Review and perspective on polyhedron model for estimating thermodynamic properties of oxides

Knowledge of thermodynamics and phase equilibria of oxidic materials is crucial for advancement in the field of ceramics and glass. With the development of computational thermodynamics, predicting phase diagrams and chemical reactions of multicomponent systems has become possible. However, there are...

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Bibliographic Details
Published inJournal of the American Ceramic Society Vol. 107; no. 3; pp. 1636 - 1647
Main Authors Moosavi‐Khoonsari, Elmira, Arias‐Hernandez, Jesus Alejandro, Kwon, Sun Yong
Format Journal Article
LanguageEnglish
Published Columbus Wiley Subscription Services, Inc 01.03.2024
Subjects
Artificial intelligence
Chemical reactions
Estimation
Extrapolation
Ionic crystals
Model accuracy
Oxides
Phase diagrams
Phase equilibria
Polyhedra
Scale (corrosion)
Scale models
Thermodynamic equilibrium
Thermodynamic models
Thermodynamic properties
Thermodynamics
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Summary:Knowledge of thermodynamics and phase equilibria of oxidic materials is crucial for advancement in the field of ceramics and glass. With the development of computational thermodynamics, predicting phase diagrams and chemical reactions of multicomponent systems has become possible. However, there are still plenty of oxides, the thermodynamic properties of which have not been identified due to the challenges in conducting experiments. Therefore, a key to the advancement in thermodynamic modeling would be to develop a universal model that can be used to estimate the thermodynamic properties of oxides with reliable extrapolation capacity. Atomistic (or molecular) scale models are still insufficient in predicting the thermodynamic properties of oxides at any scale. Alternatively, among group contribution–based methods, the polyhedron model has presented its potential in the estimation of the thermodynamic properties of ionic crystals. However, this model still demands improvements that increase the model's accuracy and extrapolation capacity. In this paper, the background and the state‐of‐the‐art of polyhedron model will be presented together with its strengths and shortcomings. Subsequently, it will be briefly discussed how the field of artificial intelligence could be exploited to devise the next generation of the polyhedron model, the modified polyhedron model.
ISSN:0002-7820
1551-2916
DOI:10.1111/jace.19343