Disinfection and advanced oxidation of highly absorbing fluids by UV/VUV light: process modeling and validation
Bibliographic record
Abstract
One of the limitations in treating highly absorbing fluids with ultraviolet photoreactors is the short light penetration into the fluid leading to the following issues: (a) if not engineered properly, ultraviolet photoreactors dealing with highly absorbing fluids are likely to be energy-inefficient due to a non-ideal use of emitted photons and non-uniform dose distribution (b) the quantification of photo-chemical rate constants could be a challenging task due to the severe mixing-limited conditions of the experimental apparatus used during the investigation. As a result, new lab-scale apparatus (alternative to the conventional collimated beam system) and modeling approaches are needed in order to overcome such technical limitations.\nThe aim of this thesis is two-fold: firstly, to develop and validate lab-scale apparatus and standard operating procedures suitable for investigating the disinfection and the advanced oxidation processes (AOPs) initiated by short-penetrating wavelengths; secondly, to apply such newly developed methodologies for quantifying microbial inactivation kinetics in liquid foods by 253.7 nm light as well as total organic carbon (TOC) removal from ultrapure water by Vacuum-UV-initiated (VUV) AOPs employing the 172 and the 185 nm wavelengths.\nFor quantifying microbial inactivation kinetics in liquid foods, a Taylor-Couette (TC) apparatus can be used for fluids with ultraviolet transmittance as low as ~0.001% cm-1. A computational fluid dynamics (CFD) model was used to optimize the TC system, indicating that a Taylor number of ~46,500 was sufficient to overcome the very short UV light penetration.\nFor the TOC removal from ultrapure water by AOPs employing VUV light a mechanistic VUV-AOP model was developed by incorporating the vacuum UV-AOP kinetics into the theoretical framework of in-series continuous stirred tank reactors (CSTRs). Experimental trials were conducted using an annular photoreactor equipped with VUV lamps able to emit the 185 nm and 172 nm radiation revealed that, at the investigated conditions, the 185 nm AOP process gave three times better TOC degradation performance than the 172 nm AOP process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".