Self-Discharge in Electrochemical Capacitors: A Perspective Article
Bibliographic record
Abstract
This perspective article outlines some of the key considerations and literature that have been published on self-discharge in electrochemical capacitors. While for some consumer applications self-discharge is not considered to be a significant issue (e.g. energy storage from regenerative breaking) in applications where the electrochemical capacitor is stored in the charged state for significant times (e.g. coupled with a battery in a cell phone), the impact on energy, power and recharging frequency of both the capacitor and battery can be significant. A description is provided here of the common methods of self-discharge study: half cell vs. full cell measurements and open-circuit potential decay versus float currents. A description of some of the models used to evaluate faradaic self-discharge is presented, with a synopsis of the important aspects of the many available charge redistribution models. An overview of the current self-discharge mechanisms for various ECs is provided, highlighting that for many systems there are significant factors of the self-discharge process which remain unknown. Finally, some future directions are anticipated for the field of self-discharge in electrochemical capacitors.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".