Calibration process for rechargeable cell and battery test systems
Bibliographic record
Abstract
Coulombic efficiency is a powerful metric for evaluating the performance of materials in rechargeable cells and batteries. The ideal Coulombic efficiency, the ratio of charge removed to charge inserted, is unity. Some specialized systems can accurately measure cell capacity and Coulombic efficiency within 0.001%, which requires precise control and measurement of current, voltage, time, and temperature. Most battery electrode and electrolyte research is not performed with such precise but complex systems. The purpose of this paper is to demonstrate a simple, robust procedure to measure and possibly improve the accuracy of capacity and Coulombic efficiency measurements on standard systems in their as-used state. This approach is built on a commercially available thin film rechargeable cell for micro or milliampere currents and can be extended to, e.g., 18 650, cells for higher currents. An improved method to display Coulombic efficiency data is also presented. Regular, consistent calibration of testing systems and reporting of system resolution at specified test conditions is encouraged.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.009 |
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".