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Record W1978248023 · doi:10.1063/1.4721460

Piezoresistive strain sensing using carbon nanotube forests suspended by Parylene-C membranes

2012· article· en· W1978248023 on OpenAlexaff
Anas Bsoul, Mohamed Sultan Mohamed Ali, Alireza Nojeh, Kenichi Takahata

Bibliographic record

VenueApplied Physics Letters · 2012
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGauge factorParylenePiezoresistive effectCarbon nanotubeMaterials scienceMembraneStrain gaugeSensitivity (control systems)Strain (injury)NanotubeBendingOptoelectronicsPolymerNanotechnologyComposite materialFabricationChemistryElectronic engineering

Abstract

fetched live from OpenAlex

We present a strain gauge that uses a carbon nanotube (CNT) forest, partially embedded in a Parylene-C membrane, as a piezoresistor. The device exhibits high sensitivity with a gauge factor of 4.52 or higher for strains up to ∼1.5%, offering much higher sensitivity in the strain range than those reported for other types of CNT-forest/polymer composite piezoresistors. The gauge also shows a linear response to bending strains generated by forces applied perpendicularly to the membrane with a 55-ppm/mN sensitivity. These findings suggest promising characteristics for a variety of sensing applications of the CNT-forest/Parylene film.

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 score0.000
Threshold uncertainty score0.001

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)0.0000.000

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 head0.016
GPT teacher head0.239
Teacher spread0.223 · 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

Citations12
Published2012
Admission routes1
Has abstractyes

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