Equation of state predictions for ScF3 and CaZrF6 with neural network-driven molecular dynamics

In silico property prediction based on density functional theory (DFT) is increasingly performed for crystalline materials. Whether quantitative agreement with experiment can be achieved with current methods is often an unresolved question, and may require detailed examination of physical effects su...

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Veröffentlicht in:	The Journal of chemical physics 2023-08, Vol.159 (8)
Hauptverfasser:	Stoppelman, John P., Wilkinson, Angus P., McDaniel, Jesse G.
Format:	Artikel
Sprache:	eng
Schlagworte:	Anharmonicity Density functional theory Equations of state First principles Low temperature Molecular dynamics Neural networks Thermal expansion
Online-Zugang:	Volltext
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