Ultrasonic characterization of the crystallization behavior of poly(ethylene terephthalate)
Bibliographic record
Abstract
Abstract On the basis of the previous observations that the ultrasonic signals are sensitive to the crystallization of polymers (Tatibouet and Piché, Polymer 1991, 32, 3147), we have expanded our efforts to study the detail relationship between the ultrasonic signals and crystallization process in this work. The nonisothermal and isothermal crystallization of virgin poly(ethylene terephthalate) (PET) and PET samples after degradation were studied by using a specially designed pressure‐volume‐temperature (PVT) device, with which an ultrasonic detector was combined. The results showed that the evolution of the ultrasonic signals not only can be used to probe the crystallization process but also can qualitatively characterize the crystallization rate, crystallinity, crystallite size, and amorphous. DSC measurement was used to verify such results. Ultrasonic signals could be as a complementary tool to polymer chain movement and well be applied to characterize the crystallization behavior. Furthermore, the ultrasonic measurement has the potential use to characterize crystallization of products in‐line during processing (i.e., injection molding, micromoulding). © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009
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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 | 0.001 |
| 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) | 0.001 | 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".