Laterally Actuated Si-to-Si DC MEMS Switch for Power Switching Applications
Bibliographic record
Abstract
Electrothermal actuators are highly advantageous for microelectromechanical systems (MEMS) due to their capability to generate significant force and large displacements. Despite these benefits, their application in reconfigurable conduction line switches is limited, particularly when employing commercial processes. In DC MEMS switches, electrothermal actuators require electrical insulation between the biasing voltage and the transmission line to prevent interference and maintain the integrity of the switch. This work presents a chevron-type electrothermal actuator utilizing a stack of SiO2/ Al thin films on a silicon (Si) structural layer beam to create a DC MEMS switch. The design leverages a thin film Al heater to drive the actuator while the SiO2 layer provides electrical insulation, suppressing crosstalk with the Si layer. The electrical contact resistance of a Si-to-Si interface was evaluated by applying a controlled current and measuring the resultant voltage. A low contact resistance of 150 Ω was achieved when an initial contact gap of 2.52 μm was closed using an actuator with an actuation voltage of 1.2 V and a current of 205 mA, with a switching speed of less than 5 ms. Factors such as the contact force, the temperature, and the residual device layer etching angle significantly impact the Si-to-Si contact resistance and the switch's longevity. The switch withstands a breakdown voltage up to 350 V at its terminal contacts. Thus, it will be robust to self-actuation caused by unwanted voltage contributions, making it suitable for high-voltage and harsh environment applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".