Investigation and Suppression of Oxygen Release by LiNi<sub>0.8</sub>Co<sub>0.1</sub>Mn<sub>0.1</sub>O<sub>2</sub> Cathode under Overcharge Conditions
Bibliographic record
Abstract
Abstract The safety issue of lithium‐ion batteries is a crucial factor limiting their large‐scale application. Therefore, it is of practical significance to evaluate the impact of their overcharge behavior because of the severe levels of oxygen release of cathode materials during this process. Herein, by combining a variety of in situ techniques of spectroscopy and electron microscopy, this work studies the structural degradation of LiNi0.8Co0.1Mn0.1O2 (NCM811) accompanying the oxygen release in the overcharge process. It is observed that a small amount of O2 evolves from the initial surface at ≈4.7 V. When charging to a higher voltage (≈5.5 V), a large amount of O2 evolves on the newly formed surface due to the occurrence of microcracks. Based on experimental results and theoretical calculations, it is determined that the oxygen release mainly occurs in the near‐surface regions, where the remaining oxygen vacancies accumulate to create voids. To suppress the oxygen release, single‐crystalline NCM811 with integrated structure is introduced and serves as a cathode, which can effectively inhibit morphology destruction and reduce the activation of lattice oxygen in the surface region. These findings provide a theoretical basis and effective strategy for improving the safety performance of Ni‐rich cathode materials in practical applications.
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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) | 0.000 | 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".