Simulation and optical measurement of MEMS thermal actuator sub-micron displacements in air and water
Bibliographic record
Abstract
The aim of this study is to simulate and measure sub-micron motion of a chevron type MEMS thermal actuator in air and water. Finite element analysis (FEA) of the physical system provided predictions of the actuator temperature increase and displacement in both media. Simulations indicate that for 6V the maximum temperature on the chevron actuator arm is 335 °C in air and 35 °C in water. In water the temperature increase is confined to the vicinity of the heat source: 30 μm from the actuator center the temperature increase is smaller than 0.5 °C. FEA predicts a chevron displacement of 0.98 μm in air and 49 nm in water at 6 V. Experimental measurements of displacements were performed using an FFT image analysis algorithm with sub-micron precision. Experimental results show a displacement of 1.11 ± 0.01 μm in air and 67 ± 17 nm in water for 6V. The agreement between simulated and measured results validates the accuracy of the computational model used in this study. From the experimental data, the performance of the thermal actuator in water is about 6% of its performance in air. The study indicates the feasibility of using thermal actuators to perform cell tests in aqueous media.
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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 | 0.000 |
| 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".