A corrugated plate photocatalytic reactor for degradation of waterborne organic contaminants
Bibliographic record
Abstract
Abstract A UV‐C/titanium dioxide (TiO2) plate coated photocatalytic reactor using a corrugated frame system was designed for water borne organic contaminant degradation. The anticipated advantages of using the corrugated layout include a larger photocatalytic surface area per unit volume and improved photocatalytic activity. The water distribution system was designed to assist effective interactions among the water pollutant, photocatalyst, and photons. The degradation of a methylene blue solution, as a model water contaminant, was carried out at room temperature (22 °C) at different concentrations and flowrates. With an 11 mg/L methylene blue solution, 70 % was degraded within the first 10 min using TiO2 coated corrugated plates, whereas under the same conditions the degradation rate was only 12 % for a corrugated reactor without a catalyst coating, and 4 % for a no‐plate reactor. The methylene blue degradation was described by the Langmuir‐Hinshelwood model, and the apparent photonic efficiency of the corrugated arrangement was found to be in the range of 1.53–2.83 % when half the initial concentration was degraded. The local area specific rate of energy absorption (LASREA) profile over the plates was determined from a model developed based on UV‐C light irradiation distribution and plate configuration. Light intensity measurements were carried out and were found to correlate with this model. A set of corrugated plate photocatalytic reactors with different geometries, but with the same coated area, were then analyzed and absorbed UV light intensities were integrated to determine the best geometry.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".