Pressure–volume–temperature–viscosity relations in fluorinated polymers
Bibliographic record
Abstract
Recently, Mekhilef published new data on the pressure– volume–temperature (PVT) behavior of fluorinated polymers, polyvinylidenefluoride (PVDF), and copolymers of poly(vinylidene-co-hexafluoropropylene) (PVDF-HFP). The author also reported on the viscoelastic performance of these resins in the solid and molten states. Since 1969, PVT dependencies have been analyzed by means of the Simha–Somcynsky (S–S) equation of state (EoS). The EoS has the formof coupled equations written in terms of the reduced variables: P˜ = P/P*, V˜ = V/V*, and T˜ = T/T*. According to Rodgers’s evaluation of several EoSs, the S–S EoS has provided the best description of the PVT behavior in the whole range of independent variables. From the fundamental point of view, the S–S EoS has a significant advantage over other EoS relations; simultaneously with V = V(T, P), it provides the hole fraction (h) as a function of P and T: h = h(T, P). The latter function has been shown4 to be directly related to the free volume fraction (f), for example, as determined by positron annihilation lifetime spectroscopy. The knowledge of h has been found useful in many applications, namely, the correlation of surface tension with bulk properties. Furthermore, it relates the equilibriumwith transport properties, for example, the constant stress viscosity of melts and their mixtures and other viscoelastic functions. Analysis of the new PVT data for fluoropolymers is of interest for several reasons. Because the tested samples were well characterized,1 it would be interesting to know how the changes of molecular weight and composition affect the reducing parameters, P*, V*, and T*. Once these parameters are known, the compressibility, thermal expansion coefficient, and cohesive energy density (or the solubility parameter) can easily be calculated. Furthermore, the interrelation between the melt viscosity and h should be examined.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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 teacher head, 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".