Paste Extrusion and Mechanical Properties of PTFE
Bibliographic record
Abstract
Abstract The paste extrusion process of two types of PTFE has been studied in capillary extrusion using dies having different reduction ratio (RR) and die entrance angles. The extrusion pressure shows a weak increase with shear rate over a wide range of flow rates and a more significant increase with reduction ratio. Moreover, the extrusion pressure exhibits a minimum for entrance angle at around 30°. A simple analytical model based on the radial flow hypothesis (previously developed) has been found to represent the extrusion pressure adequately as a function of flow rate (shear rate) and geometrical characteristics of the capillary dies. The extrudates collected at different processing conditions were dried and tested in uniaxial extension to assess their effect on mechanical properties. The tensile modulus, yield stress and ultimate tensile strength of the obtained extrudates were found to be increasing functions of reduction ratio, although the opposite effect was found for the ultimate elongational strain. These mechanical properties are also found to be insensitive to changes in the die entrance angle although the ultimate tensile strength has shown a maximum at the entrance angle of about 60°. The PTFE paste extrudates show a Poisson's ratio equal to zero in tensile experiments, thus exhibiting expansion (significant density reduction with stretching). Finally, a simple model was derived for the density change in tensile deformation by taking into the account the Poisson's ratio and the strain recovery (recovery of the elastic energy stored upon removal of the tensile stress).
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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 | 0.001 |
| 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 | 0.000 |
| 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".