Effects of Pressure and Supercritical Fluids on the Viscosity of Polyethylene
Bibliographic record
Abstract
A high-pressure sliding plate rheometer was used to determine the effects of supercritical fluids and pressure on the viscosity of molten high-density polyethylene (HDPE). In this instrument, the shear strain, temperature, pressure, and gas concentration are all uniform, and a shear stress transducer senses the stress in the center of the sample to eliminate edge effects. The effect of pressure alone at 180 °C was determined up to 70 MPa. The sample exhibited piezorheologically simple behavior, and the Barus equation was found to describe the pressure-shift factor. The effects of gas concentration and pressure on the viscosity were determined up to 23 wt % CO 2 concentration and 34.5 MPa. Because the gas of interest is the pressurizing fluid, it is necessary to ensure that the sample was saturated before measurements were made. The saturation time was estimated by use of Fick's law, and the prediction was confirmed by monitoring the viscosity as a function of time. This implies that the rheometer can be used to obtain a good estimate of the diffusion coefficient for gas into polymer. Small-amplitude oscillatory shear was found to significantly accelerate the diffusion process. To interpret the data, it was necessary to determine the pressure−volume−temperature behavior of pure HDPE, and the Tait model provided a good fit to the data. The solubility of gas and the swollen volume of polymer were also required, and these were determined using a magnetic suspension balance. The Sanchez−Lacombe model was used to analyze these data. Using both horizontal and vertical shift factors for concentration and a horizontal shift factor for pressure led to an excellent superposition of all data. The shift factor for concentration alone was obtained by assuming that the shift factors for pressure and concentration are separable, and the Fujita−Kishimoto model was found to describe the effect of concentration alone on the concentration shift factor. The effects of carbon dioxide and nitrogen were found to be the same if the concentration is expressed in moles.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".