Intermittent ultrasound‐assisted ceramic membrane fouling control in ultrafiltration
Bibliographic record
Abstract
Abstract In this study, remediation of ceramic membrane fouling by an in‐line intermittent ultrasound system was investigated. A piezoelectric ultrasonic transducer was integrated into a membrane unit that provided ultrafiltration (UF) of a diluted skim milk solution containing 0.10 wt% of protein. The effects of ultrasound at varied frequencies (20, 28, and 40 kHz) and power intensities (1.44, 2.88, and 5.76 W/cm2) under continuous operation and intermittent mode at various intervals (0.50, 1.0, 1.5, 2.0, 2.5, and 3.0 minutes) on membrane fouling were studied. The quality and flow rate of the permeate stream were monitored for the evaluation of the UF process performance. Optimal conditions of continuous ultrasound were found at 28 kHz and 2.88 W/cm2. Moreover, at optimal ultrasonic conditions, the optimal intermittent time was found at 0.50 minute. At optimal ultrasonic conditions, the permeate amount increased by 79.8% and 94.2% for 0.50 minute intermittent ultrasound and continuous ultrasound, respectively, as compared with that of the UF process without ultrasound. Also, intermittent ultrasound induced better fouling control at a lower protein concentration of 0.05% by weight. The cleaning effect of ultrasound could be attributed to the cavitation bubbles generated by the rarefaction and pressure cycles of the applied ultrasound.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".