Relaxation in nuclear magnetic resonance is a powerful method for obtaining spatially resolved, timescale-specific dynamics information about molecular systems. However, dynamics in biomolecular systems are generally too complex to be fully characterized based on NMR data alone. This is a familiar problem, addressed by the Lipari-Szabo model-free analysis, a method that captures the full information content of NMR relaxation data in case all internal motion of a molecule in solution is sufficiently fast. We investigate model-free analysis, as well as several other approaches, and find that model-free, spectral density mapping, LeMaster’s approach, and our detector analysis form a class of analysis methods, for which behavior of the fitted parameters has a well-defined relationship to the distribution of correlation times of motion, independent of the specific form of that distribution. In a sense, they are all “model-free.” Of these methods, only detectors are generally applicable to solid-state NMR relaxation data. We further discuss how detectors may be used for comparison of experimental data to data extracted from molecular dynamics simulation, and how simulation may be used to extract details of the dynamics that are not accessible via NMR, where detector analysis can be used to connect those details to experiments. We expect that combined methodology can eventually provide enough insight into complex dynamics to provide highly accurate models of motion, thus lending deeper insight into the nature of biomolecular dynamics.

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<p>Granular systems are ensembles of inelastic particles which dissipate energy during collisions. Granular systems serve as excellent models for a wide variety of materials such as sand, soils, corn, and powder. A rather remarkable property of granular systems is when excited, whether due to an interstitial fluid or via the boundaries, the granular particlesdisplay fluid-like behavior. As a result, there has been decades of granular research with the overarching goal of formulating a general granular hydrodynamic theory.</p> <p>However, the granular hydrodynamic theory is limited, and the underlying transport coefficients often require modifications which are based on empirical observations, and assuch, are system-specific. It is ideally better to devise a general theory which minimizes the information needed about the systema priori. The main thrust of the work undertaken shown here strives to develop such a model by using kinetic theory as the basis. More specifically, I investigate granular gases via the direct simulation Monte Carlo (DSMC) methodand modify the governing equations. In this thesis, two idealized cases of granular gases areconsidered: the homogeneous cooling state and a boundary-heated gas (or the pure conduc-tion case). In the former, the effects of polydispersity are probed. In the latter, the evolutionof the local hydrodynamics due to strong rarefaction effects are divulged. Additionally, amodified, more generalized constitutive relation for the heat flux is proposed and comparedwith DSMC results. Extensions of the DSMC method for dense granular gases and granulargases composed of non-spherical particles are also discussed.</p>

It remains a major challenge in biophysics to understand the conformational dynamics of biomolecules. As powerful tools, molecular dynamics (MD) simulations have become increasingly important in studying the full atomic details of conformational dynamics of biomolecules. In addition, many statistical models have been developed to give insight into the big datasets from MD simulations. In this work, I first describe three statistical models used to analyze MD simulation data: Lifson-Roig Helix-Coil theory, Bayesian inference models, and Markov state models. Then I present the applications of each model in analyzing MD simulations and revealing insight into the conformational dynamics of biomolecules. These statistical models allow us to bridge microscopic and macroscopic mechanisms of biological processes and connect simulations with experiments. / Chemistry

Multicomponent high-entropy and amorphous alloys represent relatively new classes of structural materials with complex atomic configurations and exceptional mechanical properties. However, there are several knowledge gaps in the relationships between their atomic structure and mechanical properties. Understanding these critical relationships will enable novel alloy design and tailoring of their mechanical properties for desired engineering applications. In this dissertation, first-principles calculations and molecular dynamics simulations are applied to investigate the local atomic configurations and ordering in high-entropy and amorphous alloys. Our findings suggest that fluctuations in local atomic configurations for high- entropy alloys result in significant changes in stacking fault energy, twin energy, dislocation behavior, dislocation-twin interactions, and critical shear stress. For amorphous alloys or metallic glasses, the short-range order (SRO) and medium-range order (MRO) were found to play decisive roles in determination of their mechanical properties. Structural relaxation was found to lead to shear localization, which was attributed to free volume change and evolution of SRO and MRO to more brittle nature. In contrast, rejuvenated metallic glasses had relatively large and uniform free volume distribution giving rise to homogeneous flow and increased plasticity.

The research reported in this dissertation focuses on the response of grain boundaries in polycrystalline metallic nanostructures to applied strain using molecular dynamics simulations and empirical interatomic force laws. The specific goals of the work include establishing how local grain boundary structure affects deformation behavior through the quantitative estimation of various plasticity mechanisms, such as dislocation emission and grain boundary sliding. The effects of strain rate and temperature on the plastic deformation process were also investigated. To achieve this, molecular dynamics simulations were performed on both thin-film and quasi-2D virtual samples constructed using a Voronoi tessellation technique. The samples were subjected to virtual mechanical testing using uniaxial strain at strain rates ranging from 105s-1 to 109s-1. Seven different interatomic embedded atom method potentials were used in this work. The model potentials describe different metals with fcc or bcc crystal structures. The model was validated against experimental results from studying the tensile deformation of irradiated austenitic stainless steels performed by collaborators at the University of Michigan. The results from the model validation include a novel technique for detecting strain localization through adherence of gold nanoparticles to the surface of an experimental sample prior to deformation. Similar trends with respect to intergranular crack initiation were observed between the model and the experiments. Simulations of deformation in the virtual samples revealed for the first time that equilibrium grain boundary structures can be non-planar for model potentials representing fcc materials with low stacking fault energy. Non-planar grain boundary features promote dislocation as deformation mechanisms, and hinder grain boundary sliding. This dissertation also reports the effects of temperature and strain rate on deformation behavior and correlates specific deformation mechanisms that originate from grain boundaries with controlling material properties, deformation temperature and strain rate. / Ph. D.

No / Review article. No abstract.