Safety of Lithium-Ion Cells and Batteries at Different States-of-Charge
Bibliographic record
Abstract
Lithium-ion cells and batteries pose safety risks along with their favorable characteristics such as high energy and power densities. The numerous differences in chemistries and form-factors along with poor manufacturing quality in some cases, can lead to unpredictable field failures with this battery chemistry. The safety of lithium-ion cells and batteries at various states of charge (SOC) has not been studied comprehensively in the past and the goal of this study was to determine if the result of off-nominal conditions would vary with SOC. The study includes cells and batteries of different form factors, cathode chemistries, and capacities. The off-nominal conditions that the cells were exposed to were high-temperature and low impedance external short. In addition to this, voltage stability for the cells and batteries at various SOC was studied for a period of 9 months. The results demonstrate the differences in the level of safety for the cells and batteries at different SOC.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".