Production of Carbonaceous Materials with High Capacitance by Electrochemical Technique
Bibliographic record
Abstract
Green" energy production and storage is a rapidly growing area of research due to increased demand of society.Commonly used lithiumion and lead based batteries can reach energy densities up to 180 W h kg -1 or higher, but they present slow energy delivery/uptake.Electrochemical capacitors, on the other hand, deliver high power and can work stably through many cycles.Their properties make them promising option to fill the gap between electrostatic capacitors and batteries.Electrochemical capacitors can be divided in two groups by their action mechanism: 1) electrical double layer capacitors, in which energy is stored in electrical double-layer formed at a solid electrode -electrolyte interface, so there is no charge transfer (1); 2) pseudocapacitors, there the energy is stored by fast reversible Faradaic reactions between the electrode and the ions in the electrolyte, so it involves charge transfer across the interface (2).It was shown that pseudocapacitors can deliver higher specific capacitance, so a lot of studies were dedicated to a search for appropriate electrode materials and working conditions.As mentioned above, supercapacitors store energy by ion adsorption, so specific surface area (SSA) of electrode materials must be relatively high to facilitate the process.Carbon based materials are prominent in electrode development because of their unique properties.Many allotropic forms of carbon were studied to be used in supercapacitors.The most promising results were obtained for graphene and other shapes of carbon, due to their high surface area (3, 4).Graphene is considered one of the most promising materials for electrode development due to its electrical conductivity and a high theoretical specific surface area (up to 2630 m 2 g -1 ) (5).Although, this area was not achieved in practice, 135 F g -1 gravimetric capacitance was reported for graphene in aqueous electrolytes (6).A gravimetric capacitance for graphene materials was improved (298 F g -1 ) in ionic liquids (3).Another way to improve gravimetric capacitance is doping graphene materials with nitrogen.For instance,
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".