Understanding Anomalous Behavior in Coulombic Efficiency Measurements on Li-Ion Batteries
Bibliographic record
Abstract
When identical dry Li-ion batteries are filled with different electrolyte solutions, those with higher coulombic efficiency (CE) normally have a longer life-time, provided the batteries have the same test history (storage time and temperature, cycling protocol etc.). Accurate CE measurements can therefore be used to rapidly rank cells according to their life-time without relying on tests that are many years long. The CE of Li-ion cells normally increases with time since SEI layers thicken and parasitic reactions between electrodes and electrolyte, which cause the departure of the CE from unity, slow down. However, in some cases, the CE of Li-ion cells has been observed to be greater than unity and decrease during early charge-discharge cycling, which is unexpected. This anomalous behavior is shown here to be caused by the impact of lithium atoms stored in the negative electrode "overhang", the small portion of the negative electrode that extends past the positive electrode in commercial Li-ion cells. Storage protocols are discussed that allow CE to more rapidly stabilize with time or cycle number.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".