Natural polymers as sustainable precursors for scalable production of <scp>N/SO<sub>x</sub></scp> doped carbon material enabling high‐performance supercapacitors
Bibliographic record
Abstract
Abstract Natural polymers‐based carbon electrodes have gained significant research attention for next‐generation portable supercapacitors. Herein, present an environmentally benign and novel approach for the synthesis of N/S‐O x carbon material derived from natural polymers on gram scale. By capitalizing the synergistic effect of sulfonated lignin and amino‐containing chitosan, this methodology produces a straightforward, low‐budget, and scalable process. The incorporation of sulfonate motifs from lignin contributes to the formation of C‐SO x moieties and multi‐porous architecture with a high surface area. Simultaneously, amino groups in chitosan induce nitrogen doping, enhancing conductivity, and wettability. The resulting N/SO x carbon material exhibits a micro/meso‐porous architecture, facilitating electrolyte diffusion, and demonstrating improved rate capability and pseudocapacitance via Faradaic redox reactions. The N/SO x carbon material showcases notable capacitance (392 F g −1 at 1 Ag −1 ) as compared with the reported carbon materials form biomass and outstanding cyclic stability (94.8% retention after 5000 cycles). By optimizing various chitosan mass ratios, the most effective N/SO x carbon material SNACM = S/N‐doped activated carbon material (SNACM‐2) was produced using a lignin: chitosan sample ratio of 1:2 for symmetric supercapacitors. Furthermore, the quasi‐solid‐state symmetric supercapacitors based on SNACM‐2 exhibit an excellent specific capacitance of 142 F g −1 at 1 A g −1 , coupled with outstanding flexibility. The SNACM‐2 demonstrates a high‐energy density of 9.8 W h kg −1 at a power density of 0.5 kW kg −1 . This study presents a successful strategy for transforming low‐valued, eco‐friendly natural polymers into renewable, high‐performance carbon materials for supercapacitors. image
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".