Efficiency Factors in Photocatalytic Reactors: Quantum Yield and Photochemical Thermodynamic Efficiency Factor
Bibliographic record
Abstract
Abstract Photocatalytic efficiency is evaluated using quantum yields (QYs) and the photochemical thermodynamic efficiency factor (PTEF). The PTEF allows establishing reactor efficiency as the ratio of utilized enthalpy for the formation of consumed OH• free radicals over the absorbed photon energy. A key consideration for the evaluation of efficiency factors is the establishment of macroscopic energy balances together with an accurate assessment of evolved and absorbed photons. Of considerable help are the experimental devices developed at the Chemical Reactor Engineering Centre (CREC)/University of Western Ontario (UWO) laboratories. Photoconversion kinetics is required for calculation of the OH• consumption rates and establishment of the related kinetic parameters. PTEFs and QYs have been applied by CREC‐UWO researchers for efficiency calculations in photocatalytic reactors for the decontamination of air, water, and hydrogen production.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".