Abstract
The dissolution–precipitation of quartz controls porosity and permeability in many lithologies and may be the best studied mineral-water reaction. However, the rate of quartz-water reaction is relatively well characterized far from equilibrium but relatively unexplored near equilibrium. We present kinetic data for quartz as equilibrium is approached from undersaturation and more limited data on the approach from supersaturated conditions in 0.1 molal NaCl + NaOH + NaSiO(OH) 3 solutions with pH 8.2–9.7 at 398, 423, 448, and 473 K. We employed a potentiometric technique that allows precise determination of solution speciation within 2 kJ mol −1 of equilibrium without the need for to perturb the system through physical sampling and chemical analysis. Slightly higher equilibrium solubilities between 423 and 473 K were found than reported in recent compilations. Apparent activation energies of 29 and 37 kJ mol −1 are inferred for rates of dissolution at two surface sites with different values of connectedness: dissolution at Q 1 or Q 2 silicon sites, respectively. The dissolution mechanism varies with Δ G such that reactions at both sites control dissolution up until a critical free energy value above which only reactions at Q 1 sites are important. When our near-equilibrium dissolution rates are extrapolated far from equilibrium, they agree within propagated uncertainty at 398 K with a recently published model by Bickmore et al. (2008). However, our extrapolated rates become progressively slower than model predictions with increasing temperature. Furthermore, we see no dependence of the postulated Q 1 reaction rate on pH, and a poorly-constrained pH dependence of the postulated Q 2 rate. Our slow extrapolated rates are presumably related to the increasing contribution of dissolution at Q 3 sites far from equilibrium. The use of the potentiometric technique for rate measurement will yield both rate data and insights into the mechanisms of dissolution over a range of chemical affinity. Such measurements are needed to model the evolution of many natural systems quantitatively.
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