Plasmon Enhanced Photocatalysis with Group IV Metal Nitride and TiO2 Composites: Rhodamine B Dye Degradation Case Study
Bibliographic record
Abstract
Traditional photocatalysis often employs TiO2 for its affordability and safety, but its large bandgap (>3 eV) limits solar absorption to under 5%. Plasmonic materials serve as sensitizers to expand absorption into the visible and near-IR spectrum while generating localized electromagnetic fields, hot carriers, and heat to boost catalytic efficiency. While noble metals have been extensively studied for visible light absorption, their high cost and poor oxidative stability have spurred interest in alternative plasmonic materials. Transition metal nitrides, such as TiN, ZrN, and HfN, offer strong absorption in the visible and near-IR regions and are cost-effective. In this study, TiN, ZrN, and HfN were combined with traditional P25 TiO2 to yield composite materials and their photocatalytic activity was evaluated by monitoring rhodamine B dye degradation. Under optimized conditions and 100 mW cm-2 illumination, degradation efficiencies of 96, 71, and 99% were observed for TiN/TiO2, ZrN/TiO2, and HfN/TiO2, respectively. Reaction temperature and power density studies allude to reaction efficiency enhancement due to a hot carrier driven process in TiN/TiO2 and ZrN/TiO2 systems. In the case of HfN/TiO2, photothermal contributions are likely to be significant.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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 teacher head, 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".