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Record W2063605609 · doi:10.1115/imece2006-14938

Modal Interactions in Contact-Mode Atomic Force Microscopes

2006· article· en· W2063605609 on OpenAlexaff
Haider N. Arafat, Ali H. Nayfeh, Eihab Abdel‐Rahman

Bibliographic record

VenueApplied Mechanics · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsStiffnessAtomic force microscopyModalResonance (particle physics)Excited stateMode (computer interface)Normal modeNon-contact atomic force microscopyMaterials scienceModal analysisOpticsNoise (video)ThermalPhysicsAcousticsVibrationKelvin probe force microscopeAtomic physicsNanotechnologyThermodynamicsComposite material

Abstract

fetched live from OpenAlex

Atomic force microscopes (AFM) are used to estimate material and surface properties. When using contact-mode AFM, the specimen or the probe is excited near a natural frequency of the system to estimate the linear coefficient of the contact stiffness. Because higher modes offer lower thermal noise, higher quality factors, and higher sensitivity to stiff samples, their use in this procedure is more desirable. However, these modes are candidates for internal resonances, where the energy being fed into one mode may be channeled to another mode. If such interactions are ignored, the results obtained from the probe may be distorted. The method of multiple scales is used to derive an approximate analytical expression to the probe response in the presence of two-to-one autoparametric resonance between the second and third modes. We examine characteristics of this solution in relation to a single-mode response and consider its implications in AFM measurements.

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)0.003
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.006
GPT teacher head0.267
Teacher spread0.261 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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