Inherited control of crystal surface reactivity

Abstract

Material and environmental sciences have a keen interest in the correct prediction of material release as a result of fluid-solid interaction. For crystalline materials, surface reactivity exerts fundamental control on dissolution reactions; however, it is continuously changing during reactions and governs the dynamics of porosity evolution. Thus, surface area and topography data are required as input parameters in reactive transport models that deal with challenges such as corrosion, CO2 sequestration, and extraction of thermal energy. Consequently, the analysis of surface reaction kinetics and material release is a key to understanding the evolution of dissolution-driven surface roughness and topography. Kinetic Monte Carlo (KMC) methods simulate such dynamic systems. Here we apply these techniques to study the evolution of reaction rates and surface topography in crystalline materials. The model system consists of domains with alternating reactivity, implemented by low vs. high defect densities.Our results indicate complex and dynamic feedbacks between domains of high versus low defect density, with the latter apparently limiting the overall dissolution rate of the former - a limitation that prevails even after their disappearance. We introduce the concept of “inherited” control, consistent with our observation that maximum dissolution rates in high defect density domains are lower than they would be in the absence of low defect density neighboring domains.The controlling factor is the spatial pattern of surface accessibility of fluids. Thus, the distribution of large etch pits centers is inherited almost independently of spatial contrasts in crystal defect density during ongoing reactions. As a critical consequence, the prediction of both the material flux from the reacting surface and the evolution of topography patterns in crystalline material is constrained by the reaction history. Important applications include the controlled inhibition of reactivity of crystalline materials as well as the quantitative evaluation and prediction of material failure in corrosive environments.