Modulating pore channels of activated carbon from biomass to assemble zinc ion hybrid supercapacitor with high specific capacitance
Bibliographic record
Abstract
A notable challenge in zinc ion hybrid supercapacitor (ZiHSC) is the size discrepancy between the carbon cathode pores and the [Zn·(H 2 O) 6 ] 2+ (diameter of ∼0.86 nm), which weakens ionic migration kinetics and reduces energy density. To address this, wood-derived porous carbon with a hierarchical pore structure was synthesized via combined chemical and physical activation. The thermal reduction reaction between H 2 O steam and the marginal carbon atoms in the pre-existing pores was revealed, successfully enlarging pore diameters from 0.54 nm to 0.71 nm and 1.13 nm. The optimized electrode exhibited a specific capacitance of 412.76 F/g at the scan rate of 5 mV/s in a three-electrode system, and a specific capacity of 269.54 mAh/g at 0.2 A/g current density, and a high energy density of 210.76 Wh/kg at the power density of 1 296 W/kg (based on active material). Furthermore, it exhibited accelerated ion diffusion kinetics within the ZiHSC device and excellent cycling stability (93.55% capacity retention after 20, 000 cycles). In situ X-ray powder diffraction (XRD) and Raman spectra revealed that the enhanced charge storage mechanism was coupled with dynamic phase transitions of Zn 4 SO 4 (OH) 6 ·5H 2 O crystallites on electrode surface and the adsorption of Zn 2+ /[Zn·(H 2 O) 6 ] 2+ into hierarchical pore channel during discharge. This study presents a novel approach for improving the structural and supercapacitive properties of activated carbon materials, demonstrating excellent potential for practical applications.
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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 | 0.000 | 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".