Lack of Cation Clustering in Li[Ni<i><sub>x</sub></i>Li<sub>1/3</sub><sub>-</sub><sub>2</sub><i><sub>x</sub></i><sub>/3</sub>Mn<sub>2/3</sub><sub>-</sub><i><sub>x</sub></i><sub>/</sub><sub>3</sub>]O<sub>2</sub> (0 < <i>x</i> ≤ <sup>1</sup>/<sub>2</sub>) and Li[Cr<i><sub>x</sub></i>Li<sub>(1</sub><sub>-</sub><i><sub>x</sub></i><sub>)/3</sub>Mn<sub>(2</sub><sub>-</sub><sub>2</sub><i><sub>x</sub></i><sub>)/3</sub>]O<sub>2</sub> (0 < <i>x </i>< 1)
Bibliographic record
Abstract
Recent papers by Ammundsen et al. and Pan et al. give evidence for the formation of local regions high in Mn content and other local regions high in Cr or Ni content in Li[Li 0.2 Cr 0.4 Mn 0.4 ]O 2 and Li[Ni 0.5 Mn 0.5 ]O 2 by EXAFS and NMR methods, respectively. These observations are surprising for the following reasons: (1) each of these materials is a part of a solid solution series, Li[Cr x Li (1 - x )/3 Mn (2 - 2 x )/ 3 ]O 2 (0 < x < 1) or Li[Ni x Li 1/3 - 2 x /3 Mn 2/3 - x /3 ]O 2 (0 < x < 1 / 2 ); (2) the materials are made at high temperature, and entropy considerations suggest that like transition-metal atoms should not cluster; and (3) the electrochemical and structural properties of the materials vary smoothly with composition. Here, using careful X-ray diffraction on many samples from each solid solution, we show that it is very unlikely that such local regions high in Mn, Ni, or Cr exist. We show that long-ranged lithium ordering on the 3 1/2 a × 3 1/2 a superstructure occurs as expected based on the work of Schick et al., however, this does not imply local regions of Li 2 MnO 3 . Instead, the diffraction angles of the superstructure peaks shift with composition suggesting that the Mn, Cr, or Ni are uniformly mixed on the transition-metal sites. In addition, we show that the electrochemical behavior of Li[Ni x Li 1/3 - 2 x /3 Mn 2/3 - x /3 ]O 2 heated to 1000 °C is improved compared to that of samples made at 900 °C.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".