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Record W1971660894 · doi:10.1063/1.3694972

Methods and instrumentation for piezoelectric motors

2012· article· en· W1971660894 on OpenAlexafffund
Benedict Drevniok, William Paul, K. R. Hairsine, A. B. McLean

Bibliographic record

VenueReview of Scientific Instruments · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsQueen's University
FundersMcGill University
KeywordsPiezoelectricityInertial frame of referenceComputer sciencePiezoelectric motorElectronicsTransducerMicroscopeRigidity (electromagnetism)Ultrasonic motorElectrical engineeringMechanical engineeringAcousticsMaterials sciencePhysicsEngineeringOptics

Abstract

fetched live from OpenAlex

Because of their compact form factor and rigidity, piezoelectric motors are used in scanning probe microscopes that operate at low temperature and high magnetic field. Here we present detailed information to facilitate the assembly, operation, and characterization of inertial motors. Specifically, a model of the motor is developed and used to identify different regions of operation. Drive electronics with high slew rate and large output current are described and a step-by-step procedure for assembling piezoelectric shear stacks is detailed. Additionally, a novel reflective object sensor is described and used to characterize a Pan-style inertial motor that was designed and assembled using the concepts 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)0.001
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.029
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0290.021

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 head0.021
GPT teacher head0.376
Teacher spread0.355 · 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
GenreMethods

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

Citations25
Published2012
Admission routes2
Has abstractyes

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