Bibliographic record
Abstract
EPDM polymers have been used in automotive weather seals for more than 30 years and there have been numerous investigations into their mixing and extrusion. However, the stability of EPDM polymers under the heat and shear forces that occur during the production of composites is generally ignored and inadequately understood. This paper describes an investigation into a variety of commercial grades of EPDM polymers exposed to heat ageing and shear. The behaviour of the polymers on their own and in composites was investigated. Weight loss and colour change were observed at 150°C in a hot air oven. Shear stability was investigated in a mixing chamber with an internal volume of 800 cm3. The mixer was equipped with tangential (Banbury) rotors. The chamber temperature was set at 66°C. The change in the molecular weight of the polymer, the molecular weight distribution and the degree of branching after exposure to shear stress for different periods of time were characterised using GPC and RPA. It was established that a polymer product with metallocene catalysts has the best thermal stability. However, a polymer with approximately the same molecular weight produced with conventional Ziegler-Natta catalysts had the best overall molecular and structural stability when exposed to heat ageing and shear. As far as the oil-extended polymers with high molecular weights were concerned, one of the polymers investigated was found to have much better molecular weight retention than the oil-extended polymer even though they are both produced with similar catalysts and production methods. It is not at present possible to reach a final conclusion regarding the interaction between the stability of a polymer when aged in hot air or in the mixer and the catalysts used in its production assuming that most polymers contain a similar stabiliser in a similar concentration.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 0.014 |
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".