Modeling the morphology development of ethylene copolymers in rotational molding
Bibliographic record
Abstract
Abstract A model is proposed to describe the solidification and crystallization phenomena in rotational molding. To capture the morphology development with crystallization behavior, a two‐dimensional theoretical simulation was carried out, consisting of a phase‐field model emphasizing the metastability of polymer crystallization and a heat‐transfer model describing the molding cycle. The model parameters were experimentally evaluated with differential scanning calorimetry and isothermal crystallization tests. Molding trials were also conducted with bench‐scale rotational molding equipment, and the cross sections of the molded products were examined under polarized light optical microscopy. The model predictions capture the formation of transcrystalline structures near the mold surface, which is more apparent under moderate cooling conditions. Our results show that the model predictions are in general agreement with the experimental results obtained in our laboratory as well as those presented in the literature. Because morphological features are important contributing factors to product performance, the model will be useful for the formulation of new materials and process optimization. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 5903–5917, 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".