Characterization of the dielectric endurance of reinforced recycled PET using electro-thermal aging test
Bibliographic record
Abstract
This paper presents the advantages of dielectric characterization by electro-thermal aging testing in the durability analysis of reinforced recycled polyethylene terephthalate (PET), as compared to short-term dielectric breakdown strength measurements. Dielectric breakdown strength measurements were carried out at room temperature according to ASTM D149-a, while electro-thermal aging tests were conducted in air at different constant temperatures ranging from 140 to 170 °C, using an experiment setup comprising a cell test arranged in a point-to-plane configuration, with a very small air gap of 50±1 μm. The tests were conducted at an AC voltage of amplitude 7 kV rms on eight different reinforced recycled PET samples. The degradation of recycled PET-based composites during exposure to corona discharges at elevated temperatures was characterized by optical microscopy and scanning electron microscopy (SEM). The main goal of this study is to characterize and to determine the relationship between the addition of different inorganic reinforcements, such as mica and glass fibers, to a recycled PET matrix, as well as the resistance to dielectric failure during electro-thermal aging. The effect of plasticizers on the dielectric endurance of recycled PET-based composites was also investigated. Results obtained showed that glass fibers contribute to the enhancement of the resistance to dielectric failure. Our experiments also revealed that the dielectric behaviour of these composites can be affected by the presence of plasticizers. In addition, the size of additives such as mica can greatly improve the resistance to the dielectric breakdown caused by electrothermal aging.
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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 | 0.003 |
| 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".