Bibliographic record
Abstract
The main focus of the research presented in this paper is the investigation of the ability of various polyolefin resins to be converted into integral-skin cellular composites by using the rotational foam molding process. Integral-skin foamed rotational moldings are formally denoted as cellular composites ideally having a clearly distinct surface layer of solid skin of uniform thickness that is encapsulating a seamlessly coupled fine-celled foamed core or layer of uniform cell density and distribution. A systematic comparative material characterization study that attempts to derive practical guidelines about determining the roto-foamability of polyolefins that would be useful for rotomolding processors is presented. The study included two experimental methods of characterization, a melt rheology-based and a rotational foam molding processing-based. The experimental results from both implemented characterization methods revealed good agreement. A comprehensive insight into the key polyolefin material characteristics that would ensure satisfactory results if processed using the rotational foam molding technology have been provided. The experimental results revealed that high quality polyethylene (PE) based cellular morphologies can be obtained from both dry blended and melt compounded foamable compositions for both 6-fold and 3-fold expanded foams. Unlike PE resins, it was observed that successful foaming of polypropylene (PP) resins in rotational foam molding can only be successfully accomplished over a very narrow range of melt temperatures that are close to the melting point of the polymer and by using PP grades with a quite limited range of Melt Flow Rates (MFR).
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".