Evaluation of Photon Absorption in an Aqueous TiO<sub>2</sub> Slurry Reactor Using Monte Carlo Simulations and Macroscopic Balance
Bibliographic record
Abstract
The radiation field in an annular photocatalytic reactor is simulated using a Monte Carlo method (MC) for two TiO 2 suspensions in water. Simulations are performed by using both the spectral distribution and the wavelength-averaged scattering and absorption coefficients. The Henyey−Greenstein phase function is adopted to represent forward, isotropic, and backward scattering modes. It is assumed that the UV lamp reflects the backscattered photons by the slurred medium. Photoabsorption rates using MC simulations and spectral distribution of the optical coefficients agree closely with experimental observations from a macroscopic balance. It is found that the scattering mode of the probability density function is not a critical factor for a consistent representation of the radiation field. MC simulation for the optimal catalyst concentration reveals that the maximum LVREA is reached at a concentration of 0.14 g L −1 for TiO 2 Degussa P25. From this concentration, the apparent optical thickness is determined to be 2.8476 which is in agreement with the optimal one previously reported. This concentration is comparable to that determined experimentally for phenol photocatalytic degradation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".