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Record W2909835698 · doi:10.7567/1347-4065/ab0008

Temperature dependent angular dispersions of surface acoustic waves on GaAs

2019· article· en· W2909835698 on OpenAlexafffund
Mats Powlowski, F. Sfigakis, Na Young Kim

Bibliographic record

VenueJapanese Journal of Applied Physics · 2019
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsPerimeter InstituteUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and ScienceCMC Microsystems
KeywordsPiezoelectricityMaterials scienceAcoustic waveSurface acoustic waveNetwork analyzer (electrical)Crystal (programming language)TransducerGallium arsenideAcousticsOptoelectronicsPhysicsComposite materialElectrical engineering

Abstract

fetched live from OpenAlex

Abstract We measure the phase velocities of surface acoustic waves (SAWs) propagating at different crystal orientations on (001)-cut GaAs substrates and their temperature dependance. We design and fabricate sets of interdigital transducers (IDTs) to induce 4 μ m SAWs via the inverse piezoelectric (PZE) effect between the PZE [110] direction (set as θ = 0°) and the non-PZE [100] direction ( θ = 45°) on GaAs. We also prepare ZnO film sputtered GaAs substrates in order to launch SAWs efficiently by IDTs even in the non-PZE direction. We quantify acoustic velocities between 1.4 and 300 K from the resonant frequencies in the S 11 parameter using a network analyzer. We observe parabolic velocity–temperature trends at all θ -values both on GaAs and ZnO/GaAs substrates. Below 200 K, in ZnO/GaAs substrates slower SAW modes appear around the [110] direction, which are unseen at RT.

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 score0.411
Threshold uncertainty score0.575

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 head0.005
GPT teacher head0.195
Teacher spread0.190 · 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

Citations6
Published2019
Admission routes2
Has abstractyes

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