Effective recovery of the air-exposed Ni-rich lithium transition metal oxide cathodes with a coating-stabilized surface
Bibliographic record
Abstract
The electrochemical cycling performance of Ni-rich cathode materials is adversely affected by the exposure of the active materials to the ambient environment, especially for a harsh cycling condition. To mitigate this degradation, LixByC1-yOz (LBCO) was synthesized where B and C are with identical chemical bonding structures and a 0.5 at% LBCO sol-gel coating process is introduced. Here we provide a comprehensive characterization of the coating material and the effect of coating. We confirm the effectiveness of the coating method and optimize processing parameters from both chemical and electrochemical perspectives. The coating and following process can regenerate the deteriorated surface and recover the capacity. After extended cycling, we demonstrate that the LBCO coating stabilized the surface and protected the bulk from severe structural degradation, with multiscale electron microscopy and spectroscopy characterization techniques. Our in-depth investigation provides a promising approach to recovering the degraded surface structure and electrochemical performance by applying LBCO coatings.
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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".