Enhanced Photocatalytic Property of Reduced Graphene Oxide/TiO<sub>2</sub> Nanobelt Surface Heterostructures Constructed by an In Situ Photochemical Reduction Method
Bibliographic record
Abstract
A facile method is proposed to assemble graphene oxide (GO) on the surface of a TiO2 nanobelt followed by an in situ photocatalytic reduction to form reduced graphene oxide (rGO)/TiO2 nanobelt surface heterostructures. The special colloidal properties of GO and TiO2 nanobelt are exploited as well as the photocatalytic properties of TiO2 . Using water-ethanol solvent mixtures, GO nanosheets are tightly wrapped around the surface of the TiO2 nanobelts through an aggregation process and are then reduced in situ under UV-light irradiation to form rGO/TiO2 nanobelt surface heterostructures. The heterostructures enhance the separation of the photoinduced carriers, which results in a higher photocurrent due to the special electronic characteristics of rGO. Compared to TiO2 nanobelts, the rGO/TiO2 nanobelt surface heterostructures possess higher photocatalytic activity for the degradation of methyl orange and for the production of hydrogen from water, as well as excellent recyclability, with no loss of activity over five cycles.
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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".