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Record W2042979552 · doi:10.1088/0960-1317/21/4/045005

Parametric evaluation of shear sensitivity in piezoresistive interfacial force sensors

2011· article· en· W2042979552 on OpenAlexaff
David Benfield, Edmond Lou, Walied A. Moussa

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPiezoresistive effectParametric statisticsSensitivity (control systems)Materials scienceShear forceShear (geology)Composite materialMicroelectromechanical systemsNanotechnologyOptoelectronicsEngineeringElectronic engineeringMathematics

Abstract

fetched live from OpenAlex

A three-axis load detector has been designed and manufactured utilizing four piezoresistive sensors on a flexible silicon membrane. The detector was prototyped using bulk microfabrication techniques on a single-crystal silicon wafer and was designed to detect normal and shear loadings applied to the membrane. Finite element analysis and experimental calibration methods have been used to determine the shear and normal sensitivity values. Device parameters were modified with emphasis on increasing the absolute shear to normal sensitivity ratio of the sensors without reducing their ultimate strength. It was determined that the shear to normal sensitivity ratio greater than 0.5 would allow detection of shear loads considering experimental error present. For devices with square membranes having 1000 µm edge lengths and 65 µm thicknesses, this amount of shear sensitivity was achievable using a mesa with a height of at least 150 µm.

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)0.001
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 score0.028
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.024
GPT teacher head0.220
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

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

Citations9
Published2011
Admission routes1
Has abstractyes

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