Photodegradation Efficiencies in a Photo-CREC Water-II Reactor Using Several TiO <sub>2</sub> Based Catalysts
Bibliographic record
Abstract
Abstract This study reports phenol degradation using several TiO 2 photocatalysts (DP25, Anatase 1, Hombikat UV-100, Anatase 2) in a Photo-CREC Water-II Reactor. The physicochemical properties of the photocatalysts used, such as crystallinity, superficial area, and pore size distribution are reported. Reactor efficiencies are calculated using both Quantum Yields (QYs) and Photochemical and Thermodynamic Efficiency Factors (PTEFs). This is accomplished using phenol and phenol intermediate photoconversion rates. This allows the determination of hydroxyl radical consumption rates, at every step of the photodegradation process. With these data, and with the absorbed photon rates, energy efficiencies are calculated. It is shown that for the best performing photo catalysts the maximum QYs reach 50 % levels. These favourable photoconversion efficiencies confirm the critical importance of having available highly performing photocatalysts and photoreactors, such is the case of Photo-CREC Water-II Reactor unit.
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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 | 0.001 |
| 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".