Cargando…
Understanding high pressure molecular hydrogen with a hierarchical machine-learned potential
The hydrogen phase diagram has several unusual features which are well reproduced by density functional calculations. Unfortunately, these calculations do not provide good physical insights into why those features occur. Here, we present a fast interatomic potential, which reproduces the molecular h...
Autores principales: | Zong, Hongxiang, Wiebe, Heather, Ackland, Graeme J. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538439/ https://www.ncbi.nlm.nih.gov/pubmed/33024105 http://dx.doi.org/10.1038/s41467-020-18788-9 |
Ejemplares similares
-
H(2) Chemical
Bond in a High-Pressure Crystalline
Environment
por: Marqués, Miriam, et al.
Publicado: (2023) -
When immiscible becomes miscible—Methane in water at high pressures
por: Pruteanu, Ciprian G., et al.
Publicado: (2017) -
Hierarchical confounder discovery in the experiment-machine learning cycle
por: Rogozhnikov, Alex, et al.
Publicado: (2022) -
Understanding Hierarchical Processes
por: Buntine, Wray
Publicado: (2022) -
Evaluating hierarchical machine learning approaches to classify biological databases
por: Rezende, Pâmela M, et al.
Publicado: (2022)