Exploring Interactions between Electrodes in Li[Ni<sub>x</sub>Mn<sub>y</sub>Co<sub>1-xy</sub>]O<sub>2</sub>/Graphite Cells through Electrode/Electrolyte Interfaces Analysis
Bibliographic record
Abstract
Interactions occurring between positive and negative electrodes during constant current-constant voltage cycling in Li[Ni x Mn y Co 1-xy ]O 2 /graphite pouch cells at various upper cutoff voltages was investigated. Below 4.3 V, good capacity retention, high/stable coulombic efficiency (CE) and low gas production were observed. At 4.5 V, however, extensive capacity loss, dramatic/unstable CE and large gas generation were observed due to extensive electrolyte degradation at the NMC electrodes. XPS experiments highlighted that solvents (-CO containing species) and salt (mostly LiF) degradation products including gas and NMC dissolution products are produced at the NMC electrodes then migrate to the graphite electrodes surface where they are either reduced or simply deposited. Although these phenomena were greatly accelerated at high voltage, the dominant failure mechanism was the formation of a Li-ion insulator/electron conductor surface layer (maybe rock salt) due to irreversible structural change of the NMC particles surface. At low voltage, the failure mechanism was explained by accumulation of SEI at the graphite electrode surface that hinder the ionic transport through the electrode porosity. Overall, both failure mechanisms are driven by oxidative parasitic reactions at the positive electrode and interaction with the negative electrode. Passivation of the positive electrode appears therefore crucial to promote long lifetime of 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".