MétaCan
Menu
Back to cohort
Record W2086372548 · doi:10.1115/detc2010-28299

Using an In-Situ Micromirror to Assist the Measurement of In-Plane Vibration of Microstructures

2010· article· en· W2086372548 on OpenAlexaff
Jacky Chow, Yongjun Lai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsQueen's University
Fundersnot available
KeywordsOpticsCantileverMaterials scienceMicroelectromechanical systemsPerpendicularInterferometryLaserLaser Doppler vibrometerHeterodyne (poetry)Substrate (aquarium)Surface micromachiningVibrationDisplacement (psychology)OptoelectronicsDistributed feedback laserAcousticsPhysics

Abstract

fetched live from OpenAlex

Heterodyne laser interferometry is an optical technique often used to measure displacement of surfaces along the wave vector direction of a measurement laser. For common microelectromechanical system (MEMS) testing setup, such laser wave vector is perpendicular to the substrate which the micromachined devices stand on. Therefore, this technique can only be used to characterize dynamics of the micro devices in the direction perpendicular to their substrate (out-of-plane motions) with the classic setup and it is not able to measure any motion that is parallel to the substrate (in-plane motions). In this study, in-situ micromirrors are fabricated onto a microstructure that is near the device to be measured by using a focused ion beam system. The micromirrors have a slant angle of approximate 45 degree to horizontal surface (or their substrate). By using the post-fabricated in-situ micromirror, the measurement laser of a heterodyne interferometer can be directed into horizontal plane which enables characterization of in-plane motions for micromechanical. To experimentally demonstrate the technique a micro cantilever fabricated using MetalMUMPs is used. The micro cantilever is excited by inplane electrostatic force. The results confirm the effectiveness of the method by the fact that the magnitude of the measured in-plane signal is increased by more than ten folds.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.028
GPT teacher head0.261
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced MEMS and NEMS TechnologiesFrench-language works237,207