MétaCan
Menu
Back to cohort
Record W4403863718 · doi:10.1109/ted.2024.3480028

Micromachined Capacitive Sensor With Configured Boundaries: Approach, Design and Fabrication

2024· article· en· W4403863718 on OpenAlexafffund
Haleh Nazemi, R. A. Graham, Gian Carlo Antony Raj, D. S. Damiani, A. Emadi

Bibliographic record

VenueIEEE Transactions on Electron Devices · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationCMC Microsystems
KeywordsFabricationCapacitive sensingSurface micromachiningMicroelectromechanical systemsElectrical engineeringElectronic engineeringEngineeringMaterials scienceCapacitanceOptoelectronicsComputer sciencePhysicsElectrode

Abstract

fetched live from OpenAlex

A new set of capacitive-based resonators is introduced in this work that utilizes a unique configured boundaries approach. The proposed design strategy is utilized to develop and characterize three circular resonators as proof-of-concept with strategically configured boundaries. For a fair comparison, the introduced novel resonators along with a reference conventional structure are fabricated using a commercially available fabrication technique, PolyMUMPs. The effects of the presented approach on plate deflection and electromechanical coupling coefficient are demonstrated through finite element analysis (FEA) using COMSOL Multiphysics as well as experimental characterizations. The fabricated devices are electrically evaluated. The white light interferometry is further used for deflection measurements. The device performance evaluations illustrate a robust control of the resonator’s plate stiffness and deflection while maintaining the same dimensions. Experimental evaluations demonstrate an enhanced deflection profile of the plate, which significantly increases the average deflection by up to 50% compared to the conventional resonator developed with the same dimensions and fabrication process. Furthermore, it is observed that using the proposed approach reduces the pull-in voltage by up to 17% compared to the conventional resonators while preserving the resonant frequency within ±150 kHz.

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: none
Teacher disagreement score0.886
Threshold uncertainty score0.606

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 head0.216
Teacher spread0.207 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueIEEE Transactions on Electron DevicesSame topicAdvanced MEMS and NEMS TechnologiesFrench-language works237,207