Waste bio-tar based N-doped porous carbon for supercapacitors under dual activation: performance, mechanism, and assessment
Bibliographic record
Abstract
Abstract Bio-tar extra-produced from biomass pyrolysis is prone to pose a threat to environment and human health. A novel N-doped porous electrode from bio-tar was produced under dual-activation of urea and KOH in this study. One-pot dual-activation played significant roles in N-functional group and micro-mesoporous structure, which resulted in the carbon material with the highest of nitrogen content (4.08%) and the special surface area (1298.26 m 2 ·g −1 ). Specifically, the potential mechanisms of pore formation and N-doping in the one-pot dual-activation strategy were also proposed as a consequence, the one-pot dual-activated carbon material displayed excellent electrochemical performance with the highest capacitance of 309.5 F·g −1 at 0.5 A·g −1 , and the unipolar specific capacitance remained with cyclic characteristics of 80.1% after 10,000 cycles in two-electrode symmetric system. Furthermore, the one-pot dual-activation strategy could create a profit of $1.64–$2.38 per kilogram of bio-tar processed without considering the initial investment and labor costs, which provides new perspectives for the utilization of waste bio-tar. Graphical Abstract
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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".