A novel approach to interpret quasi-collimated beam results to support design and scale-up of vacuum UV based AOPs
Bibliographic record
Abstract
UV-C at 254 nm and vacuum UV (VUV) at 185 nm are the two major emission lines of a low-pressure mercury lamp. Upon absorption of VUV photons, water molecules and selected inorganic anions generate hydroxyl (HO . ) and other redox radicals, both capable of degrading organic micropollutants (OMPs), thereby offering the opportunity to reduce H 2 O 2 and energy consumption in UV-based advanced oxidation process (AOP). To be successfully scaled-up, the dual-wavelength VUV+UV/H 2 O 2 AOP requires laboratory-scale experiments to establish design criteria. The figures of merit typically used for reporting and interpreting quasi-collimated beam results for UV-based AOPs (time, dose, absorbed energy and E EO ) are insufficient and inaccurate when employed for dual-wavelength AOP such as the VUV+UV/H 2 O 2 AOP, and do not support system scale-up. In this study, we introduce a novel figure of merit, useful absorbed energy (uAE), defined as fraction of absorbed energy that results in the generation of oxidative radicals. Here, results of quasi-collimated beam VUV+UV/H 2 O 2 AOP experiments on four different water matrices are used to introduce 2D plots that employ both uAE UV and uAE VUV as a novel method to represent laboratory-scale experiments of VUV+UV/H 2 O 2 AOP and demonstrate how the 2D plots sufficiently support scale-up of the AOP.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".