Material advancements in supercapacitors: From activated carbon to carbon nanotube and graphene
Bibliographic record
Abstract
Abstract The electrochemical capacitor (EC), also known as supercapacitor, is an energy storage device possessing a near infinite life‐cycle and high power density recognised to store energy in the double‐layer or through pseudocapacitance as a result of an applied potential. Fundamental principles of charge storage in relation to the important physical and chemical characteristics of electrode materials are addressed in the following review, with carbon‐made electrodes, specifically activated carbon, carbon fibres and aerogels, carbon nanotubes and graphene emphasised in regards to their enhancement of the characteristic energy and power densities of ECs. Pseudocapacitive materials, notably transition metal oxides and nitrides, and conducting polymers are remarked by the potential to further improve EC performance through synergistic effects and asymmetric design. Research towards gaining a better understanding of charge storage in sub‐micropores, material design and improving the performance of alternative electrolytes are expected to greatly enhance the capabilities of these devices in the near future.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".