Updating the Structure and Electrochemistry of Li<sub>x</sub>NiO<sub>2</sub> for 0 ≤ x ≤ 1
Bibliographic record
Abstract
Ni-rich transition metal layered oxide materials are of great interest as positive electrode materials for lithium ion batteries. As the popular electrode materials NMC (LiNi 1-x-y Mn x Co y O 2 ) and NCA (LiNi 1-x-y Co x Al y O 2 ) become more and more Ni-rich, they approach LiNiO 2 . Therefore it is important to benchmark the structure and electrochemistry of state of the art Li x NiO 2 for the convenience of researchers in the field. In this work, LiNiO 2 synthesized from a commercial Ni(OH) 2 precursor and modern synthesis methods shows a specific capacity close to the theoretical specific capacity of 274 mAh/g. In-situ X-ray diffraction (XRD) measurements were conducted to obtain accurate structural information versus lithium content, x. The known multiple phase transitions of Li x NiO 2 during charge and discharge were clearly observed, and the variation in unit cell lattice constants and volume was measured. Differential capacity versus voltage (dQ/dV vs. V) studies were used to investigate the electrochemical properties including regions of composition that show very slow kinetics. It is hoped that this work will be a useful reference for those working on Ni-rich positive electrode materials for Li-ion cells.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".