Blends, hydrogen bonds, and orientation: Understanding the role of interactions
Bibliographic record
Abstract
Abstract A review of past and present studies on orientation, rheology, and FTIR investigations on a hydrogen bond–forming polymer, poly(vinyl phenol) (PVPh), and its blends with polyethylene oxide (PEO), poly(methyl methacrylate) (PMMA), and poly(vinyl methyl ether) (PVME) is presented. Orientation is analyzed on the basis of deformation‐induced orientation and relaxation. For deformation, it is proposed from recent molecular modeling studies that orientation is similar for flexible backbone polymers of the types studied. To investigate relaxation, dynamical rheology analysis was performed previously on PVPh/PEO blends and global molecular weight between entanglement, M e , and chain friction ζ were estimated. M e remained close to that of the polymer forming the dominant network, a discontinuity being observed near 50 mole percent. Friction coefficient exhibited a maximum near that of the orientation function of this system. Near‐infrared measurements also showed a maximum in the number of interchain hydrogen bonds at this concentration, although broader than that of orientation or of the friction coefficient. For strongly interacting blends, it is proposed that a break in orientation behavior would be associated with the dominant network present, and therefore to M e , whereas ζ will dictate whether orientation decreases or increases in a given network domain.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".