Chemically Bonded Ni Cocatalyst onto the S Doped g-C<sub>3</sub>N<sub>4</sub> Nanosheets and Their Synergistic Enhancement in H<sub>2</sub> Production under Sunlight Irradiation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nickel deposited S-doped carbon nitride (Ni–S:g-C3N4/Ni-SCN) nanosheets have been synthesized using calcination followed by a sulfidation process. X-ray photoelectron spectra revealed that the doped S atoms are successfully introduced into the 301 lattices of the host g-C3N4. XPS spectra indicated that the deposited Ni species are chemically bonded onto the host SCN nanosheets through sulfur bonds. The sunlight-driven photocatalytic hydrogen production efficiency of the synthesized Ni-SCN nanosheets is found to be 3628 μmol g–1 h–1, which is around 1.5 folds higher than that of Pt-SCN that synthesized in the present study. The observed efficiency is attributed to the chemical bonding of Ni through S that largely favored the photocatalytic process in terms of charge-separation as well as self-catalytic reactions. The apparent quantum efficiency of the photocatalyst at 420 nm is estimated to be 17.2%, which is relatively one of the higher values reported in the literature. The photocatalytic recyclability results showed consistent hydrogen evolution efficiency over 4 cycles (8 h) that revealed the excellent stability of the photocatalyst. This work has demonstrated that the chemical bonding of cocatalyst onto the host photocatalyst is relatively an effective strategy as compared to the conventional deposition of cocatalyst by means of electrostatic or van der Waals forces.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it