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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
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Conference presentation
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Abstract Most research on the electrochemical dynamics in materials for high‐energy Li‐ion batteries has focused on the global behavior of the electrode. This approach is susceptible to misleading analyses resulting from idiosyncratic kinetic conditions, such as surface impurities inducing an apparent two‐phase transformation within LiNi 0.8 Co 0.15 Al 0.05 O 2 . Here, nano‐focused X‐ray probes are used to measure delithiation operando at the scale of secondary particle agglomerates in layered cathode materials during charge. After an initial latent phase, individual secondary particles undergo rapid, stochastic, and largely uniform delithiation, which is in contrast with the gradual increase in cell potential. This behavior reproduces across several layered oxides. Operando X‐ray microdiffraction (‐XRD) leverages the relationship between Li content and lattice parameter to further reveal that rate acceleration occurs between Li‐site fraction ( x Li ) ≈0.9 and ≈0.5 for LiNi 0.8 Co 0.15 Al 0.05 O 2 . Physics‐based modeling shows that, to reproduce the experimental results, the exchange current density ( i 0 ) must depend on x Li , and that i 0 should increase rapidly over three orders of magnitude at the transition point. The specifics and implications of this jump in i 0 are crucial to understanding the charge‐storage reaction of Li‐ion battery cathodes.
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