Energy Efficiencies in a Photo-CREC-Air Reactor: Conversion of Model Organic Pollutants in Air
Bibliographic record
Abstract
The energy efficiency of the photocatalytic conversion of gas-phase organic pollutants was studied using a redesigned and scaled-up photo-CREC-air reactor. This photocatalytic unit has the unique feature of allowing an accurate analysis of the irradiation field by establishing macroscopic balances and in situ measurements. The photo-CREC-air reactor operates in batch mode with the photocatalyst supported by a stainless steel mesh being irradiated by eight UV lamps. Kinetic modeling was performed, and quantum yields (QYs) and photochemical thermodynamic efficiency factors (PTEFs) were calculated using data for acetone and acetaldehyde photocatalytic degradation in ambient air utilizing a Degussa P25 (Aeroxide 25) photocatalyst. It was found that the photo-CREC-air reactor is suitable for the determination of kinetic and adsorption parameters, given a design with excellent irradiation usage and fluid–catalyst contact. In this respect, quantum yields for both acetone and acetaldehyde exceed the value of 1 (equivalent to 100%), with PTEFs in both cases remaining below the level of 1, as required by thermodynamics.
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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 | 0.001 | 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 | 0.000 | 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".