An Investigation Into The Fouling Phenomena Of Polycarbonate Membranes Used In The Treatment Of Latex Paint Wastewater
Bibliographic record
Abstract
The treatment of latex paint wastewater with ultrafiltration allows for the reuse of the filtrate as process water or for cleaning purposes, as well as the potential for reclamation of the valuable paint solids. In this study, the utilization of polycarbonate membranes for the ultrafiltration of dilute latex dispersions was evaluated. Hydrophilic, flat sheet ultrafiltration membranes with a mean pore size of 0.1 μm were used. All filtration experiments were conducted under constant pressure operation, in a circular, centre-fed, cross-flow filtration cell. The effect of feed flow rate was investigated, and the steady-state permeate flux achieved showed an increase of 294% between 1.0 and 3.0 L/min. Increasing the operating pressure also resulted in an increased permeate flux, with a 320% increase from 1.5 to 5.5 psi. Also considered was the effect of the feed solid concentration on the permeate flux. When compared to the clean water flux (0% solids) of 5.5×10- Surfactant-enhanced ultrafiltration was also studied, with concentrations ranging from 25% to 200% of the literature values of the surfactant's critical micelle concentration (CMC) in pure water. The addition of an anionic surfactant, sodium dodecyl sulphate (SDS), reduced the effectiveness of the filtration. However, the addition of a cationic surfactant, cetyl trimethylammonium bromide (CTAB), increased the permeate flux of the latex dispersion up to 130% when twice its CMC was used, with evidence of a reduction in the effect of fouling of the membranes. This may be due to repelling interactions between the surface of the membrane and the surface of the formed micelles, as well as a reduced cake resistance due to the larger particle size of the constituents forming a less dense cake layer.
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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 | 0.001 | 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".