Modeling aqueous association constants and mineral solubilities at subcritical and supercritical temperatures

The need for sustainable power generation has increased interest in the use of hydrothermal fluids for industrial applications. New high-enthalpy geothermal systems and biowaste-to-fuel processes are two relevant examples that employ supercritical fluids which require an in-depth understanding of complex chemical reactions occurring near the supercritical temperature of water (374 degree celsius). As these processes operate in thermodynamic regimes that are not currently covered by a standard molar Gibbs energy of formation model, only empirical fits for single reaction systems are available which limit the use of multi-component phase equilibria cal-culations that are standard practice for less extreme environments. Here, we advance a standard molar Gibbs energy of formation model able to operate in these otherwise inaccessible thermodynamic states to include species needed for key mineral solubility systems and ion association reactions. This work extends a model based on molecular statistical thermodynamics (MST) into four new systems (Na3PO4-H2O, LiOH-H2O, KOH-H2O, and BaSO4-H2O) by extending the model to cover 10 new species. For each of these systems, model predictions were consistently within the experimental uncertainties for the new systems covered. A breakdown of MST contributions to the model revealed that electrostatic and hard sphere contributions were key to reproducing density dependencies of standard molar Gibbs energy of formation values around the critical point of water.

Automated summary

The increasing demand for sustainable power generation has led to growing interest in the use of hydrothermal fluids for industrial applications. However, the complex chemical reactions that occur near the supercritical temperature of water have limited the understanding and calculations in this field. In this study, a new model based on molecular statistical thermodynamics was developed to cover previously unexplored thermodynamic states and accurately predict the behavior of different chemical systems. This model proved successful in predicting the behavior of four new systems, providing valuable insights for future research in this area.