Current-Corrected Cycling for True Electrode Performance Measurement
Bibliographic record
Abstract
In battery research, galvanostatic cycling is the most widely used method to evaluate electrode performance.1 By applying pre-set current throughout the test, this method often fails to accurately reflect electrode performance at the designed cycling rate (particularly for high-rate cycling) because the actual capacity can be considerably affected by polarization and electrode degradation.2 To address this issue, a current-corrected galvanostatic cycling (CCGC) method is proposed, in which the current is actively adjusted during cycling based on the measured capacity of previous cycles.3 Compared to the traditional galvanostatic cycling (TGC) method, which may result in cycling rates that are hundreds of times faster than the designed rate, the proposed cycling strategy can effectively measure rate-dependent electrode performance precisely at designated rates. As shown in Figure 1, graphite electrodes were cycled in half cells at different rates ranging from C/20 to 5C using TGC and CCGC methods. For TGC, the capacity decreases quickly at rates higher than C/5 and becomes negligeable when the rate is ≥ 2C. This is because the actual cycling rates are much higher than the designed rates when the capacity becomes lower due to polarization, as shown in Figure 1(b). For instance, at a designed 5C rate, the observed actual cycling rate for TGC is 1200 C – 3600 C, about 500 times higher than the designed rate. In addition to the low capacities at high rates, at C/2 the capacity is not stable, due to the increasing overpotential, which causes staging plateaus to be truncated by the lower potential cutoff. References J. Liu et al., Nat. Energy, 4, 180–186 (2019). C. Heubner, M. Schneider, and A. Michaelis, Adv. Energy Mater., 10, 1902523 (2020). Z. Yan, B. Scott, S. L. Glazier, and M. N. Obrovac, Batter. Supercaps (2021) doi: 10.1002/batt.202100345. Figure 1 (a) Lithiation capacity and (b) the actual cycling rate of graphite electrodes cycled at different rates using CCGC and TGC. Reproduced with permission from ref 3. Copyright 2021 Wiley-VCH GmbH. Figure 1
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".