Machine learning molecular dynamics simulations toward exploration of high-temperature properties of nuclear fuel materials: case study of thorium dioxide

Predicting materials properties of nuclear fuel compounds is a challenging task in materials science. Their thermodynamical behaviors around and above the operational temperature are essential for the design of nuclear reactors. However, they are not easy to measure, because the target temperature r...

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Detalles Bibliográficos
Autores principales: Kobayashi, Keita, Okumura, Masahiko, Nakamura, Hiroki, Itakura, Mitsuhiro, Machida, Masahiko, Cooper, Michael W. D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9192752/
https://www.ncbi.nlm.nih.gov/pubmed/35697713
http://dx.doi.org/10.1038/s41598-022-13869-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9192752/
https://www.ncbi.nlm.nih.gov/pubmed/35697713
http://dx.doi.org/10.1038/s41598-022-13869-9

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