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Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
This work is the first report of a molybdenum carbide-based electrocatalyst for sulfur-based sodium metal batteries (SMBs/NMBs). MoC/Mo 2 C is in-situ grown on nitrogen-doped carbon nanotubes in parallel with formation of extensive nanoporosity. Sulfur impregnation (50 wt% S) results in unique triphasic architecture termed MoC/Mo 2 C@PCNT-S. Quasi-solid-state phase transformation to Na 2 S is promoted in carbonate electrolyte, with in-situ time-resolved Raman, XPS and optical analysis demonstrating minimal soluble polysulfides. MoC/Mo 2 C@PCNT-S cathodes delivered among the most promising rate performance characteristics in literature, achieving 987 mAh g -1 at 1 Ag -1 , 818 mAh g -1 at 3 A g -1 , and 621 mAh g -1 at 5 A g -1 . The cells deliver superior cycling stability, retaining 650 mAh g -1 after 1000 cycles at 1.5 Ag -1 , corresponding to 0.028% capacity decay per cycle. High mass loading cathodes (64 wt% S, 12.7 mg cm -2 ) also show cycling stability, with anode degradation due to deep plating/stripping driving capacity decay. Density functional theory (DFT) demonstrates that formation energy of Na 2 S x (1 ≤ x ≤ 4) on surface of MoC/Mo 2 C is significantly lowered compared to analogous redox in liquid. Strong binding of Na 2 S x (1 ≤ x ≤ 4) on MoC/Mo 2 C surfaces results from charge transfer between the sulfur and Mo sites on carbides' surface.
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations