Ultrafiltration of oil-in-water emulsion: Comparison of ceramic and polymeric membranes
Bibliographic record
Abstract
Ultrafiltration (UF) has been recognized as a highly attractive technique for the treatment of stable oil-in-water emulsions. This technique has proved to be more effective then conventional methods since it may produce a water phase of higher quality and an oil phase which can be recycled. However, low permeate fluxes due to membrane fouling still represent one of the main limitations for its extensive application. The aim of this paper is to further contribute to the investigations of mass transfer characteristics during UF of oil-in-water emulsions. The performance of a polymeric (polyaryletherketone) membrane and a ceramic (zirconia) membrane were compared under different parameters of the UF process. The permeate recirculation experiment showed that the ceramic membrane is sensitive to oil penetration at lower cross-flow velocities and higher transmembrane pressures. The optimal performance for the ceramic membrane was obtained at a lower feed flow rate and transmembrane pressure compared to the optimal values for the polymeric membrane. The comparison experiments with volumetric concentration of the feed were carried out at optimal operation conditions for each of the membranes in order to maximise their performance. While the polymeric membrane showed expected oil rejection variation consistent with surface layer formation, the ceramic membrane showed poor oil rejection at the beginning of the operation. Further investigations need to show if the poor initial oil rejection of the ceramic membrane can be reduced without losing proved advantages of ceramic membranes over polymeric membranes.
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".