Orientation and Relaxation in Thick Poly(ethylene Terephthalate) Films by Transmission Infrared Linear Dichroism
Bibliographic record
Abstract
Infrared spectroscopy is a powerful tool for the study of the orientation in amorphous and semi-crystalline polymers, but it is generally limited to thin samples. In this study, we have used transmission infrared linear dichroism to study the orientation of thick poly(ethylene terephthalate) (PET) films. To overcome the saturation problem of the intense bands of PET, overtones and combination bands in the high-frequency region of the mid-infrared spectrum were used. Using polarization-modulation infrared linear dichroism (PM-IRLD), it was possible to follow in real-time the relaxation of orientation of uniaxially oriented PET films up to 500 μm thick. It was observed that between 30 and 500 μm, the thickness of the films has no effect on the orientation relaxation dynamics. It should, therefore, be possible to use thick films, which are much easier to prepare than thin films, for future infrared studies of the deformation of PET. A very good correlation was also observed for the relaxation curves obtained using high- and low-frequency bands related to gauche and trans conformers in thin and thick films. An example of the application of these high-frequency bands to obtain orientation and structural information is also given in the case of a commercial PET bottle showing a biaxial orientation.
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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) | 0.001 | 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 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".