Thermodynamic g^E Models and Equations of State for Electrolytes in a Water-Poor Medium: A Review

Abstract

Research on the thermodynamics of electrolytes is timeless, and modeling an electrolyte solution might be considered to be a golden oldie, which was, is, and will be important in the design of processes and new materials in the future. The reason is that electrolytes play important roles in different scientific disciplines, such as material development, technical processes (chemical industry, biotechnology, and pharma and food industries), and most recently the energy sector. Closely connected is the further development of advanced thermodynamic models. The age of digitalization requires robust physical models as the basis for static and dynamic process modeling, and that will provide the basis for surrogate approaches in future machine learning developments. This all brings thermodynamic modeling to a consideration of its most important feature. There are many thermodynamic approaches which have been developed to correlate, model, and predict the properties and phase behavior of electrolytes. Usually, this has been very successful for aqueous electrolyte solutions. However, for solutions with poor water content, electrolyte modeling is challenging. This mini-review summarizes the recent advance of thermodynamic models for electrolyte solutions in a water-poor medium and suggests the required theoretical framework.

Prediction of salting‐out in liquid‐liquid two‐phase systems with ePC‐SAFT: Effect of the Born term and of a concentration‐dependent dielectric constant

“…That is, not only the Born term itself is important for the successful modeling of electrolyte systems, also taking into account the dependence of the dielectric constant on salt concentration is a very sensitive property that has to be included consistently in any electrolyte model. This answers partially also the main questions from recent literature [90,91] …”

“…This answers partially also the main questions from recent literature. [90,91] Figure 2 compares experimental LLE data and modeling results for the system water + MEK + NaCl and provides insights into the physical meaning of each used strategies and mixing rules within the ePC-SAFT framework. The results shown are representative for all the investigated LLTPS water + organic solvent + salt.…”

Data Analysis for Electrolyte Systems: A Method Illustrated on Alkali Halides in Water

“…This was already pointed out 10 years ago by Hendriks et al and very recently by Kontogeorgis et al , The reason why this application domain is so challenging may be summarized by the following four points: The data often refer to simple systems and do not include mixtures related to those of interest in industrial applications (this is perhaps true in many other fields) Very few models are available in commercial simulators, and these models allow reaching high salinities and/or high-temperature conditions only through strong parameterization efforts. In other words, no truly predictive approach exists, despite the many attempts in the academic community. − Many electrolyte applications feature reactive compounds, meaning that the true species in a solution may be very different from the apparent species. As a consequence, the number of binary interaction parameters to be considered in the empirical equations may become very large. Last but not least, the number of phases that may appear in these applications may be numerous (sometimes several liquids, or more often several solid phases), which implies the necessity to have access to robust and stable algorithms that allow both physical and chemical equilibria to be computed. …”

“…Very few models are available in commercial simulators, and these models allow reaching high salinities and/or high-temperature conditions only through strong parameterization efforts. In other words, no truly predictive approach exists, despite the many attempts in the academic community. − …”

Solid–Liquid Equilibrium and Binodal Curves for Aqueous Solutions of NH3, NH4HCO3, MDEA, and K2CO3

“…Interaction parameters between CO 2 and MEA, n -methyldiethanolamine (MDEA), , piperazine, or ammonia have been obtained based on different types of phase equilibria (vapor pressure, vapor–liquid, and solid–liquid) and thermal (heat capacity and heat of absorption) data. ePC-SAFT has been used to model the mean ionic activity coefficient, the osmotic coefficient, the liquid–liquid equilibrium (LLE), and the density of alkali metal halides + organic solvent + water mixtures. − The model also provided an accurate prediction of the vapor–liquid equilibrium of sour gas and amine solvents using only parameters obtained from binary data . COSMO-RS-based models have also been successfully used to predict the solid–liquid equilibrium (SLE) and LLE of salt + water/organic solvent systems. − COSMO-based models can perform fully predictive calculations and are excellent tools for solvent screening applications; however, models with adjustable binary parameters (such as the extended UNIQUAC and ePC-SAFT) tend to present smaller deviation from experimental measurements.…”