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Record W2105391861 · doi:10.1109/icmens.2003.1222013

Nonlinear effects in MEMS capacitive microphone design

2004· article· en· W2105391861 on OpenAlexaff
Sazzadur Chowdhury, Majid Ahmadi, William C. Miller

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCapacitive sensingMicroelectromechanical systemsMaterials scienceNonlinear systemMicrophoneDeflection (physics)Diaphragm (acoustics)VoltageResidual stressAcousticsFinite element methodSpring (device)Structural engineeringMechanicsSound pressureEngineeringElectrical engineeringPhysicsVibrationOpticsComposite materialOptoelectronics

Abstract

fetched live from OpenAlex

An analytical method is presented that provides a better approximation for design parameter values of a MEMS capacitive microphone. The spring softening effect associated with the nonlinear characteristics of the electrostatic pressure due to a bias voltage, and the spring hardening effect associated with nonlinear stretching of the central region of a uniformly loaded fully clamped diaphragm with residual stress are both considered. The method allows a more accurate determination of the developed electrostatic pressure, maximum diaphragm deflection and the pull-in voltage. The resulting electrostatic pressure, pull-in voltage and deflection profile of the diaphragm are in close agreement with finite element analysis results.

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 score0.030
Threshold uncertainty score0.354

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 head0.205
Teacher spread0.197 · 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

Citations36
Published2004
Admission routes1
Has abstractyes

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