Morphology Control of Polysulfone Membranes in Filtration Processes: a Critical Review
Bibliographic record
Abstract
Abstract Polysulfone (PSU) membranes have been widely applied in microfiltration and ultrafiltration processes due to their excellent properties, such as chemical inertness across the entire pH range, compressive strength, and thermal stability. Despite these advantages, the application of PSU membranes in filtration processes has often been restricted due to their hydrophobic nature, which results in serious membrane fouling and a reduced permeate flux. Moreover, PSU membranes suffer from several disadvantages, including bulky structure, low binding force between fibers, and poor mechanical properties. The key factor in the development and application of polymeric membranes is the control of its polymeric morphology due to the significant influence of membrane morphology on the membrane performance. Effective techniques of controlling PSU membrane morphology are accessed, and the effects of the morphological control on mechanical properties, chemical stability, membrane performance, and membrane fouling are investigated. Findings from various individual studies were analyzed and discussed in order to provide a critical review of this subject. The results emphasized that the membrane pore size and surface porosity mostly governs PSU membrane morphology, which enhances membrane performance and reduces membrane fouling.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".