Morphology and coalescence of ethylene copolymers: Influence of thermal treatments and sorbitol nucleating agents
Bibliographic record
Abstract
Abstract Coalescence of polymer particles is a key phenomenon in many powder processing technologies. Both the extent and the rate of coalescence between particles govern the production cycle and the performance of the end‐product. It is well accepted that both processing conditions and material formulation affect the morphology of molded parts and consequently their mechanical properties. The interest of this study is to evaluate the impact that changes in morphological features caused by the imposition of different thermal treatments as well as by the addition of a nucleating agent (bis 3,4 dimethylbenzylidene sorbitol) have on the coalescing behavior of ethylene copolymers produced from Ziegler–Natta and metallocene catalyst technologies. Results showed that samples produced using slower cooling rates exhibited higher crystallinity and increased thermal stability. Variations in thermal treatments, however, only resulted in minor changes in the coalescing behavior of the resins considered in this work. However, the addition of the nucleating agent to Ziegler–Natta ethylene copolymers led to the formation of crystalline structures with increased material thermal stability, but reduced chain mobility, and consequently resulted in a slower coalescing rate. These effects, however, are dependent on the molecular structure of the copolymers. The addition of the sorbitol nucleating agent influenced the morphological structure of the metallocene copolymer used in this work but did not result in any significant changes in the coalescence behavior of the resin. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 5443–5455, 2006
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 | 0.001 |
| 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".