Performances of poly(vinylidene fluoride‐<i>co</i>‐hexafluoropropylene) ultrafiltration membranes modified with poly(vinyl pyrrolidone)
Bibliographic record
Abstract
The structure and performance of modified poly(vinylidene fluoride‐co‐hexafluoropropylene) (PVdF‐co‐HFP) ultra‐filtration membranes prepared from casting solutions with different concentrations of poly(vinyl pyrrolidone) (PVP) were investigated in this study. Membrane properties were studied in terms of membrane compaction, pure water flux (PWF), water content (WC), membrane hydraulic resistance (Rm), protein rejection, molecular weight cut‐off (MWCO), average pore size, and porosity. PWF, WC, and thermal stability of the blend membranes increased whereas the crystalline nature and mechanical strength of the blend membranes decreased when PVP additive concentration was increased. The contact angle (CA) decreased as the PVP concentration increased in the casting solution, which indicates that the hydro‐philicity of the surface increased upon addition of PVP. The average pore size and porosity of the PVdF‐co‐HFP membrane increased to 42.82 Å and 25.12%, respectively, when 7.5 wt% PVP was blended in the casting solution. The MWCO increased from 20 to 45 kDa with an increase in PVP concentration from 0 to 7.5 wt%. The protein separation study revealed that the rejection increased as the protein molecular weight increased. The PVdF‐co‐HFP/PVP blended membrane prepared from a 7.5 wt% PVP solution had a maximum flux recovery ratio of 74.3%, which explains its better antifouling properties as compared to the neat PVdF‐co‐HFP membrane. POLYM. ENG. SCI., 55:2482–2492, 2015. © 2015 Society of Plastics Engineers
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".