Studying the Effect of Deposition Conditions on the Performance and Reliability of MEMS Gas Sensors
Bibliographic record
Abstract
In this paper, the reliability of a micro-electro-mechanical system (MEMS)-based gas sensor has been investigated using Three Dimensional (3D) coupled multiphysics Finite Element (FE) analysis. The coupled field analysis involved a two-way sequential electro- thermal fields coupling and a one-way sequential thermal-structural fields coupling. An automated substructuring code was developed to reduce the computational cost involved in simulating this complicated coupled multiphysics FE analysis by up to 76 percent. The substructured multiphysics model was then used to conduct a parametric study of the MEMS-based gas sensor performance in response to the variations expected in the thermal and mechanical characteristics of thin films layers composing the sensing MEMS device generated at various stages of the microfabrication process. Whenever possible, the appropriate deposition variables were correlated in the current work to the design parameters, with good accuracy, for optimum operation conditions of the gas sensor. This is used to establish a set of design rules, using linear and nonlinear empirical relations, which can be utilized in real-time at the design and development decision-making stages of similar gas sensors to enable the microfabrication of these sensors with reliable operation.
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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".