Understanding Surface Charging on PCB Materials Under High Electric Field and Low-Pressure Conditions
Bibliographic record
Abstract
Transportation electrification has been one of the important milestones towards sustainability. A recent addition to this list is all-electric aircraft. One of the key challenges in achieving this goal is the design of insulation systems, which must withstand high electric fields at low pressure, where electrical discharges are ineviTable, leading to surface charging. In this work, the surface charging of printed circuit board (PCB) base material, epoxy, and its composites (filled with$\text{TiO}_{2}$and$\mathrm{h}-\text{BN}$) are studied at low pressure. The samples are subjected to a controlled discharge of 10 kV at different pressures ranging from 100 kPa to 60 kPa, and the resultant accumulated charges are measured using a non-contact electrostatic voltmeter. The variation in accumulated surface charges and patterns at different pressures is analyzed. The surface charging is observed to be increasing with the decrease in pressure. The$5 \text{wt} \%$filled samples performance is found to be optimum for both$\text{TiO}_{2}$and$\mathrm{h}-\text{BN}$fillers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".