Ultrafiltration of oily waste water: Contribution of surface roughness in membrane properties and fouling characteristics of polyacrylonitrile membranes
Bibliographic record
Abstract
The present study focuses on the contribution of surface roughness to properties of polyacrylonitrile (PAN) membranes and its fouling during ultrafiltration (UF) of used engine oil. Nine membranes were cast using varying polymer concentration, molecular masses of hydrophilic additive polyethylene glycol (PEG), and concentration of PEG. Surface roughness decreased from 35 to 10 nm with polymer concentration in the range 0.01–0.15 g/g (1–15 wt %). Surface roughness increased from 8 to 42 nm as the molecular mass of PEG increased from 200 to 20 000 g/mol. Increasing concentration of PEG from 0.5 to 0.12 g/g (5 to 12 wt %) increased the surface roughness from 11 to 26 nm. Three membranes were identified as having permeate flux above 45 L/m 2 · h and oil rejection beyond 90 %. The membrane hydrophilically modified by 0.08 g/g (8 wt %) PEG 400 showed the best antifouling performance. The flux decline ratio for this membrane was the lowest between 10–20 % and the flux recovery ratio was above 90 % for oil concentrations between 100–1000 mg/L at 276 kPa transmembrane pressure (TMP). Permeate concentration was between 2–12 mg/L (well within permissible levels) corresponding to oil concentrations from 100–1000 mg/L in the feed at the same TMP. Permeation of oil is lower (hence higher rejection) at higher feed concentrations, indicating the agglomeration of oil in the retentate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".