Elucidating the temperature and density dependence of silver chloride hydration numbers in high-temperature water vapor: A first-principles molecular simulation study

• Published in: Chemical geology Vol. 594; p. 120766
• Main Authors: Messerly, Richard A., Yoon, Tae Jun, Jadrich, Ryan B., Currier, Robert P., Maerzke, Katie A.
• Format: Journal Article
• Language: English
• Published: United States Elsevier B.V 05-04-2022; Elsevier
• Subjects: Density functional theory; GEOSCIENCES; Hydration structure; Hydrothermal fluids; Inorganic and Physical Chemistry; INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; Machine learning potentials; Monte Carlo; Hydrothermal fluids; Density functional theory; Machine learning potentials; Monte Carlo; Hydration structure
• ISSN: 0009-2541; 1872-6836
• DOI: 10.1016/j.chemgeo.2022.120766

Hydration numbers of metal complexes in low-density aqueous solutions are required for developing geochemical models for ore-forming metals and for designing supercritical desalination processes. In this study, we investigate the temperature and density dependence of the hydration numbers of silver chloride at 623 K, 673 K, and 713 K and densities of 10–100 kg/m3. Experimental estimates of the hydration number in the literature for AgCl at these conditions are inconclusive and possibly contradictory as to the temperature and density dependence. First-principles molecular simulation presents an attractive alternative to experimental measurements. Specifically, recent work shows that machine-learning-accelerated nested Monte Carlo simulations provide reliable estimates for the hydration numbers of CuCl at 623 K from 10 to 100 kg/m3. Using the same technique, we find a monotonic temperature dependence, with the hydration number decreasing slightly with increasing temperature. In addition, the simulation-predicted hydration numbers steadily increase with increasing density. These temperature and density trends are in agreement with certain experimental data sets. Therefore, this work demonstrates how first-principles Monte Carlo simulations assist in resolving discrepancies between experimental data sets. Our simulation results also correctly predict that the hydration number, and thus also the solubility, of AgCl is lower than that of CuCl under the same conditions. Furthermore, the bond length and angle formed between the water complex and AgCl differ from those for CuCl, consistent with the lower solubility of AgCl.
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