying the experimental findings, demonstrating that the interfacial area -- a key predictor of the electrochemical performance of the resulting fibers after oxidation and carbonization -- reaches a maximal value when the two blocks are at a 50% volume fraction. This understanding paves the way for designing PCFs with optimal energy storage capabilities. Next, all-atom MD simulations are used to explore a strategy to enhance polymer nanocomposites by mitigating nanofiller aggregation. Experiments show that coating the surface of reduced graphene oxide (rGO) nanoparticles with PEI chains can improve their dispersion in a PEI matrix and thus lead to stronger composites. Simulations reveal that the PEI chains grafted to the edge surface a rGO particle form a protective layer of the particle, preventing particle aggregation and creating a more compatible interface with the host polymer. This enhanced compatibility makes the composites perform more strongly under mechanical loading, as seen experimentally. Polymer grafting is therefore confirmed as a powerful strategy for creating stronger, more reliable composite materials. Finally, a computationally efficient coarse-grained (CG) model is developed for epoxy resins based on EPON 862 (Diglycidyl Ether of Bisphenol F) monomers and diethyltoluenediamine (DETDA) curing agent, a critical component of high-performance composite materials. The CG model is transferable across a wide range of temperatures and is used to predict the mechanical properties of epoxy resins with reasonable accuracy. It provides a facile approach to creating large epoxy networks. Then via a backmapping procedure, the CG network is mapped to an all-atom network with the same topology. The all-atom and CG networks are used for understanding the fracture behavior of epoxy resins at experimentally relevant spatiotemporal scales. Collectively, this dissertation provides a suite of validated computational tools and fundamental molecular insights to advance the bottom-up design and optimization of next-generation polymeric and composite materials.