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Record W2040081653 · doi:10.1088/0960-1317/23/8/085009

<i>Q</i>-factor enhancement for self-actuated self-sensing piezoelectric MEMS resonators applying a lock-in driven feedback loop

2013· article· en· W2040081653 on OpenAlex
Martin Kučera, Tomás Manzaneque, J. L. Sánchez-Rojas, Achim Bittner, U. Schmid

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMechanical and Optical Resonators
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Department of Energy
KeywordsLock-in amplifierSIGNAL (programming language)AmplifierMicroelectromechanical systemsFeedback loopCantileverNoise (video)ResonatorActuatorQ factorVoltagePiezoelectricityCharge amplifierLoop gainControl theory (sociology)Electronic engineeringMaterials scienceEngineeringOperational amplifierOptoelectronicsComputer scienceElectrical engineeringCMOS

Abstract

fetched live from OpenAlex

This paper presents a robust Q-control approach based on an all-electrical feedback loop enhancing the quality factor of a resonant microstructure by using the self-sensing capability of a piezoelectric thin film actuator made of aluminium nitride. A lock-in amplifier is used to extract the feedback signal which is proportional to the piezoelectric current. The measured real part is used to replace the originally low-quality and noisy feedback signal to modulate the driving voltage of the piezoelectric thin-film actuator. Since the lock-in amplifier reduces the noise in the feedback signal substantially, the proposed enhancement loop avoids the disadvantage of a constant signal-to-noise ratio, which an analogue feedback circuit usually suffers from. The quality factor was increased from the intrinsic value of 1766 to a maximum of 34 840 in air. These promising results facilitate precise measurements for self-actuated and self-sensing MEMS cantilevers even when operated in static viscous media.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.326
Threshold uncertainty score1.000

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 head0.006
GPT teacher head0.202
Teacher spread0.196 · 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