Suppression of erosion due to dry-band arcing under DC by alumina tri-hydrate filler in silicone rubber
Bibliographic record
Abstract
The paper describes a study into understanding the mechanism by which alumina tri-hydrate suppresses dry-band arcing erosion of silicone rubber under DC. Commercial silicone elastomers filled with alumina tri-hydrate to 25 and 58 wt% are exposed to the inclined plane tracking/erosion tests while simultaneously monitoring surface temperature. During the early stages of testing, a surface residue is formed, which promotes stable dry-band arcing. An earlier inception of the stable discharge, thus initiation of deep erosion at a temperature approaching 400 °C, is obtained with 25 wt% alumina tri-hydrate. A lower temperature rise is obtained for the 58 wt% filled specimens as compared to the 25 wt% filled specimens. Differential scanning calorimetry shows a larger enthalpy of dehydration for 58 wt% alumina tri-hydrate filled samples. To verify the role of dehydration on reducing the surface temperature and erosion, the erosion of liquid silicone rubber specimens is compared for samples filled with alumina tri-hydrate and silica, both at 30 wt%. As a measurement parameter, the time-to-erosion is compared between the specimens showing a reduced time for the silica filled specimens as compared to the alumina tri-hydrate filled specimens, thereby verifying the influence of the water of hydration to suppress surface temperature and erosion. The paper provides an experimental approach by which the suppression of erosion by alumina tri-hydrate can be investigated, employing simultaneous leakage current and temperature measurements.
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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) | 0.000 | 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 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".