Influence of ultrasonic waves on the removal of different oil components from oily sludge
Bibliographic record
Abstract
Ultrasonic technology is a promising tool for washing oily sludge to recover oil. In this study, the influence of ultrasonic conditions on the removal of different oil components from oily sludge was investigated to optimize ultrasonic washing technology. Among the three frequencies (25, 50 and 100 kHz) applied, ultrasonic washing at 25 kHz exhibited the best performance in terms of oil extraction rate and efficiency. An ultrasonic intensity of 0.33 W/cm2 was necessary to overcome the energy threshold for oil washing. Application of a standing wave or dual frequencies did not improve the oil removal performance perceptibly. The optimum conditions for the removal of oil from oily sludge were an ultrasonic frequency of 25 kHz, intensity of 0.33 W/cm2 and sludge/water ratio of 1/2 (in volume). Thin-layer chromatographic flame ionization detection showed that ultrasonication could overcome high energy thresholds, resulting in an increase in the removal of asphaltenes and resins, with the removal of asphaltenes particularly affected by frequency. This study could provide valuable information for the application of ultrasonic technology in oily sludge treatment.
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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 | 0.000 | 0.001 |
| 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".