Effect of PVDF characteristics on extruded film morphology and porous membranes feasibility by stretching
Bibliographic record
Abstract
Abstract Three different polyvinylidene fluoride (PVDF) resins were selected to develop porous membranes through melt extrusion and stretching. The effect of the polymer rheology on chain elongation in the melt state was studied. The possibility of generating a row‐nucleated lamellar crystallization for precursor films was investigated. The arrangement and orientation of the crystalline phase were examined by wide angle X‐ray diffraction (WAXD) and Fourier Transform Infrared Spectroscopy (FTIR). The extrusion conditions and the blend compositions were adjusted to obtain uniform precursor films with appropriate morphology. Annealing, cold and hot stretching were consequently employed to generate and enlarge the pores. It was found that a proper crystalline structure of the precursor films was strongly dependent on molecular weight of PVDF and process conditions. Blending of two PVDF resins having low and high molecular weights improved the water vapor permeability of the obtained membranes. The tensile response was monitored during the stretching process for membrane development and the results revealed a distinct behavior for the membranes having low or high permeability. The membranes with low permeability did not show any significant strain hardening during stretching whereas for highly permeable membranes, a noticeable strain hardening behavior was observed. © 2009 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 47: 1219–1229, 2009
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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 | 0.001 |
| 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".