MétaCan
Menu
Back to cohort
Record W4402807886 · doi:10.1109/jmems.2024.3455106

Design and Experimental Validation of a Piezoelectric Resonant MEMS Phase Comparator

2024· article· en· W4402807886 on OpenAlexafffund
Mathieu Gratuze, Mohammad Kazemi, Seyedfakhreddin Nabavi, Paul-Vahé Cicek, Alexandre Robichaud, Frédéric Nabki

Bibliographic record

VenueJournal of Microelectromechanical Systems · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversité du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsComparatorMicroelectromechanical systemsPiezoelectricityPhase (matter)Electronic engineeringMaterials scienceComputer scienceEngineeringPhysicsElectrical engineeringOptoelectronicsVoltage

Abstract

fetched live from OpenAlex

In this paper, the design, concept and experimental validation of the performances of a piezoelectric resonant microelectromechanical systems (MEMS) phase comparator is presented. Compared to traditional integrated circuits, the potential benefits of a MEMS phase comparator include a low power consumption, higher sensitivity, higher selectivity and improved robustness. The design and experimental validation of a resonant MEMS phase comparator are presented along with characterization recommendations. The operation of this resonant MEMS phase comparator is experimentally validated over the first five eigen modes at 108 kHz, 298.7 kHz, 583.3 kHz, 962.8 kHz and 1.4375 MHz. Calibration of the resonant MEMS phase comparator is presented, allowing for simple device operation, which is validated under various waveform stimulations: sinusoidal, square, and triangular. This work is expected to lead to the development of new applications for MEMS resonating devices. [2024-0037]

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)0.002
metaresearch head score (Gemma)0.004
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: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.273
Teacher spread0.255 · 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
GenreMethods

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

Citations3
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Microelectromechanical SystemsSame topicAdvanced MEMS and NEMS TechnologiesFrench-language works237,207