Crystal Dissolution Kinetics Studied by a Combination of Monte Carlo and Voronoi Methods

KIMERA: A Kinetic Montecarlo Code for Mineral Dissolution

KIMERA is a scientific tool for the study of mineral dissolution. It implements a reversible Kinetic Monte Carlo (KMC) method to study the time evolution of a dissolving system, obtaining the dissolution rate and information about the atomic scale dissolution mechanisms. KIMERA allows to define the dissolution process in multiple ways, using a wide diversity of event types to mimic the dissolution reactions, and define the mineral structure in great detail, including topographic defects, dislocations, and point defects. Therefore, KIMERA ensures to perform numerous studies with great versatility. In addition, it offers a good performance thanks to its parallelization and efficient algorithms within the KMC method. In this manuscript, we present the code features and show some examples of its capabilities. KIMERA is controllable via user commands, it is written in object-oriented C++, and it is distributed as open-source software.

A Statistical Approach for Analysis of Dissolution Rates Including Surface Morphology

Understanding mineral dissolution is relevant for natural and industrial processes that involve the interaction of crystalline solids and fluids. The dissolution of slow dissolving minerals is typically surface controlled as opposed to diffusion/transport controlled. At these conditions, the dissolution rate is no longer constant in time or space, an outcome observed in rate maps and correspondent rate spectra. The contribution and statistical prevalence of different dissolution mechanisms is not known. Aiming to contribute to close this gap, we present a statistical analysis of the variability of calcite dissolution rates at the nano- to micrometer scale. A calcite-cemented sandstone was used to perform flow experiments. Dissolution of the calcite-filled rock pores was measured using vertical scanning interferometry. The resultant types of surface morphologies influenced the outcome of dissolution. We provide a statistical description of these morphologies and show their temporal evolution as an alternative to the lack of rate spatial variability in rate constants. Crystal size impacts dissolution rates most probably due to the contribution of the crystal edges. We propose a new methodology to analyze the highest rates (tales of rate spectra) that represent the formation of deeper etch pits. These results have application to the parametrization and upscaling of geochemical kinetic models, the characterization of industrial solid materials and the fundamental understanding of crystal dissolution.