Synthesis of g‐C<sub>3</sub>N<sub>4</sub> Nanosheets by Using a Highly Condensed Lamellar Crystalline Melamine–Cyanuric Acid Supramolecular Complex for Enhanced Solar Hydrogen Generation
Bibliographic record
Abstract
Abstract A highly condensed lamellar melamine–cyanuric acid supramolecular (MCS) complex was synthesized in an autoclave at high pressure as a precursor for preparing g‐C 3 N 4 nanosheets. Given the distinctive properties of the prepared MCS complex, an efficient g‐C 3 N 4 nanosheet photocatalyst can be obtained by heat treatment of this MCS complex under Ar followed by calcination in air at 400 °C. The resulting nanosheets with in‐plane nanoholes showed an extremely high specific surface area (≈270 m 2 g −1 ) and significantly enhanced light absorption in the visible region. This phenomenon is observed for the first time in carbon nitride nanosheets. The enhanced light absorption results from the sizeable conjugated system of tri‐striazine units in the carbon nitride framework, coupled with the structural defects arising from the presence of oxygen‐containing groups induced during the synthesis. Consequently, the obtained carbon nitride nanosheets exhibited excellent performance for hydrogen generation under sunlight and especially under visible light. Its quantum efficiency (QE) of 20.9 % at 420 nm is one of the highest reported values for carbon nitride materials. A QE of 3.5 % could be observed even at 590 nm. The integrated QE of this material in the visible region (420–600 nm) is approximately 1 %. To the best of our knowledge this is the highest value compared to all other the carbon nitride nanosheet materials reported previously.
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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) | 0.001 | 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".