The Negative Impact of Layered-Layered Composites on the Electrochemistry of Li-Mn-Ni-O Positive Electrodes for Lithium-Ion Batteries
Bibliographic record
Abstract
The Li-Mn-Ni-O system has received much attention for potential positive electrode materials in lithium ion batteries. In recent work the phase diagram under certain experimental conditions has been mapped out. Using the phase diagram as a guide, it is possible to select compositions near the boundary of the layered region that are layered-layered nano-composites or are single phase layered depending on the synthesis conditions. Some compositions are single phase layered no matter what synthesis conditions are used. Other compositions near LiNi 0.5 Mn 0.5 O 2 , which lie near the boundary of the single phase layered region, can either be single phase layered when quenched or a layered-layered nano-composite if cooled more slowly in an oxygen poor atmosphere or be a three phase material if cooled slowly in an oxygen rich atmosphere. Here, XRD and electrochemical data are reported on samples synthesized under various oxygen partial pressures for both quenched and slow cooled samples. These results are related to the phase diagram in order to better understand the consequences of the structural changes taking place during cooling on the electrochemistry. Single phase samples show excellent charge-discharge capacity and reversibility. However, there is a dramatic decrease in capacity in samples showing the first signs of forming a layered-layered nano-composite, suggesting that layered-layered nano-composites should be avoided.
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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) | 0.001 | 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".