Effect of Random and Block Copolypropylenes on Structure and Properties of Uniaxially and Biaxially Oriented PP Films
Bibliographic record
Abstract
Abstract Cast films of two linear polypropylenes (PP) having different molecular weights and their blends with 5, 20, and 40 wt.% random and block copolymers were prepared. The produced cast films were uniaxially and biaxially hot drawn at T = 155°C using a biaxial stretcher and the changes in structure and morphology were examined and related to barrier, mechanical, haze, and tear properties. The crystallinity and crystal size distribution of the films were studied using differential scanning calorimetry (DSC). The uniaxial drawing generated a highly oriented fibrillar structure, resulting in an increase in the melting point of the films. A significant effect of the random copolymer on the size of crystallites was found using DSC, which was also confirmed from polarized optical microscopy (POM). Compared to the neat homopolymers, finer and numerous spherulites were observed for the blends. During drawing, the applied loads in the machine and transverse directions (MD and TD, respectively) were recorded and related to breaking up and tilting of the crystal lamellae. Adding the random copolymer appreciably decreased the haze of the films and hence drastically improved the clarity. Tensile properties and tear resistance of the cast films in MD and TD were evaluated. The addition of the random copolymer slightly reduced the Young modulus and tensile strength, but increased the elongation at break. A slight increase in the oxygen transmission rate (OTR) of the biaxially drawn films were observed by adding the copolymer.
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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) | 0.000 | 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 | 0.000 |
| 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".