Surface chemical heterogeneous distribution in over-lithiated Li1+xCoO2 electrodes
Bibliographic record
Abstract
Abstract In commercial Li-ion batteries, the internal short circuits or over-lithiation often cause structural transformation in electrodes and may lead to safety risks. Herein, we investigate the over-discharged mechanism of LiCoO2/graphite pouch cells, especially spatially resolving the morphological, surface phase, and local electronic structure of LiCoO2 electrode. With synchrotron-based X-ray techniques and Raman mapping, together with spectroscopy simulations, we demonstrate that over-lithiation reaction is a surface effect, accompanied by Co reduction and surface structure transformation to Li2CoO2/Co3O4/CoO/Li2O-like phases. This surface chemical distribution variation is relevant to the depth and exposed crystalline planes of LiCoO2 particles, and the distribution of binder/conductive additives. Theoretical calculations confirm that Li2CoO2-phase has lower electronic/ionic conductivity than LiCoO2-phase, further revealing the critical effect of distribution of conductive additives on the surface chemical heterogeneity evolution. Our findings on such surface phenomena are non-trivial and highlight the capability of synchrotron-based X-ray techniques for studying the spatial chemical phase heterogeneity.
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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".