Design and Modelling of a MEMS Capacitive Temperature Sensor With Linear Capacitance-Temperature Response
Bibliographic record
Abstract
A capacitive temperature sensor with separate thermal actuation and capacitive readout is introduced. A bi-layer plate with fixed-free boundary condition is used for the thermal actuation to change the gap between two parallel electrodes used for capacitance measurement. Different coefficients of thermal expansion (CTE) of the two layers in actuator cause out-of-plane deformations in the plate when the temperature changes. The proposed design has the capability to control the response of the sensor by increasing its sensitivity in a given temperature range. To obtain the desired characteristic C-T curve, the design utilizes asymmetric geometries. Different design parameters such as the size of the bi-layer plate and the sense electrodes are considered as design variables. ANSYS® FEM simulations are used to extract the C-T responses of different geometries. The results of the FEM simulations show that for a given fabrication process and material properties, the design can be modified to provide the highest sensitivity and linearity in the C-T response for a given temperature range. This temperature sensor can be used for remote and on-chip temperature measurement or temperature compensation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".