Experimental Data for Electrochemical Impedance Characterization of Li-ion Batteries Under Varying State of Charge, Current Amplitude and Rest Time
Bibliographic record
Abstract
Pilot testing – This test was conducted initially to select appropriate AC amplitudes for main EIS experiment. The tests were conducted on the single cylindrical cell made by Molicel of type INR-21700-P42A, labelled MCLE3231. The test was conducted over a frequency range of 0.1 Hz to 20 kHz using different current amplitudes 1 mA, 2 mA, 3 mA, 4 mA, 5 mA, 10 mA, 15 mA, 20 mA, 25 mA, 30 mA, 50 mA, 100 mA, 500 mA, and 1 A. Variability testing - The data was collected on four cylindrical batteries made by Molicel of type INR-21700-P42A labelled as MCLI01, MCLI02, MCLI03, MCLI04. The experiments were performed at different SOC levels (80%, 60%, 40%, and 20%), various current amplitudes (30 mA, 50 mA, 100 mA, 500 mA, and 1 A), and rest times (30 minutes, 1 hour, and 2 hours). All tests were conducted over a frequency range of 0.01 Hz to 10 kHz. The experiments were conducted using two instruments Arbin battery cycler and Gamry 5000P potentiostat. The data collected during pilot testing are stored as CSV (Comma-Separated Values) files inside a folder named “Factor_CurrentAmplitude”. The data collected during the variability testing are in CSV format and are stored in a folder named “Factor_Resttime.”
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".