Kinetic Monte Carlo as a bridge between nano- and macroscales: a case study on dissolution of (Ba,Sr,Ra)SO4 solid solution

Barite (BaSO₄) is a common rock-forming mineral, controlling barium behavior in Earth’s crust and marine water. This mineral can incorporate Sr and Ra into the crystal lattice by forming binary and ternary solid solutions. It makes barite a promising material for use in nuclear storages e.g., for nuclear waste containers. The achievement of high levels of safety in modern nuclear waste deposits requires studies on container’s material-water interaction. The data on solid-liquid interface reactions can be obtained by both experimental and computational methods. The most widespread experimental methods for studying surface reaction kinetics are Atomic Force Microscopy (Putnis, 1995; Bosbach, 1998; Risthaus, 2001; Kuwahara, 2011) and Vertical Scanning Interferometry (Luttge, 2010). However, these methods do not provide information on reaction mechanisms at the molecular scale. Approaches such as Density Functional Theory and Molecular Dynamics give detailed information of the reaction mechanisms at the nano-scale but are limited by the computational costs, system size, and reactions time period (Kurganskaya et al., 2022). Kinetic Monte Carlo is a stochastic approach, which can be successfully used as a connecting link between molecular and macroscopic scales, incorporating both experimental (AFM, VSI) and computational (DFT, MD) data. The KMC model of pure barite dissolution in water was developed by Kurganskaya et al., 2022. We present a new Kinetic Monte Carlo model of mineral-water dissolution in (Ba,Sr,Ra)SO₄ system and discuss the general approaches for KMC models parameterization, based on a crystal chemistry of studied material.

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