journal article·2015-12

Phase diagrams and thermochemical modeling of salt lake brine systems. I. LiCl+H2O system

Dongdong Li, Dewen Zeng, Haijun Han, Lijiang Guo, Xia Yin, Yan Yao

Calphad· Volume 51
Publisher page

Abstract

Abstract Salt lake brine chemical engineering involves the study of the solid–liquid equilibria of more than one hundred water–salt systems and approximately 70 solid salts over a wide temperature range. Prediction of the crystallization behavior of these complex systems as a function of temperature can only be achieved using a thermodynamic model. However, no systematic simulation studies have been reported for the complex salt lake brine systems, especially those systems containing the highly soluble salt LiCl. To complete this task, we plan to carry out a series of work. As the first part of the series of work, the Pitzer–Simonson–Clegg (PSC) model is selected to represent the thermodynamic properties of the LiCl+H2O system in the temperature range of 190 K to nearly 400 K. In this model’s framework, the temperature dependence of the thermodynamic functions (entropy, enthalpy and Gibbs energy) of the aqueous species and solid phases are determined using their heat capacities, which serves to keep their inner thermodynamics consistent and confers a strong extrapolation ability. The comprehensive thermodynamic properties, i.e., water activity, mean ionic activity coefficient, enthalpy of dilution and solution, heat capacity and solubility, are used to evaluate the model parameters. The proposed parameter regression strategy has proven successful for the LiCl+H2O system. The present work forms a solid foundation for the simulation of thermochemical properties of other complicated salt lake brine systems.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Chemical and Physical Properties in Aqueous Solutions · Calcium Carbonate Crystallization and Inhibition · Crystallization and Solubility Studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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