Processing enhancers for rotational molding of polyethylene
Bibliographic record
Abstract
Abstract Rotational molding is a zero shear process used to manufacture hollow plastic parts. One disadvantage of this process is long cycle times, which are significantly affected by the sintering rates of thermoplastic powder. The objective of this work was to evaluate low molecular weight additives as sintering enhancers for polyethylene and to validate the results in rotational molding. The following additives were blended with linear low‐density polyethylene: mineral oil, glycerol monostearate and pentaerythritol monooleate. The additives resulted in decreased melt viscosity and/or elasticity at low shear rate. The reduction in melt elasticity was particularly significant. Sintering studies confirmed that the additives resulted in significantly faster coalescence. In uniaxial rotational molding, the decreased melt viscosity and elasticity obtained with mineral oil were observed to result in much faster densification and bubble removal. Part thickness was uniform and there was no warpage. Adding mineral oil to polyethylene reduced the cycle time in uniaxial rotational molding and the peak impact strength was identical to that obtained without any additive. Biaxial rotational molding experiments confirmed that the use of mineral oil resulted in shorter cycle time without sacrificing peak impact strength.
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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 | 0.000 |
| 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".