Bibliographic record
Abstract
Supercapacitor (SCs), known as outstanding electrical storage capacity, which times more than the batteries and fuel cells, recharges with a large amount of released power, fast overpassing the gap between capacitors and batteries, and widely be employed in the field of energy storage. Metal-organic frameworks (MOFs) attract intensive attention as electrode materials in supercapacitor application, owing to their ultrahigh porosity, adjustable distribution of pore size, convenient synthesis, great structural adaptability, etc. Composited with different materials, such as carbons family, metal oxide, can improve pristine MOFs' conductivity and chemical stability, which are all-important as electrode materials in SCs. This review comprehensively summarizes the common synthesis methods of four kinds of MOFs materials: the pristine MOFs, MOFs composites, MOFs-derived nanoporous carbons, and MOFs-derived metal oxides. Also, the applications of these four kinds of materials in SCs electrode materials are systematically introduced. Furthermore, a perspective on MOFs materials in the field of SCs is discussed.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".