Luttge, Andreas2014-09-162014-09-162013-122013-08-14December 2Kurganskaya, Inna. "A multi-scale approach to study silicate dissolution: Kinetic Monte Carlo simulations and experimental observations." (2013) Diss., Rice University. <a href="https://hdl.handle.net/1911/77190">https://hdl.handle.net/1911/77190</a>.https://hdl.handle.net/1911/77190Dissolution of silicate minerals is an important part of many geological processes taking place on Earth’s surface as well as in the deep crust. Weathering of rocks and soil formation, metasomatic rock alteration by hydrothermal fluids, and diagenetic transformation of sediments are controlled by dissolution reactions. Secondary pore space of natural reservoirs can be significantly altered by dissolution and the subsequent precipitation of clay minerals. As a consequence, the potential storage capacity of natural fuels, carbon dioxide, or radioactive waste, can be affected. In addition, the stability of rocks hosting potentially hazardous materials largely depends on their dissolution rates. The development of computational ab initio and Molecular Dynamics techniques drives the interest to study dissolution reactions at the molecular scale. At the same time, advanced microscopic techniques allow us to study dissolution process at the nm to micron scale and investigate spatio-temporal variations of surface reactivity. The combination of these methods has great potential for tackling fundamental questions of the mechanisms of mineral dissolution. My thesis work presents an integrated multiscale approach to studying the dissolution of silicates. The work consists of three main parts: experimental studies of the dissolving mineral surface at the micron scale, Kinetic Monte Carlo (KMC) simulations at the nanometer scale, and the parametrization of KMC models by ab initio derived activation energies. Muscovite mica and quartz were chosen as template study objects. These two minerals represent “2-dimentional” (phyllosilicates) and 3-dimentional (tectosilicates) crystal structures of silicates as well as “complex” and “simple” chemical bond networks. The first part of my muscovite dissolution studies is based on experimental observations of the reacted surface with vertical scanning interferometry. We quantified the distribution of surface reactivity in terms of surface roughness and mean height levels and also measured the dissolution rate. Additional investigations of the detailed surface structure were done by using atomic force microscopy. KMC simulations of muscovite dissolution constitute the second part of this work. We developed KMC models that simulate the dissolution of mica structures. We varied the number of the basic reaction types in the system and achieved a satisfying match between modeling results and experimental observations. Also, we showed how KMC methods can be used as a tool for testing my hypotheses regarding the role of surface reactions on the overall reaction mechanism. The third part of the work is dedicated to the problems of complexity and parametrization of KMC models. Here, we present four KMC models of quartz dissolution that vary by their complexity level. The capabilities of the models to predict experimentally observed dissolution features were shown for prism, rhombohedral, and pinacoid quartz faces. The simulation results demonstrate the role of the topological state in the recognition of key surface sites. From this study we derived basic dissolution mechanisms for the three faces.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.Mineral dissolutionDissolution kineticsCrystal dissolutionKinetic Monte CarloMonte CarloStochastic simulationsSilicatesComputer simulationsMultiscaleVSIOptical InterferometrySurface roughnessDissolution rateSheet silicatesPhyllosilicatesMicaQuartzMuscoviteSurface topographySurface reactivitySite topologyStepwave modelKinematic stepwaveEtch pitEtch hillockMica edgeCrystallographic controlModel complexityModel parameterizationGeochemistryThesis2014-09-16