Kinetic modeling of the photocatalytic degradation of air‐borne pollutants
Bibliographic record
Abstract
Abstract The photocatalytic conversion of organic model pollutants (acetone, acetaldehyde, and isopropanol) in a novel Photo‐CREC‐Air unit is considered. This photocatalytic unit features: (1) external near‐UV lamps placed in parabolic reflectors, (2) a basket supporting the irradiated glass mesh holding TiO 2 loadings to achieve high photoconversion rates, and (3) a fluid flow pattern securing high gas velocities in the near‐mesh region. Given the high quantum efficiencies observed in Photo‐CREC‐Air and, as a result, the high prospects for this novel design, rate equations and associated mechanistic formulations are investigated. With this goal, a Langmuir–Hinshelwood model, involving a one‐site model pollutant mechanism, is considered. The associated kinetic parameters with the related statistical indicators are established, using least‐square nonlinear regression. It is found that this model is adequate for describing the photodegradation of acetone on both Degussa P25 and Hombikat UV‐100. It is also observed that the same type of reaction rate model is less adequate for the photodegradation of acetaldehyde and isopropanol, in particular, for predicting the formation of carbon dioxide. © 2004 American Institute of Chemical Engineers AIChE J 50: 1017–1027, 2004
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".