MétaCan
Menu
Back to cohort
Record W2031435759 · doi:10.1117/12.700565

Stereolithography as a meso-structure for input force reduction to a capacitive force MEMS sensor

2007· article· en· W2031435759 on OpenAlexafffund
Henry K. Chu, James K. Mills, William L. Cleghorn

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Toronto
FundersNetworks of Centres of Excellence of Canada
KeywordsMicroelectromechanical systemsCapacitive sensingMaterials scienceTactile sensorCapacitanceElectrical engineeringComputer scienceCapacitorSurface micromachiningFabricationOptoelectronicsElectrodeVoltageEngineering

Abstract

fetched live from OpenAlex

This paper focuses on the design and development of a novel MEMS based force sensor for use in a smart electrical switch which can be used to sense forces applied during the disconnection/connection of the switch. Sensed forces will permit the power to the switch to be turned on/off electronically to prevent arcing at 42 Volts, which would otherwise damage the switch electrical contacts. This paper focuses on the design of a packaging cover for the switch incorporated with a meso-structure, for input force reduction, using a Stereolithography fabrication process. This packaging cover will be installed on a standard ceramic pin grid array (PGA) package to which a MEMS force sensor will be wire-bonded. The complete sensor is proposed for use in smart electrical connectors within automobiles. The purpose of the packaging cover is to transform the macroscopic input force imparted by a technician during disconnection or connection of the switch into a grasping action on the sensor. The macroscopic input force is estimated to be 60N at maximum. To prevent potential damage on the MEMS sensor, the cover converts the applied force to a smaller force in the milli-Newton scale. Since the sensor is to be operated under the harsh environment of the automobile, transverse comb-drive capacitors are selected as the force sensing technique. The capacitive MEMS sensor will be fabricated using PolyMUMPs surface micromachining. To ensure linearity, the displacement of the comb drive is limited to 1 &mgr;m for a net capacitance change of 0.013 pF. Principles of strain energy and Castigliano's Theorem are used to model the proposed cover design. It is found that for a 60 N input force, the design is capable of converting that force to a lateral displacement of 30.86 &mgr;m, which is equivalent to a 0.01 N force onto the sensor. Design analysis, and results from Finite Element Method (FEM) simulation of the cover design will be presented in this paper.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.009
GPT teacher head0.233
Teacher spread0.224 · 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
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
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdvanced MEMS and NEMS TechnologiesFrench-language works237,207