Building a DFT+U machine learning interatomic potential for uranium dioxide

Despite uranium dioxide (UO2) being a widely used nuclear fuel, fuel performance models rely extensively on empirical correlations of material behavior, leveraging the historical operating experience of UO2. Mechanistic models that consider an atomistic understanding of the processes governing fuel...

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Veröffentlicht in:	Artificial intelligence chemistry 2023-12, Vol.2 (1)
Hauptverfasser:	Stippell, Elizabeth Louise, Alzate-Vargas, Lorena Leidy, Subedi, Kashi Nath, Tutchton, Roxanne M'liss, Cooper, Michael William DOnald, Tretiak, Sergei, Gibson, Tammie Renee, Messerly, Richard Alma
Format:	Artikel
Sprache:	eng
Schlagworte:	Actinides Atomistic simulations Machine learning Molecular dynamics NUCLEAR FUEL CYCLE AND FUEL MATERIALS
Online-Zugang:	Volltext
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