Pressure−Volume−Temperature Dependence of Poly-ε-caprolactam/Clay Nanocomposites
Bibliographic record
Abstract
The pressure−volume−temperature ( PVT ) dependence of commercial poly-ε-caprolactam melt (PA-6) and based on it a nanocomposite containing 1.6 wt % of exfoliated montmorillonite (PNC) as well as their 1:1 mixture was determined at T = 300−560 K and P = 0−150 MPa. Incorporation of clay into PA-6 resulted in lowering the specific volume of PNC by about 1.0%. For all three molten resins excellent agreement between experiment and the results from Simha−Somcynsky lattice−hole theory was found. The hole (free volume) fraction, a sensitive indicator of structural changes, shows a pressure-dependent reduction of ca. 14−15% in PNC as compared with the neat PA-6. An evaluation of the binary interactions from the computed mean scaling parameters of the theory requires definition of the constituents. On the basis of experimental and computer simulation results in the literature, the following model was adopted: Flat disk particles of specified diameter are covered with a uniform layer of solidified PA-6 of specified thickness, thus forming “hairy” clay platelets (HCP). The remainder of PA-6 constitutes the matrix. Its mobility and other properties vary with the distance from the clay surface in the normal direction and reach as an asymptotic limit bulk values. Thus, the characteristic interaction parameters of the matrix vary with the interparticle distance and hence with clay content. The estimated cross-interaction parameters are appropriate averages of the two self-interaction quantities.
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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".