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Machine Learning Energies of 2 Million Elpasolite(ABC2D6)Crystals
Open accessAbstract
Elpasolite is the predominant quaternary crystal structure (${\mathrm{AlNaK}}_{2}{\mathrm{F}}_{6}$ prototype) reported in the Inorganic Crystal Structure Database. We develop a machine learning model to calculate density functional theory quality formation energies of all $\ensuremath{\sim}2\ifmmode\times\else\texttimes\fi{}{10}^{6}$ pristine $AB{C}_{2}{D}_{6}$ elpasolite crystals that can be made up from main-group elements (up to bismuth). Our model's accuracy can be improved systematically, reaching a mean absolute error of $0.1\text{ }\text{ }\mathrm{eV}/\mathrm{atom}$ for a training set consisting of $10\ifmmode\times\else\texttimes\fi{}{10}^{3}$ crystals. Important bonding trends are revealed: fluoride is best suited to fit the coordination of the $D$ site, which lowers the formation energy whereas the opposite is found for carbon. The bonding contribution of the elements $A$ and $B$ is very small on average. Low formation energies result from $A$ and $B$ being late elements from group II, $C$ being a late (group I) element, and $D$ being fluoride. Out of $2\ifmmode\times\else\texttimes\fi{}{10}^{6}$ crystals, 90 unique structures are predicted to be on the convex hull---among which is ${\mathrm{NFAl}}_{2}{\mathrm{Ca}}_{6}$, with a peculiar stoichiometry and a negative atomic oxidation state for Al.
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Metadata
- Authors
- Faber, F. A., Lindmaa, A., von Lilienfeld, O. A., & Armiento, R.
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 2016-09-20
- Volume
- 117
- Issue
- 13
- Pages
- 135502-135502
- ISSN
- 0031-9007 (ISSN-L)
- 1079-7114
- OpenAlex
- W1865667476
- Cited by
- 409
- References
- 10
- FWCI
- 19.65
- Type
- journal article
- Language
- en
- Open access
- hybrid
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