A Statistical Approach for Analysis of Dissolution Rates Including Surface Morphology

Abstract

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.

Statistical Characterization of Heterogeneous Dissolution Rates of Calcite from In situ and Real-Time AFM Imaging

“…5. These pdfs exhibit common features, which have been detected also in previous studies (Bibi et al 2018;Trindade Pedrosa et al 2019). These include (i) the presence of a dominant peak, eventually accompanied by multiple local peaks and (ii) a positive skewness.…”

“…In this sense, these authors interpret the ensuing frequency distribution of rates as a convolution of modes, each representing a basic kinetic component. This aspect has been further investigated by other studies where rate spectra are extrapolated from (i) AFM in situ imaging of surface topography on dissolving calcite in limestone pores (Levenson and Emmanuel 2013) and dolostone (Emmanuel 2014); (ii) VSI topography data under far-from-equilibrium conditions taken in situ and in real time on the surface of a calcite crystal (Bibi et al 2018) or ex situ on a calcite-cemented sandstone (Trindade Pedrosa et al 2019); and (iii) digital holographic microscopy (DHM) for in situ topography acquisitions on a calcite crystal in contact with deionized water (Brand et al 2017).…”

Generalized Sub‐Gaussian Processes: Theory and Application to Hydrogeological and Geochemical Data

“…With reference to the spatial distribution of surface roughness, these results constitute an important step to bridge across characterizations of reactive phenomena at microscopic and laboratory scales. In this context, there is documented and growing interest in the application of statistical methods (Fischer et al, 2012; Lüttge et al, 2013; Pollet‐Villard, Daval, Ackerer, et al, 2016; Trindade Pedrosa et al, 2019) to firmly ground the multiscale nature of such processes on rigorous theoretical bases. The quality of our results is encouraging to promote further studies targeting statistically based descriptions of the temporal evolution of the surface topography of calcite minerals subject to precipitation/dissolution processes acting at diverse scales.…”

Dissolution of Carbonate Rocks in a Laboratory Setting: Rates and Textures

“…The role that a sample's surface has on the dissolution rates of minerals has been discussed in the literature (e.g., [38][39][40][41][42][43]). The relative importance of modeling dissolution rates assuming an even diffusion boundary layer versus a more complicated surface (often defined by the Brunauer-Emmett-Teller theory (BET)) [40] is poorly constrained [38,39,41].…”