Finding Nature’s Missing Ternary Oxide Compounds Using Machine Learning and Density Functional Theory
Top Cited Papers
- 27 May 2010
- journal article
- research article
- Published by American Chemical Society (ACS) in Chemistry of Materials
- Vol. 22 (12), 3762-3767
- https://doi.org/10.1021/cm100795d
Abstract
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This publication has 36 references indexed in Scilit:
- Density functional theory based screening of ternary alkali-transition metal borohydrides: A computational material design projectThe Journal of Chemical Physics, 2009
- Pnictide Oxides: A New Class of High‐TC SuperconductorsAngewandte Chemie-International Edition, 2008
- Li−Fe−P−O2 Phase Diagram from First Principles CalculationsChemistry of Materials, 2008
- Complex thermoelectric materialsNature Materials, 2008
- Computational high-throughput screening of electrocatalytic materials for hydrogen evolutionNature Materials, 2006
- Toward Computational Materials Design: The Impact of Density Functional Theory on Materials ResearchMRS Bulletin, 2006
- Accuracy of ab initio methods in predicting the crystal structures of metals: A review of 80 binary alloysCalphad, 2005
- Cu-Au, Ag-Au, Cu-Ag, and Ni-Au intermetallics: First-principles study of temperature-composition phase diagrams and structuresPhysical Review B, 1998
- Self-Consistent Equations Including Exchange and Correlation EffectsPhysical Review B, 1965
- Inhomogeneous Electron GasPhysical Review B, 1964