The Dissolution Anisotropy of Pyroxenes: Experimental Validation of a Stochastic Dissolution Model Based on Enstatite Dissolution

摘要

The understanding of the atomic-scale mechanisms controlling silicate dissolution represents a necessary prerequisite for the success of upscaling exercises aimed at predicting the rates of water-silicate interactions over large space and time scales. In that respect, it has been recently shown that physically based stochastic models of crystal dissolution at the atomic scale represent a promising alternative to the conventional treatment of silicate dissolution rates, which consists in using empirical rate laws adjusted to the results of powder dissolution experiments. However, most stochastic simulations conducted so far have been based on simple cubic solid structure, and very few were directed to ascertaining the extent to which the simulation outputs quantitatively compare to experimental measurements. In the present study, we take advantage of the anisotropic crystallographic structure and reactivity of chain silicates (pyroxenes) to tackle this issue. Face-specific enstatite dissolution experiments conducted at pH 0 and 90 degrees C reveal that the face-specific dissolution rates observe the following trend: r((001)) r((210)) > r((010)) >= r((100)). Electron microscopy characterizations additionally show that lenticular etch pits elongated following the c axis grow on (hk0) faces, and that nanometer-thick amorphous Mg-depleted layers cover the reacted enstatite surfaces. A stochastic model was developed, and we show that simulations conducted with bond-breaking probability ratios (and therefore, activation energy differences) that are consistent with the existing literature regarding the hydrolysis of Mg-O-Mg, Mg-O-Si, and Si-O-Si bonds can quantitatively account for the measured dissolution rates. In addition, the lenticular shape, the orientation, and the symmetry of the pits generated numerically on (hk0) faces are also consistent with those observed experimentally, while predicting the formation of Mg-depleted surface layers. As a consequence, this study provides a first milestone to the application of stochastic simulations to investigate the dissolution of pyroxenes.