Microporous membranes obtained from polypropylene blends with superior permeability properties
Bibliographic record
Abstract
Abstract A blend of two polypropylene resins, different in molecular structure, one with linear chains and the other with long chain branches, was investigated to develop microporous membranes through melt extrusion (cast film process) followed by film stretching. The branched component significantly affected the row‐nucleated lamellar crystalline structure in the precursor films. The arrangement and orientation of the crystalline and amorphous phases were examined by wide angle X‐ray diffraction and Fourier transform infrared spectroscopy methods. It was found that blending of a small amount of a long chain branched polypropylene improved the orientation of the both crystalline and amorphous phases in the precursor films. Annealing, followed by cold and hot stretching were consequently employed to generate and enlarge pores in the films as a result of lamellae separation. SEM micrographs of the surface of the membranes obtained from the blend revealed elongated thin fibrils and a large number of lamellae. The lamellae thickness for the blend was much shorter in comparison to that of the linear PP precursor film. The permeability of the samples to water vapor and N 2 was significantly enhanced (more than twice) for the blend system. The porosity of the blend membrane showed a significant improvement with a value of 53% compared to 41% for the linear PP membrane. © 2007 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 46: 148–157, 2008
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".