Development of a model for predicting dry stiction in microelectromechanical systems (MEMS)
Bibliographic record
Abstract
Adhesion between micro parts, also referred to as stiction, is a major failure mode in MEMS. Undesirable stiction, which results from contact between surfaces, can severely compromise the reliability of MEMS. In this paper, a model is developed to predict the dry stiction between uncharged micro parts in MEMS. In dry stiction, the interacting surfaces are assumed to be either hydrophobic or placed in dry environment. In this condition, the van der Waals (vdW) and asperity deformation forces are dominant. Here, a model is developed for the vdW force between rough micro surfaces and the new model is combined with a newly developed multiple asperity point model for the elastic/plastic deformation of rough surfaces in contact to solve for the equilibrium condition of the forces. This, in turn, will yield the equilibrium distance between micro surfaces, using which the apparent work of adhesion can be found. The result of the theory is compared with the available experimental data from literature. The developed model can be easily used for design purpose. If the topographic data and material constants are known, the adhesion parameters can be quickly calculated using the model.
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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 | 0.001 | 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".