A Literature Review of Ultrasound Technology and Its Application in Wastewater Disinfection
Bibliographic record
Abstract
Abstract In recent years, there has been an increase in the application of ultraviolet (UV) light as an alternative to chemical disinfection technologies. However, in the case of poor quality effluents, the practical limit of UV disinfection of wastewater is dictated by disinfection-resistant, particle-associated bacteria. Although these particles may be removed by filtration, an alternative method to reduce the impact of suspended particles on disinfection efficiency is to decrease particle size using ultrasound technology. Mechanical forces exerted on particles due to the collapse of cavitation bubbles created by sonication break suspended particles into small fragments. In this paper, a critical review of ultrasound application for wastewater treatment is presented with emphasis on disinfection. Much of the work in this area remains at the laboratory scale. As a result, there is a need for fundamental information regarding the effect of sonication on the kinetics of disinfection and interaction of ultrasound with suspended particles. Such information is necessary for process engineering, design, and scale-up of ultrasound systems.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".