Internally consistent thermodynamic data for aqueous species in the system Na–K–Al–Si–O–H–Cl

Abstract

A large amount of critically evaluated experimental data on mineral solubility, covering the entire Na-K-Al-Si-O-H-Cl system over wide ranges in temperature and pressure, was used to simultaneously refine the standard state Gibbs energies of aqueous ions and complexes in the framework of the revised Helgeson-Kirkham-Flowers equation of state. The thermodynamic properties of the solubility-controlling minerals were adopted from the internally consistent dataset of Holland and Powell (2002; Thermocalc dataset ds55). The global optimization of Gibbs energies of aqueous species, performed with the GEMSFITS code (Miron et al., 2015), was set up in such a way that the association equilibria for ion pairs and complexes, independently derived from conductance and potentiometric data, are always maintained. This was achieved by introducing reaction constraints into the parameter optimization that adjust Gibbs energies of complexes by their respective Gibbs energy effects of reaction, whenever the Gibbs energies of reactant species (ions) are changed. The optimized thermodynamic dataset is reported with confidence intervals for all parameters evaluated by Monte Carlo trial calculations. The new thermodynamic dataset is shown to reproduce all available fluid-mineral phase equilibria and mineral solubility data with good accuracy and precision over wide ranges in temperature (25 to 800°C), pressure (1 bar to 5 kbar) and composition (salt concentrations up to 5 molal). The global data optimization process adopted in this study can be readily repeated any time when extensions to new chemical elements and species are needed, when new experimental data become available, or when a different aqueous activity model or equation of state should be used. This work serves as a proof of concept that our optimization strategy is feasible and successful in generating a thermodynamic dataset reproducing all fluidmineral and aqueous speciation equilibria in the Na-K-Al-Si-O-H-Cl system within their experimental uncertainties. The new dataset resolves the long-standing discrepancies between thermodynamic data of minerals and those of aqueous ions and complexes, by achieving an astonishing degree of consistency between a large number of fluid-mineral equilibrium data. All of this at the expense of changing the standard state properties of aqueous species, manly the Gibbs energy of formation. Using the same strategy, the core dataset for the system Na-K-Al-Si-O-H-Cl can be extended with additional rock-forming elements such as Ca, Mg, Fe, Mn, Ti, S, C, B. In future, the standard-state properties of minerals and aqueous species should be simultaneously optimized, to create the next-generation of fully internally consistent data for fluid-mineral equilibria. Although we employ the widely used HKF equations for this study, the same computational approach can be readily applied to any other speciation-based equation of state for multicomponent aqueous solutions.

Local Bulk Composition Effects on Metamorphic Mineral Assemblages

“…Successful application of forward equilibrium models requires an internally consistent thermodynamic database with accurate solution models and a robust estimate for the bulk composition of the system. The development and successive improvements of internally-consistent thermodynamic databases for solid and fluids (Berman 1988;Holland and Powell 1988Gottschalk 1996;Miron et al 2016) are one of the greatest advances in the field of metamorphic petrology in the last three decades. Using the Gibbs free energy minimization principle, these databases facilitate the creation of phase diagrams that describe which mineral phases are stable as a function of temperature (T), pressure (P), H 2 O and CO 2 activity (aH 2 O, aCO 2 ), oxygen fugacity ( f O 2 ) or chemical potential of a component i (µ i ).…”

Rare Earth Elements in Mineral Deposits: Speciation in Hydrothermal Fluids and Partitioning in Calcite

“…A detailed list of minerals, aqueous species, and gases used from this database for the Ca-C-Na-Cl-O-H-REE components system can be found in Table 2. This dataset comprises mineral data from Holland and Powell [55] and aqueous species from SUPCRT92 [36,57,63,64], with the recently updated internally consistent dataset of Miron et al [58] using the GEMSFITS code package [65]. Experimental data for REE chloride aqueous species were implemented using data from the study of Migdisov et al [35], the HCl dissociation constants of Tagirov et al [59], and the properties of REE(OH) 3 (s) compiled in the study of Navrotsky et al [56].…”

Validation of hydrogeochemical databases for problems in deep geothermal energy

“…log 10 K ) at elevated temperature, pressure, and salinity are typically derived from regression of experimental data. Examples for this procedure are parameter estimation for pressure dependence (Appelo et al 2014) or Pitzer parameters (Appelo 2015), statistical machine learning algorithms for fitting barite and celestite solubility (Safari et al 2014a, b) or global optimisation of Gibbs energies (Miron et al 2015(Miron et al , 2016(Miron et al , 2017. Thermodynamic data files, which are in active development, will sooner or later see an adjustment, taking into account newly available thermodynamic data.…”