Thesis (M.Eng.)--University of Wollongong, 2005. / Typescript. Includes bibliographical references: leaf 113-121.

Thesis (Ph. D.)--University of Missouri-Columbia, 1998. / Typescript. Vita. Includes bibliographical references (leaves 139-150). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1998. / Typescript. Vita. Includes bibliographical references (leaves 139-150). Also available on the Internet.

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2004. / Includes bibliographical references. Also available in electronic version.

Thesis (Ph.D.) - University of Queensland, 2003. / Includes bibliography.

Rotational-translational decoupling, in which translational motion is apparently enhanced overrotational motion in violation of Debye-Stokes-Einstein predictions, has been observed in a wide variety of materials near their glass transition temperatures (Tg). This has been posited to result from ensemble averaging in the context of dynamic heterogeneity. In this thesis, single fluorescent probe molecules are tracked rotationally and translationally to interrogate this explanation. In one study, ensemble and single molecule experiments are performed in parallel on the ideal fluorescent probe N,N’-dipentyl-3,4,9,10-perylenedicarboximide (pPDI) in high molecular weight polystyrene near its Tg. Ensemble results show decoupling onset at approximately 1.15Tg, increasing to over three orders of magnitude at Tg. Single molecule measurements also show a high degree of decoupling, with typical molecules at Tg showing translational diffusion coefficients nearly 400 times higher than expected from Debye-Stokes-Einstein predictions. The same experiments were performed on a microscope with somewhat lower spatial resolution to investigate the role of localization accuracy in apparent degree of breakdown. Here similar, though slightly larger, degrees of breakdown were found, consistent with the idea that averaging across heterogeneous regions, even within a single molecule’s trajectory, is the primary driver of rotational-translational breakdown, while the lower degree of localization accuracy of the microscope additionally leads to some sub-ensemble selection that further inflates apparent breakdown. Across all single molecule experiments, higher degree of breakdown is associated with particularly mobile molecules and anisotropic trajectories, providing support for anomalous diffusion as a critical driver of rotational-translational decoupling and Debye-Stokes-Einstein breakdown. In a final study, single molecule translational simulations are performed with varying types (spatial and dynamical) and degrees of heterogeneity to assist in interpreting results of single molecule translation experiments. These reveal that fast portions of translational trajectories inflate diffusion coefficients and that, taken together with experimental results, the majority of rotational- translational decoupling in glassy systems occurs through dynamic exchange consistent with wide underlying distributions of diffusion coefficients and exchange coupled to local spatiotemporal dynamics.

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Polyetherimides are an important class of engineering thermoplastics used in a broad range of industries and applications because of their high heat resistance and stability, high strength and moduli, excellent electrical properties over a wide range of temperatures and frequencies, good processability, good adhesive properties, and chemical stability. All-atom molecular dynamics (MD) simulation is a useful tool to study polymers, but the accessible length and time scales are limited. In this thesis, we explore several computational methods that go beyond all-atom MD simulations to investigate polyetherimides. First, we have developed a transferable coarse-grained MD model of polyetherimides that captures their mechanical and thermal expansion properties. Our results show that in order to make the model transferable, it is critical to include an entropic correction term in the coarse-grained force field and require the coarse-grained model to capture the thermal expansion property of polyetherimides. Secondly, we have constructed a predictive model of the glass transition temperature (Tg) for polyimides by using machine-learning algorithms to analyze existing data on Tg reported in the literature. The predictive model is validated by comparing its predictions to experimental data not used in the training process of the model. We further demonstrate that the diffusion coefficients of small gas molecules can be quickly computed with all-atom MD simulations and used to determine Tg. Finally, we have developed a Monte Carlo (MC) program to model the polymerization process of branched polyetherimides and to compute their molecular weight distribution for a wide range of systems, including fully reacted, partially reacted, stoichiometric, and nonstoichiometric ones. The MC results are compared to the predictions of the Flory-Stockmayer theory of branched polymers and an excellent agreement is found below the gel point of the system under consideration. Above the gel point, the Flory- Stockmayer theory starts to fail but the MC method can still be used to quickly determine the molecular weight distribution of branched polyetherimides under very general conditions. / Doctor of Philosophy / Polyetherimides are an important category of engineering plastics with wide applications in many fields because of their superior mechanical, thermal, chemical, and electrical properties. All-atom molecular dynamics simulations serve as a useful tool to study the properties of polyetherimides in silico. However, such simulations are computationally expensive and therefore limited to small system sizes and short time scales. To overcome these issues, we employed various computational techniques in this thesis to model polyetherimides. First, we have developed a coarse-grained model of polyetherimides where atoms are grouped into beads. We show that molecular dynamics simulations on the basis of the coarse-grained model can be used to provide a reasonable description of the mechanical and thermal expansion properties of polyetherimides. Secondly, we have constructed a predictive model of the glass transition temperature, which is the temperature at which a material enters a glassy state when cooled rapidly, of polyimides using machine-learning algorithms. This model is capable of estimating the glass transition temperature of polyimides within an accuracy of ± 15 K even for those not synthesized yet. We further show that the diffusion coefficients of gas molecules, in addition to the polymer density, can be computed accurately with all-atom molecular dynamics simulations and used to determine the glass transition temperature of polyimides. Finally, we have developed a Monte Carlo scheme to efficiently model the polymerization and compute the chain-length distribution of branched polyetherimides under very general conditions. The results from Monte Carlo simulations are compared to the predictions of the Flory-Stockmayer theory of branched polymers. The range of applicability of the theory is revealed. Overall, we have demonstrated several computational techniques that can be used to efficiently model polyetherimides, potentially other polymers as well, beyond the widely-used all-atom molecular dynamics simulations.

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