Thickness-dependent photocatalytic performance of graphite oxide for degrading organic pollutants under visible light
Bibliographic record
Abstract
Photocatalysts use sustainable solar light energy to trigger various catalytic reactions. Metal-free nanomaterials have been suggested as cost-effective and environmentally friendly photocatalysts. In this work, we propose thickness-controlled graphite oxide (GO) as a metal-free photocatalyst, which is produced by exfoliating thick GO particles via stirring and sonication. All GO samples exhibit photocatalytic activity for degrading an organic pollutant, rhodamine B under visible light, and the thickest sample shows the best catalytic performance. UV-vis-NIR diffuse reflectance absorption spectra indicate that thicker GO samples absorb more vis-NIR light than thinner ones. Density-functional theory calculations show that GO has a much smaller band gap than that of single-layer graphene oxide, and thus suggest that the largely-reduced band gap is responsible for this trend of light absorption.
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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) | 0.000 | 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".