Morphological and mechanical properties of nascent polyethylene fibers produced via ethylene extrusion polymerization with a metallocene catalyst supported on MCM‐41 particles
Bibliographic record
Abstract
Abstract Polyethylene (PE) fibers were prepared by ethylene extrusion polymerization with an MCM‐41‐supported titanocene catalyst. The morphological and mechanical properties of these nascent PE fibers were investigated. Three levels of fibrous morphologies were identified in the fiber samples through an extensive scanning electron microscopy study. Extended‐chain PE nanofibrils with diameters of about 60 nm were the major morphological units present in the fiber structure. The nanofibrils were parallel‐packed into individual microfibers with diameters of about 1–30 μm. The microfibers were further aggregated irregularly into fiber aggregates and bundles. In comparison with commercial PE fibers and data reported in the literature, the individual microfibers produced in situ via ethylene extrusion polymerization without posttreatment exhibited a high tensile strength (0.3–1.0 GPa), a low tensile modulus (3.0–7.0 GPa), and a high elongation at break (8.5–20%) at 35 °C. The defects in the alignment of the nanofibrils were believed to be the major reason for the low modulus values. It was also found that a slight tensile drawing could increase the microfiber strength and modulus. © 2003 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 41: 2433–2443, 2003
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.
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".