Study of the effect of branch content of octene‐based linear low‐density polyethylene on its melt miscibility with high‐density polyethylene by inverse gas chromatography
Bibliographic record
Abstract
Abstract Inverse gas chromatography was used to measure Flory–Huggins interaction parameters (χ23) for five binary blends consisting of high‐density polyethylene (HDPE) and octene‐based linear low‐density polyethylene (LLDPE) with different compositions at four elevated temperatures. The branch content of the LLDPE used in each pair of the blends ranged from 2 to 87 branches per 1000 backbone carbons. To obtain solvent‐independent χ23, the data analysis approach recently proposed by Zhao and Choi (Polymer 2001, 42, 1075) was used. The results indicate that the higher the branch content of LLDPE, the higher the measured χ23, signifying that HDPE/LLDPE blends with low branch content LLDPEs are relatively more miscible than those with high branch contents. In particular, when the branch content of LLDPE is higher than 50 branches per 1000 backbone carbons, phase separation may occur. This result is in good agreement with other researchers' results obtained from different techniques. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 91: 1927–1931, 2004
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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".