Free volume and viscosity of polymer‐compressed gas mixtures during extrusion foaming
Bibliographic record
Abstract
Extrusion foaming of molten polystyrene (PS) with three physical foaming agents (PFAs), carbon dioxide (CO2), 1,1,1,2-tetrafluoroethane, and 1-chloro-1,1-difluoroethane, is considered. The concentration of injected PFA was W = 0–5 wt % for CO2 and W = 0–15 wt % for the other agents. The aim of this work is to connect flow and equation of state (EOS) properties under the temperature and pressure conditions encountered during extrusion foaming. The constant-stress viscosity η at σ12 ≅ 40 kPa was measured online at temperatures T ≅ 110–210 °C and pressures P ≅ 5–13 MPa. The EOSs of PS and PFA are analyzed in terms of the Simha–Somcynsky lattice–hole theory. The hole fraction, h = h(T,P), is extracted from the analysis of the experimental pressure–volume–temperature data, and a conventional free-volume fraction is also obtained and related to h. Next, these functions are related to the constant-stress viscosity of PS/PFA mixtures in terms of alternative mixture rules. The T, P and composition dependencies of the system viscosity can be satisfactorily expressed in terms of volume-average hole fractions of the two constituents. An analysis of Newtonian viscosities of PS/PFA systems measured by Kwag et al. [Kwag, C., Manke, C. W., and Gulari, E., J Polym Sci Part B: Polym Phys, 1999, 37, 2771] under steady-state conditions results in a satisfactory agreement with the developed procedure. © 2000 John Wiley & Sons, Inc. J Polym Sci B: Polym Phys 39: 342–362, 2001
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".