Machine Learning Energies of 2 Million Elpasolite (AB2D6) Crystals

• Elpasolite is the predominant quaternary crystal structure (AlNaK2F6 prototype) reported in the Inorganic Crystal Structure Database. We develop a machine learning model to calculate density functional theory quality formation energies of all ∼2×106 pristine ABC2D6 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  eV/atom for a training set consisting of 10×103 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 2×106 crystals, 90 unique structures are predicted to be on the convex hull—among which is NFAl2Ca6, with a peculiar stoichiometry and a negative atomic oxidation state for Al.

Ämnesord

NATURVETENSKAP  -- Fysik -- Den kondenserade materiens fysik (hsv//swe)

NATURAL SCIENCES  -- Physical Sciences -- Condensed Matter Physics (hsv//eng)

Nyckelord

Machine learning

AI

Elpasolite

Materials

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