Pyrolysis-assisted synthesis of two-dimensional graphitic carbon nitride nanosheets embedded with transition metal oxide (Ni or Fe) for high-performance asymmetric supercapacitors
Bibliographic record
Abstract
This study employed a one-step pyrolysis-assisted technique to successfully synthesized with two different transition metal oxides (M = Ni, Fe) embedded on graphitic carbon nitride nanosheets (g-C 3 N 4 -NS). The resulting nanocomposites exhibit exceptional electrochemical performance in supercapacitor applications due to various parameters such as morphology, specific surface area and crystallinity. Notably, the NiO/g-C 3 N 4 -NS and Fe 2 O 3 /g-C 3 N 4 -NS electrodes simplify the Faradaic reactions and achieve the maximum capacitance of 816 F g −1 and 703 F g −1 at 0.5 A g −1 , respectively. Additionally, these electrodes demonstrate superior cycling stability, retaining approximately 96 % of their capacity retention after 5000 cycles. Furthermore, the NiO/g-C 3 N 4 -NS//AC and Fe 2 O 3 /g-C 3 N 4 -NS//AC devices exhibit promising supercapacitor device performance, yielding respectable specific capacity of 53 F g −1 (NiO/g-C 3 N 4 -NS//AC) and 43.5 F g −1 (Fe 2 O 3 /g-C 3 N 4 -NS//AC) at 0.5 A g −1 , underscoring the commendable rate capability of the asymmetric electrodes and the energy densities of 19 Wh kg −1 and 16 Wh kg −1 at a power density of 400 W kg −1 , respectively. These findings underscore the potential of metal oxide/g-C 3 N 4 -NS composites as an electrode material for power storing applications, as demonstrated by these asymmetric supercapacitor devices.
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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".