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Record W2106744592 · doi:10.1109/mnrc.2008.4683414

Development of an electron tunneling force sensor for the use in microassembly

2008· article· en· W2106744592 on OpenAlexaff
Lidai Wang, James K. Mills, William L. Cleghorn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsQuantum tunnellingActuatorElectrodeMicroelectromechanical systemsDisplacement (psychology)VoltageFabricationElectronMaterials scienceSensitivity (control systems)Process (computing)OptoelectronicsElectrical engineeringComputer scienceElectronic engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

We present the development of an electron tunneling force sensor for use in microassembly and micromanipulation tasks. The force sensor consists of flexible structural members, to which two electrodes are attached, which deflect under the application of grasping forces, and a thermal actuator. A feedback controller is developed to maintain a constant tunneling current across the two electrodes, thereby maintaining constant displacement of the electrodes. Measurement of the voltage applied to the thermal actuator to maintain a constant electrode displacement allows the grasping force to be determined. The design and modeling of the force sensor are addressed. The fabrication of sharp tunnel tips using commercially available MEMS process is investigated. A sharp tunnel tip with width less than 100 nm is achieved using the PolyMUMPs process. The electron tunneling force sensor has extremely high sensitivity, which make it very suitable for micromanipulation tasks.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.041
GPT teacher head0.298
Teacher spread0.257 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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