Engineering the Pores of Biomass‐Derived Carbon: Insights for Achieving Ultrahigh Stability at High Power in High‐Energy Supercapacitors
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Electrochemical supercapacitors with high energy density are promising devices due to their simple construction and long‐term cycling performance. The development of a supercapacitor based on electrical double‐layer charge storage with high energy density that can preserve its cyclability at higher power presents an ongoing challenge. Herein, we provide insights to achieve a high energy density at high power with an ultrahigh stability in an electrical double‐layer capacitor (EDLC) system by using carbon from a biomass precursor (cinnamon sticks) in a sodium ion‐based organic electrolyte. Herein, we investigated the dependence of EDLC performance on structural, textural, and functional properties of porous carbon engineered by using various activation agents. The results demonstrate that the performance of EDLCs is not only dependent on their textural properties but also on their structural features and surface functionalities, as is evident from the electrochemical studies. The electrochemical results are highly promising and revealed that the porous carbon with poor textural properties has great potential to deliver high capacitance and outstanding stability over 300 000 cycles compared with porous carbon with good textural properties. A very low capacitance degradation of around 0.066 % per 1000 cycles, along with high energy density (≈71 Wh kg −1 ) and high power density, have been achieved. These results offer a new platform for the application of low‐surface‐area biomass‐derived carbons in the design of highly stable high‐energy supercapacitors.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it