Porous Carbon with Willow-Leaf-Shaped Pores for High-Performance Supercapacitors
Bibliographic record
Abstract
A novel kind of biomass-derived, high-oxygen-containing carbon material doped with nitrogen that has willow-leaf-shaped pores was synthesized. The obtained carbon material has an exotic hierarchical pore structure composed of bowl-shaped macropores, willow-leaf-shaped pores, and an abundance of micropores. This unique hierarchical porous structure provides an effective combination of high current densities and high capacitance because of a pseudocapacitive component that is afforded by the introduction of nitrogen and oxygen dopants. Our synthetic optimization allows further improvements in the performance of this hierarchical porous carbon (HPC) material by providing a high degree of control over the graphitization degree, specific surface area, and pore volume. As a result, a large specific surface area (1093 m 2 g –1 ) and pore volume (0.8379 cm 3 g –1 ) are obtained for HPC-650, which affords fast ion transport because of its short ion-diffusion pathways. HPC-650 exhibits a high specific capacitance of 312 F g –1 at 1 A g –1, retaining 76.5% of its capacitance at 20 A g –1 . Moreover, it delivers an energy density of 50.2 W h kg –1 at a power density of 1.19 kW kg –1, which is sufficient to power a yellow-light-emitting diode and operate a commercial scientific calculator.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".