Self-discharge of electrochemical capacitors based on soluble or grafted quinone
Bibliographic record
Abstract
The self-discharge of hybrid electrochemical capacitors based on the redox activity of electrolyte additives or grafted species to the electrode material is investigated simultaneously for the cell and each individual electrode. Electrochemical capacitors using a redox-active electrolyte consisting in hydroquinone added to the electrolyte solution and a redox-active electrode based on anthraquinone-grafted carbon as a negative electrode are investigated. The results are analyzed by using Conway kinetic models and compared to those of a common electrochemical double layer capacitor. The self-discharge investigation is complemented by charge/discharge cycling and it is shown that processes affecting galvanostatic charge/discharge cycling and the self-discharge rate occurring at each electrode of an electrochemical capacitor are different but related to each other. The electrochemical capacitor containing hydroquinone in the electrolyte exhibits a much quicker self-discharge rate than that using a negative electrode based on grafted anthraquinone with a 50% decay of the cell voltage of the fully charged device in 0.6 and 6 h, respectively. The fast self-discharge of the former is due to the diffusion of benzoquinone molecules (formed at the positive electrode during charging) to the negative electrode, where they are reduced, causing a quick depolarization. The grafting of anthraquinone molecules on the carbon material of the negative electrode led to a much slower self-discharge, which nonetheless occurred, by the reaction of the reduced form of the grafted species with electrolyte species.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".