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Record W2168429603 · doi:10.1109/icma.2005.1626526

Design of a MEMS-based resonant force sensor for compliant, passive microgripping

2006· article· en· W2168429603 on OpenAlexaff
Issam B. Bahadur, James K. Mills, Yu Sun

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTuning forkMicroelectromechanical systemsSensitivity (control systems)CapacitanceMaterials scienceAcousticsVibrationParasitic capacitanceOptoelectronicsElectronic engineeringElectrical engineeringEngineeringPhysicsElectrode

Abstract

fetched live from OpenAlex

In this paper, a polysilicon double-ended tuning fork (DETF) is proposed for use as a force sensor for integration into a compliant, passive microgripper used in a microassembly of 3D MEMS structures. The force sensor is also designed to operate in a manner similar to scanning probe microscopy (SPM) that is commonly utilized to study surface properties and topography of material. The design, modeling, and performance characteristics of the resonant force sensor are addressed. The force sensor design has a resolution of 1.0 pN//spl radic/Hz: in absence of electronics and power noises. Furthermore, a gauge factor (i.e. sensitivity) of 1700 is obtained with applied force of 30 /spl mu/N. A DETF excitation and detection technique is proposed to minimize parasitic capacitance effects.

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: Methods · Consensus signal: none
Teacher disagreement score0.470
Threshold uncertainty score0.403

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 head0.021
GPT teacher head0.235
Teacher spread0.214 · 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
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

Citations7
Published2006
Admission routes1
Has abstractyes

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