Role of C<i><sub>x</sub></i>N<i><sub>y</sub></i>‐Triazine in Photocatalysis for Efficient Hydrogen Generation and Organic Pollutant Degradation Under Solar Light Irradiation
Bibliographic record
Abstract
A critical drawback of existing materials, which restricts the photocatalytic efficiency, is the fast recombination of charge carriers. To address this challenge, loading reduction and oxidation co‐catalysts on two opposite surfaces of a hollow semiconductor is a critical approach to improve the photocatalytic performance. These co‐catalysts mainly act as oxidation and reduction active sites, while suppressing the charge recombination. Moreover, the development of a novel and efficient co‐catalyst that boosts charge separation is a very important feature for the photocatalytic performance. Herein, we report the first synthesis of hollow Pt/TiO2/CxNy‐triazine nanocomposite using carbon colloidal spheres as a hard template, in which Pt and CxNy‐triazine are located on the two opposite hollow surfaces. CxNy‐based triazine species formed from cyanamide during calcination do not only stabilize the hollow structure and significantly enhance the surface area of Pt/TiO2/CxNy‐triazine, but also act as an efficient oxidation co‐catalysts. This new type of nanocomposite exhibits one of the best TiO2‐based photocatalysts working under solar light irradiation to date. It is 125 and 62 times higher than that of Pt/TiO2–P25 for hydrogen generation and methanol decomposition, respectively.
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.
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".