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Thermodynamic database for multicomponent oxide systems
Abstract
A state-of-the-art thermodynamic database has been developed for multicomponent oxide systems. It can be used in combination with FactSage software to calculate the properties of metallurgical slags, glasses, ceramics, refractories, minerals, cements, etc. The database has been developed by collecting all available structural, thermodynamic, and phase equilibria data for a particular chemical system, critical evaluation of this information, developing a thermodynamic model for each solution phase and optimization of model parameters to reproduce the experimental data. Then the models are used to estimate the thermodynamic properties of multicomponent solutions from the properties of lower-order subsystems. Oxide phases often exhibit complex structures and strong interactions between components, which require more sophisticated models than are normally used, for example, for metal alloys. Short-range ordering is rather common and random mixing is often not a good approximation. The models for multicomponent liquid and solid solutions have been developed within the Modified Quasichemical Formalism and Compound Energy Formalism. Optimized model equations are consistent with thermodynamic principles and fully characterize a chemical system, requiring much less experimental work to achieve this goal since only a few measurements are needed in higher-order systems to validate the model estimates. The database can be readily used in conjunction with the FactSage Gibbs energy minimization software to calculate any stable or metastable phase equilibria and phase diagrams. The present article outlines the major components and phases that are currently available in the oxide database, as well as the most important features of the models that have been developed. The model and database have also been developed for the viscosity of oxide melts and glasses. The model links the viscosity to the structure of the liquid phase, which is estimated using the thermodynamic database.
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DOI: https://doi.org/10.15826/chimtech.2018.5.1.02
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