Experimental and statistical study of the effects of material properties, curing agents, and process variables on the production of thermoplastic vulcanizates
Bibliographic record
Abstract
Abstract A comprehensive experimental study together with statistical analysis was performed to identify the optimal process conditions, materials selection, and curing system for the production of thermoplastic vulcanizates (TPVs) based on EPDM rubber and polypropylene. Two types of curing systems were studied together with five different types of EPDM rubber. The TPV products were assessed according to elastic modulus and degree of swelling (indicators of crosslink density), ultimate tensile strength, ultimate elongation, tear strength, and compression set. A design of experiments method was applied to minimize the number of experiments and to obtain response surface and regression models for this complex and highly interactive system. From the modeling results, optimum values for the influential factors were obtained to achieve the target end product properties. It was found that a phenolic resin‐based curing system gave the best product properties and that the most influential factors were the rubber characteristics (ethylene content, ethylidene norbornene content, and molecular weight) and the polypropylene content in the formulation. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010
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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 | 0.008 | 0.013 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".