Micromachined electrostatic force and vertical field mill ac/dc electric field sensors
Bibliographic record
Abstract
This thesis explores several types of micromachined electric field sensors to address the main drawbacks of traditional electric field mills, namely high power consumption, big size, and the requirement of frequent maintenance. Micromachined devices possessing significantly smaller size, less power to move mechanical parts, and free of rotating parts, therefore avoid the wear and tear of moving elements. Two types of sensors were designed. One is based on electrostatic force deflection, and another is based on a vertical movement shutter type field mill. Compared to other micromachined electric field mill (MEFM) sensors, both types of sensors overcome the issue of grounded shutter displacement under a large electric field and provide comparable or even higher performance. Two force deflection actuators were designed and fabricated – SOI membrane and metal ribbon array. Capacitance measurement was applied to both actuators, and both show the ability to measure fields greater than 50 kV/m. When use a laser monitor system to test the SOI membrane, similar sensitivity was achieved. In addition, the ac modulated method was applied to improve the sensitivity of the optical measurement. Providing 118.8 V (peak to peak) ac bias signal on the SOI membrane, sensitivity of 20 V/m was achieved with the ac modulated method. The vertical movement shutter field mill is a novel design. It employs bimaterial thermal actuators to provide vertical movement for the grounded shutter. It solves the problem of shutter displaced under the large field problem in existing micromachined electric field mills (MEFMs). Three types of bimaterial thermal actuators were modeled: SiO2-Al, SU-8-Al, and Si-Al. Due to the high stress of SiO2, the first attempt was to fabricate a SU-8-Al actuator. However, it was found that SU-8-Al actuator has a permanent deformation issue at high temperature. Then efforts were focused on the Si-Al actuator, and the device was successfully fabricated. The sensor mechanical performance test shows that the shutter movement agree with the simulation at various temperature between 25 – 100 ºC. When drive the thermal actuator by digital hot plate, the measured induced current generated by an alternative electric filed also agree with the calculation.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".