A Comparison of Commercial and Experimental Ultrafiltration Membranes via Surface Property Analysis and Fouling Tests
Bibliographic record
Abstract
Abstract Surface modified polyethersulfone (PES) membranes via the addition of different hydrophiLic Surface Modifying Macromolecules (LSMMs) have been developed by Matsuura, Narbaitz and co-workers. This study compares the performance of the best PES-LSMM membrane with nine commercial ultrafiltration membranes manufactured using five different types of base polymers (polyethersulfone, polysulfone, celluloseacetate, polyacrylonitrile and cellulose) in the same range of molecular weight cutoff (MWCO) (from 40 to 120 kDal). All membranes were characterized by using atomic force microscopy, contact angle measurements, solute transport analysis and then evaluated through fouling tests with Ottawa River water (ORW). While PES-LSMM membranes had much lower initial flux than the commercial membranes, they had the highest total organic carbon (TOC) rejection (80%) and the lowest flux reduction (62%). For the commercial membranes, the range of TOC rejections and flux reductions were 62 to 80% and 68 to 80%, respectively. Given their high TOC rejection and relatively high foulant deposition, fouling of the PES-LSMM membranes appears to be controlled by a surface gel.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".