Temperature-dependent dynamic disproportionation in LiNiO2
Bibliographic record
Abstract
Abstract Nickelate materials offer diverse functionalities for energy and computing applications. Lithium nickel oxide (LiNiO 2 ) is an archetypal layered nickelate, but the electronic structure of this correlated material is not yet fully understood. Here we investigate the temperature-dependent speciation and spin dynamics of Ni ions in LiNiO 2 . Ab initio simulations predict that Ni ions disproportionate into three states, which dynamically interconvert and whose populations vary with temperature. These predictions are verified using x-ray absorption spectroscopy, x-ray magnetic circular dichroism, and resonant inelastic x-ray scattering at the Ni L 3,2 -edge. Charge-transfer multiplet calculations consistent with disproportionation reproduce all experimental features. Our results support a model of dynamic disproportionation that explains diverse physical observations of LiNiO 2 , including magnetometry, thermally activated electronic conduction, diffractometry, core-level spectroscopies, and the stability of ubiquitous antisite defects. This unified understanding of the material properties of LiNiO 2 is important for applications of nickelate materials as battery cathodes, catalysts, and superconductors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".