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 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 | 0.000 |
| 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 | 0.000 |
| 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 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".