Nitrogen‐Doped Graphene Nanosheets/S Composites as Cathode in Room‐Temperature Sodium‐Sulfur Batteries
Bibliographic record
Abstract
Abstract Room‐temperature sodium‐sulfur (RT Na−S) batteries have gained increasing attention from energy storage community in recent years. In this work, homogeneous nitrogen‐doped graphene nanosheets/sulfur (NGNS/S) nanocomposites, synthesized using chemical reaction‐deposition method and low temperature heat treatment, were studied as active cathode materials for RT Na−S batteries. Different loading composites with 86%, 65%, 45% and 25% gamma‐S 8 have been electrochemically evaluated, respectively, and compared with two control electrodes of NGNS and S. It was found that the NGNS/S composite with 25% S loading exhibited the best electrochemical performance with specific capacities of 212 and 136 mAh g −1 in the 1st and 10th cycles, respectively. The enhanced electrochemical performance of NGNS/S nanocomposite is mainly attributed to the improved kinetics due to the NGNS conductive network and easier intercalation of Na + into expanded NGNS layers due to the addition of S within the graphene layers. In addition, the composite with 25% S loading shows higher surface area and complete reaction with product of Na 2 S, which likely contributes to the improved energy capacity.
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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) | 0.000 | 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 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".