Microfabrication influence on the behavior of capacitive type MEMS sensors and actuators
Bibliographic record
Abstract
Purpose To predict the influence of inherent microfabrication and operating environmental influences on the performance of capacitive type sensors and actuators so that one can tune the performance and carry out more realistic designs. Design/methodology/approach When the sensors and actuators are micromachined or microfabricated, they are subjected to special problems that are characteristic to microdimensions. The important concerns are the influence of microfabrication process on the material properties and influence of operating environment on the system behavior. Hence, this paper proposed a way of quantifying and modeling the influence of inherent limitations of microfabrication and operating environment for the better design of micromachined capacitive type sensors and actuators. The methodology applies the modeling the variation of the elastic property of the system due to above influences through elastic stiffening and weakening concepts. The approach includes the application of boundary conditioning concept through Rayleigh energy method. Findings The microfabrication process and electrostatic field can alter significantly both static and dynamic behavior of the device. The performance of the device could also be tuned through these influences. Research limitations/implications As the displacement of the sensors is expected to be small, linear approach is applied. The sensitivity, output range, operating limits and natural frequencies of the sensor can be easily controlled by varying the process and operating environmental influences. Practical implications Improved and more realistic design of microfabricated capacitive type sensors and actuators for many applications, such as, pressure sensors, microphones, microspeakers, etc. Originality/value A simple and easy way of modeling and quantifying the influence of process and operating environment was proposed for the betterment of design. The proposed design method can be applied for any micromachined or microfabricated capacitive type sensors and actuators so that varying sensitivities, output ranges and natural frequencies could be obtained. Over the last few years, newly emerging micro‐electro‐mechanical‐systems (MEMS) technology and micro‐fabrication techniques have gained popularity and importance in the miniaturization of a variety of sensors and actuators. The proposed technique is very useful in making the field of MEMS more matured as it attempts to model the problems that are unique to MEMS environment.
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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 | 0.000 | 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".