Equations of state for polyamide‐6 and its nanocomposites. II. Effects of clay
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The pressure‐volume‐temperature (PVT) dependencies of polyamide‐6 and its nanocomposites (polymeric nanocomposites) were measured at temperatures T = 300–600 K and pressures P = 0.1–190 MPa, thus spanning the range of molten and “solid” phases. The Simha‐Somcynsky ( S ‐S) cell‐hole equation of state (EOS) was used for describing the molten region. At T g ( P ) ≤ T ≤ T m ( P ), the “solid” phase is a mixture of the liquid polyamide‐6 with dispersion of crystals. Accordingly, the PVT behavior in this region was described as a combination of the S ‐S EOS for the liquid phase and the Midha‐Nanda‐Simha‐Jain (MNSJ) EOS for the crystalline one. These two theories based on different models yielded two sets of the characteristic reducing parameters, P * , T * , V * and the segmental molecular weight, M s . Incorporation of 2 and 5 wt % clay increased P * and reduced T * and V * , but the effects were small. Fitting the combination of S ‐S and MNSJ EOS' to isobaric “solid” phase data yielded the total crystallinity, X cryst , and the correcting excess specific volume, Δ V m,c . Both parameters were sensitive to pressure, P , and the clay content, w —the former increased with P and w , whereas the latter decreased. The raw PVT data were numerically differentiated to obtain the thermal expansion and compressibility coefficients, α and κ, respectively. At T < T m , addition of clay reduced their relative magnitude, whereas at T > T m , the opposite effect was observed, most likely owing to the excess of intercalant in the polymeric nanocomposites samples. © 2009 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 47: 966–980, 2009
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it