Quantitative Boundary Support Characterization for Cantilever MEMS
Bibliographic record
Abstract
Microfabrication limitations are of concern especially for suspended Micro-Electro-Mechanical-Systems (MEMS) microstructures such as cantilevers. The static anddynamic qualities of such microscale devices are directly related to the invariant and variantproperties of the microsystem. Among the invariant properties, microfabrication limitationscan be quantified only after the fabrication of the device through testing. However, MEMSare batch fabricated in large numbers where individual testing is neither possible nor costeffective. Hence, a suitable test algorithm needs to be developed where the test resultsobtained for a few devices can be applied to the whole fabrication batch, and also to thefoundry process in general. In this regard, this paper proposes a method to test MEMScantilevers under variant electro-thermal influences in order to quantify the effectiveboundary support condition obtained for a foundry process. A non-contact optical sensingapproach is employed for the dynamic testing. The Rayleigh-Ritz energy method usingboundary characteristic orthogonal polynomials is employed for the modeling andtheoretical analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".