A review of electrolyte materials and compositions for electrochemical supercapacitors
Bibliographic record
Abstract
Electrolytes have been identified as some of the most influential components in the performance of electrochemical supercapacitors (ESs), which include: electrical double-layer capacitors, pseudocapacitors and hybrid supercapacitors. This paper reviews recent progress in the research and development of ES electrolytes. The electrolytes are classified into several categories, including: aqueous, organic, ionic liquids, solid-state or quasi-solid-state, as well as redox-active electrolytes. Effects of electrolyte properties on ES performance are discussed in detail. The principles and methods of designing and optimizing electrolytes for ES performance and application are highlighted through a comprehensive analysis of the literature. Interaction among the electrolytes, electro-active materials and inactive components (current collectors, binders, and separators) is discussed. The challenges in producing high-performing electrolytes are analyzed. Several possible research directions to overcome these challenges are proposed for future efforts, with the main aim of improving ESs' energy density without sacrificing existing advantages (e.g., a high power density and a long cycle-life) (507 references).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".