Breakdown pattern identification in high temperature dielectric films using scanning electron microscopy (SEM)
Bibliographic record
Abstract
In this research paper DC breakdown patterns identification were carried out after applying high voltages across samples of 25 /spl mu/m Kapton/spl reg/ (polyimide) and Mylar/spl reg/ polyester (poly(ethylene terephthalate), PET) films. For pattern identifications, Scanning Electron Microscopy (SEM) technique was employed for acquiring 150/spl times/ and 300/spl times/ magnified images. In both images the shape of breakdown area was almost identical to the shape of electrodes. The SEM results clearly revealed that the melting process during high voltage DC breakdown process is higher in case of Mylar/spl reg/ polyester than that of Kapton/spl reg/ (polyimide). In case of Mylar/spl reg/ at room temperature, observed hole diameter was approximately 265.5 /spl mu/m with the total effected area of 55.3/spl times/10/sup -9/ m/sup 2/ at DC breakdown strength of 326.7 MV/m as compared to Kapton/spl reg/, which was 155.7 /spl mu/m with total effected area of 19/spl times/10/sup -9/ m/sup 2/ at breakdown strength of 364.9 MV/m. In these films for the measurement of electrical breakdown strength a new type of environmental chamber was used. Two-parameter Weibull distribution has been used to analyze the results.
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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 | 0.000 |
| 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".