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Record W2080434013 · doi:10.3390/s131216641

A Novel Comb Architecture for Enhancing the Sensitivity of Bulk Mode Gyroscopes

2013· article· en· W2080434013 on OpenAlexafffund
Mohannad Y. Elsayed, Frédéric Nabki, Mourad N. El-Gamal

Bibliographic record

VenueSensors · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversité du Québec à MontréalMcGill University
FundersCMC Microsystems
KeywordsSensitivity (control systems)GyroscopeMaterials scienceTransducerCapacitanceVibrationMicroelectromechanical systemsOptoelectronicsElectronic engineeringElectrical engineeringElectrodeAcousticsEngineeringPhysics

Abstract

fetched live from OpenAlex

This work introduces a novel architecture for increasing the sensitivity of bulk mode gyroscopes. It is based on adding parallel plate comb drives to the points of maximum vibration amplitude, and tuning the stiffness of the combs. This increases the drive strength and results in a significant sensitivity improvement. The architecture is targeted for technologies with ~100 nm transducer gaps in order to achieve very high performance devices. In this work, this sensitivity enhancement concept was implemented in SOIMUMPs, a commercial relatively large gap technology. Prototypes were measured to operate at frequencies of ~1.5 MHz, with quality factors of ~33,000, at a 10 mTorr vacuum level. Measurements using discrete electronics show a rate sensitivity of 0.31 μV/°/s, corresponding to a capacitance sensitivity of 0.43 aF/°/s/electrode, two orders of magnitude higher than a similar design without combs, fabricated in the same technology.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.096
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.226
Teacher spread0.218 · 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 teacher head, 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

Citations10
Published2013
Admission routes2
Has abstractyes

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