Impact of Membrane Surface Modification on the Treatment of Surface Water
Bibliographic record
Abstract
New polyethersulfone (PES) based membranes for ultrafiltration (UF) were developed by blending a surface-modifying macromolecule (SMM) in the casting solution, in an attempt to minimize the impact of fouling. Fouling was evaluated using concentrated Ottawa River water (CORW), either unfractionated or fractionated via UF. These membranes also included some polyvinylpyrrolidone (PVP), a pore forming additive. A statistical analysis was conducted to evaluate the impact of some variables on the treatment of the surface water. The independent variables included PVP/PES ratio in the casting solution, with and without SMM, and the nature of the feed CORW [low molecular weight (LMW) fraction, unfractionated, high molecular weight (HMW) fraction]. The performance variables studied were total organic carbon (TOC) removal, the foulant accumulation at the membrane surface after filtration, the flux reduction, and the final permeate flux. The most important variable was the feed water. Filtration of LMW had a higher final flux, less fouling, but slightly lower TOC removal. The SMM did not significantly impact the membrane performance. TOC removal was high, compared with results reported in the literature for UF membranes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".