Hybrid graphenic and iron oxide photocatalysts for the decomposition of synthetic chemicals
Bibliographic record
Abstract
Per- and polyfluoroalkyl substances (PFAS) are a group of synthetic chemicals that resist degradation, posing a significant environmental and health risk. Current methods for removing PFAS from water are often complex and costly. Here we report a simple, cost-effective method to synthesize an iron oxide/graphenic carbon (Fe/g-C) hybrid photocatalyst for PFAS degradation. This photocatalyst efficiently degrades perfluorooctanoic acid (PFOA), a common type of PFAS, achieving over 85% removal within 3 hours under ultraviolet light. The catalyst also maintains high degradation rates over extended periods, demonstrating its stability and potential for long-term use. This innovative approach offers a promising solution for addressing PFAS contamination in water, contributing to a cleaner and healthier environment. Moreira et al. developed an iron oxide/graphenic carbon hybrid photocatalyst for the decomposition of PFAS contaminants, under UV light. Their method offers a cheap and efficient alternative that achieves > 85% efficiency for PFOA decomposition under UV light.
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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 | 0.001 | 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".