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Record W2135319932 · doi:10.1109/tnano.2007.901910

Toward Carbon Nanotube-Based AFM Cantilevers

2007· article· en· W2135319932 on OpenAlexaff
Jianhua Tong, Yu Sun

Bibliographic record

VenueIEEE Transactions on Nanotechnology · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMechanical and Optical Resonators
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCantileverCarbon nanotubeMaterials scienceMicrofabricationGauge factorNanotechnologyCarbon nanotube actuatorsSiliconAtomic force microscopyElectrodeCarbon fibersMechanical properties of carbon nanotubesNanotubeOptoelectronicsComposite materialFabricationChemistry

Abstract

fetched live from OpenAlex

The mechanical properties of carbon nanotubes have been widely employed to enhance the performance of atomic force microscopy (AFM) cantilever tips. Utilizing the electromechanical properties of carbon nanotubes, this paper investigates the potential of using carbon nanotubes as active strain sensing elements on AFM cantilevers. A batch microfabrication process was developed to construct silicon microcantilevers. Multiwalled carbon nanotubes were dielectrophoretically assembled between electrodes. Based on the characterization results of 12 devices, the CNT-based cantilevers demonstrated a linear relationship between resistance changes and externally applied strain. The gauge factor ranged from 78.84 to 134.40 for four different device configurations.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.237
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

Citations19
Published2007
Admission routes1
Has abstractyes

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