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Record W1676599077 · doi:10.1063/1.2184657

HBAR-Spectroscopy Used for Materials Characterization

2006· article· en· W1676599077 on OpenAlexaff
Martin Viens

Bibliographic record

VenueAIP conference proceedings · 2006
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
Fundersnot available
KeywordsOvertoneResonatorCharacterization (materials science)PiezoelectricityMaterials scienceResonance (particle physics)Substrate (aquarium)Resonant ultrasound spectroscopyTransducerSpectroscopySeries (stratigraphy)Equivalent circuitAcousticsSpectral lineOptoelectronicsPhysicsComposite materialAtomic physicsNanotechnology

Abstract

fetched live from OpenAlex

Resonance spectra of a High‐overtone Bulk Acoustic Resonator (HBAR), consisting of a substrate plate and a piezoelectric transducer, can be used to evaluate density, elastic constants and mechanical loss of the substrate material. It is shown that density and elastic constants can be determined independently from the spacing of the parallel resonant frequencies whereas mechanical loss can be assessed from the parallel resonance Q‐value. The accuracy of the presented method is evaluated though a series of numerical simulations based on an equivalent circuit model. Application to the characterization of some industrial materials is discussed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.124
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

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 head0.012
GPT teacher head0.221
Teacher spread0.209 · 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 teacher head, 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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