Ultra High Precision Study on High Capacity Cells for Large Scale Automotive Application
Bibliographic record
Abstract
Three nominally identical cohorts of NMC/graphite automotive Li-ion cells aged zero, one, and two years were obtained from an automotive Li-ion cell producer. The aged cells were stored at 50% state of charge at room temperature without cycling. High precision coulometry and differential voltage analysis (dV/dQ vs. Q) were used to probe the fresh and aged cells to learn about the parasitic reactions occurring. The stored cells had developed a mature SEI which led to virtually no capacity loss during testing but precision coulometry still showed evidence for significant electrolyte oxidation at the positive electrode. The fresh cells showed SEI growth at the negative electrode leading to initial capacity fading which accelerated with temperature. They also showed electrolyte oxidation at the positive electrode which increased dramatically with cycling temperature or upper cutoff potential. All cells showed virtually no evidence for loss of active material during storage or cycling. These results strongly suggest that electrolyte additives which limit electrolyte oxidation at the positive electrode side are required to improve the longevity of these 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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".