Determination of mineral dissolution regimes using flow-through time-resolved analysis (FT-TRA) and numerical simulation

• The use of FT-TRA is explored as a tool to empirically determine mineral dissolution regimes.
• In this proof-of-concept study, calcite and forsterite dissolve under previously reported dissolution regimes.
• Pore-scale modeling is able to reproduce experimental calcite rhomb dissolution results.
• The combined FT-TRA–pore-scale modeling approach provides unprecedented insights into transport controls.

Flow-through time resolved analysis (FT-TRA) involves subjecting small mineral samples (< 10 mg) inserted in a miniature flow-through cell (50 μL) to controlled flows of eluent analyzed on-line by ICP-MS. In this study, FT-TRA is used to empirically determine the dissolution regimes for the two well-studied minerals forsterite and calcite, representing minerals with relatively slow and fast dissolution kinetics. A proportional increase in steady-state effluent [Mg, Si] concentrations with increasing flow-through cell eluent residence times confirms a dominantly surface-controlled dissolution regime for a powdered forsterite sample at pH 2.3, implying that transport limitations are negligible. In contrast, the relationship between flow rates and dissolution rates for single grain calcite samples at pH 2.3–4 reveals that transport limitations affect the rate of calcite dissolution. To provide a quantitative and process-based assessment of the effect of diffusive transport limitations, simulations of the calcite experiments were performed with a high resolution, pore-scale model that considers the geometry of the calcite grain and the FT-TRA flow-through reactor. The pore-scale model reproduces the observed effluent [Ca] concentrations for all experimental conditions using a single set of surface kinetic parameters, by accounting for the formation of a diffusive boundary layer (DBL) that varies in thickness as a function of flow rates. These results demonstrate that combining FT-TRA with pore-scale modeling makes it possible to obtain unprecedented insights not achievable by either method separately, including quantification of DBL thicknesses and the determination of transport controls as a function of pH, flow velocity and residence times.