Evaluation of Radiation Absorption in Slurry Photocatalytic Reactors. 1. Assessment of Methods in Use and New Proposal
Bibliographic record
Abstract
Photocatalytic reactions are the result of a light-activated process by which an appropriate semiconductor can generate electrons and holes that, afterward, can participate in oxidative−reductive reactions. One of the most important applications of these processes consists of the use of these catalytic systems for oxidizing pollutants contained in water and air systems. In these photocatalytic reactions, the initiation step is always a function of the local volumetric rate of photon absorption (LVRPA). Many of these reactions are carried out in water environments where the catalyst is a suspension of small size, solid particles. Then the system is heterogeneous, and evaluation of the light distribution becomes difficult due to the concomitant presence of radiation absorption and scattering. In this paper, we present a general theoretical frame for analyzing the different methods that have been proposed to evaluate the LVRPA. Using this approach, one can have a precise knowledge and evaluation of the assumptions that are used in each method and can critically discuss their validity. Special emphasis is put in the description of rigorous procedures that account for a complete solution of the radiative transfer equation. It is shown that in order to properly compute reaction quantum yields (or quantum efficiencies for polychromatic light) scattering should always be taken into account; otherwise, large errors can be introduced. The same conclusions are valid for scaling-up slurry-type photocatalytic reactors.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".