Special surface for power delivery to wireless micro-electro-mechanical systems
Bibliographic record
Abstract
This paper reports a special surface suitable to distribute power while providing a high-precision surface where wireless micro-electro-mechanical systems must operate. The surface is made of alternate electrically conducting and narrower insulating bands with dimensions that allow power to be delivered to the wireless systems when in contact with at least two electrically conductive bands. In this study, a first implementation using stainless steel 440C and black granite is analyzed in more detail. The dimensions of both the conducting and insulating bands are described by considering the properties of the materials used and the precision of the micro-mechanical systems that may be affected by features on the surface with dimensions down to the nanometer scale. The effects on the dimensions of the bands due to the total mass of each microsystem, the contact surface area between the microsystems and the powering surface, and the accuracy of the positioning system used, are also taken into account. Minimum widths of the insulating bands and the methods to prevent electrical shorts between a pair of successive bands, created through arcing between the conductive bands and a conductive structure of the wireless units when stationary or transiting through an insulating band, are also evaluated and compared when operating in air or helium atmosphere.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".