Rheological study of the influence of branch content on the miscibility of octene m‐LLDPE and ZN‐LLDPE in LDPE
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The influences of branch content on the miscibility of octene LLDPE made by metal‐locene catalyst (m‐LLDPE) and by Ziegler‐Natta LLDPE (ZN‐LLDPE) in LDPE were investigated with rheological methods. Dynamic and steady shear measurements were carried out in a Rheometrics Mechanical Spectrometer 800. Here, m‐LLDPEs were used to isolate interaction of molecular parameters. Blends of octene m‐LLDPE and ZN‐LLDPE with LDPE were mixed at 190°C in the presence of an adequate amount of antioxidant. The miscibilities of blends were revealed by the dependence of their measured η o , η′ and G ′ on blend composition as well as on agreement with predictions of different emulsion models. Blends of m‐LLDPE with LDPE were found to be almost miscible in the LLDPE branching range 10–30 branches/1000 C. However, immiscibility was found to develop at lower LLDPE branch contents. For ZN‐LLDPE/LDPE systems, branch content plays a significant role especially at low branch contents. The comparison of m‐LLDPE and ZN‐LLDPE systems suggest the strong influence of branch distribution (uniform and random, respectively). Palierne, Bousmina, and Scholz models fitted the loss and storage moduli data well with a value of α/R in the range 10 3 −10 4 N/m 2 . Polym. Eng. Sci. 44:660–672, 2004. © 2004 Society of Plastics Engineers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it