Pressure−Volume−Temperature Dependence of Polypropylene/Organoclay Nanocomposites
Bibliographic record
Abstract
The pressure−volume−temperature ( PVT ) dependencies of commercial polypropylene melt (PP) and its nanocomposites containing X wt % of organoclay (Cloisite-15A, or C15) and 2 X wt % of a compatibilizer were determined at T = 450−530 K and P = 0.1−190 MPa. C15 was used at concentrations: X = 0, 2, and 4 wt %. Three functionalized PP's were used as compatibilizers: two maleated and one grafted with glycidyl methacrylate. Incorporation of X = 2 wt % C15 into PP resulted in reduction of specific volume by Δ V ≈ 1%, but that of free volume (hole) fraction by Δ h ≈ 5%. The latter quantity was computed from the Simha−Somcynsky lattice−hole equation of state. Furthermore, at constant T and P the hole fraction was found to be linearly related to the bulk-average energetic interaction parameter and to be a sensitive indicator of structural changes. In binary (polymer + organoclay) systems Δ h is linearly related to the interlayer spacing, d 001 . So, where statements from the previous paper are repeated or there are similarities, this is done for purposes of comparison. In three-component systems (with a compatibilizer) the proportionality has been preserved, but large changes of Δ h result in relatively small changes of d 001 . Mechanical properties hardly correlate with either Δ h or d 001, as polymer/compatibilizer morphology and crystallinity complicate the behavior.
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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 | 0.000 |
| 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 | 0.001 |
| 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".