MétaCan
Menu
Back to cohort
Record W2088199628 · doi:10.1143/jjap.40.3599

Generation and Detection of 400-MHz-Band Surface Acoustic Waves Using the Phase Velocity Scanning Method

2001· article· en· W2088199628 on OpenAlexaff
Hideo Cho, Yusuke Tsukahara, Kazushi Yamanaka

Bibliographic record

VenueJapanese Journal of Applied Physics · 2001
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsWaferMaterials sciencePhase velocityOpticsAnisotropySurface acoustic wavePhase (matter)Crystal (programming language)Acoustic waveModulusInverseOptoelectronicsComposite materialChemistryPhysicsGeometry

Abstract

fetched live from OpenAlex

We succeeded in generating and detecting high-frequency surface acoustic waves (SAWs) up to 400 MHz by improving an apparatus for the scanning interference fringes (SIF) approach of the phase velocity scanning method using an optical knife-edge technique with a single lens. Using the new SIF apparatus, we confirmed that we are able to measure the SAW velocity anisotropy of a single-crystal Si(001) wafer within 0.1% relative error. We also measured the velocity anisotropy of Sezawa waves on a Si(001) wafer with a 1430-nm-thick Cu film and estimated Young's modulus and thickness of the Cu film by an inverse analysis. The estimated Young's modulus was close to that of bulk Cu (129.8 GPa). On a single-crystal Si(001) wafer with thinner Cu films (270–700 nm), we measured the SAW velocity along the [110] direction of the Si substrate by the time-of-flight method. The measured velocities decreased with increasing film thickness. The measured velocity for the thicker sample approximated the group velocity calculated from the estimated value for 1430-nm-thick Cu film by the inverse analysis.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.387

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 head0.033
GPT teacher head0.286
Teacher spread0.254 · 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

Citations2
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueJapanese Journal of Applied PhysicsSame topicAcoustic Wave Resonator TechnologiesFrench-language works237,207