Properties of mLLDPE/LDPE blends in film blowing
Bibliographic record
Abstract
Abstract We evaluated the inline birefringence of two blend systems in film blowing. The first system consisted of a metallocene catalyzed linear low density polyethylene (mLLDPE‐1) and a low density polyethylene (LDPE‐1); the second one was made of a metallocene catalyzed polyethylene containing sparse long chain branches (mLLDPE‐2) and another low density polyethylene (LDPE‐2). Experimental data show that before the crystallization starts, the birefringence of the mLLDPE‐2/LDPE‐2 blends is a linear function of blend composition, suggesting miscibility of the mLLDPE‐2/LDPE‐2 blends. However, the birefringence of the mLLDPE‐1/LDPE‐1 blends shows positive deviations with respect to a linear function of blend composition. This is caused by the existence of form birefringence, suggesting immiscibility of the mLLDPE‐1/LDPE‐1 blends. The nonuniform biaxial elongational viscosity (NUBEV) at the reference temperature of 175°C for LDPE‐1 was evaluated for different operating conditions. The results show that NUBEV is approximately a unique function of the deformation rate, confirming the validity of the assumptions and technique used for the NUBEV calculation. The NUBEV and the nonuniform biaxial Trouton ratio (NUTR) of the mLLDPE‐2/LDPE‐2 blends was also evaluated using the same technique. The NUBEV of all mLLDPE‐2/LDPE‐2 blends shows a strain‐thinning behavior within the deformation rates investigated. Furthermore, the NUTR results show that LDPE‐2 deviates largely from the Newtonian fluid behavior, whereas mLLDPE‐2 is quite close to the Newtonian behavior. Nevertheless, the NUTR of the mLLDPE‐2/LDPE‐2 blends is almost a linear function of blend composition. POLYM. ENG. Sci., 45:343–353, 2005. © 2005 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 | 0.001 |
| 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 | 0.000 |
| 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".