Abstract

Thermodynamic modeling of phase diagrams provides fundamental information for applications such as solidification, crystal growth, joining, solid-state reaction, casting, phase transformations and oxidations. CALPHAD method has been widely used to predict phase diagrams and thermodynamic properties. However, for systems with no or few experimental phase equilibrium data and/or thermodynamic properties, CALPHAD method cannot be applied. For these systems, predicting thermodynamic properties using theoretical and/or empirical formulae is of great interest. Engel-Brewer and Miedema tried to predict enthalpy of mixing based on electronic properties. Whereas, Faber, Guggenheim, Sommer and Wituciewicz formulated excess entropy of mixing.
In this study, Engel-Brewer method is used to calculate thermodynamic properties and phase relations for 5 binary systems and the results are compared with the experimental data from the literature. Then, Engel-Brewer method and Miedema model are applied to calculate enthalpy of mixing of 50 liquid and solid solutions and the results are compared with the experimental data from the literature. Analysis of the results indicates that the Engel-Brewer method is not robust, while Miedema model with some modifications is evaluated as an appropriate model to predict enthalpy of mixing of liquid and solid solutions. Moreover, the models of Faber, Guggenheim, Sommer and Wituciewicz are used to predict entropy of mixing of 50 liquid alloys and the results are then compared with the experimental data from the literature. A critical review of each of these entropy relations is presented and it is concluded that the Wituciewicz relation is the most appropriate model to predict entropy of mixing of liquid alloys. Finally, based on the current work, a combined Miedema-Wituciewicz model is suggested to parameterize Gibbs free energy of mixing for liquid solutions. This model can be used to predict thermodynamic properties and consequently, binary phase diagrams without relying on the experimental thermochemical data.