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Record W4408319875 · doi:10.1002/pssb.202400609

Optimizing Phononic Crystal Waveguides for Enhanced Surface Acoustic Wave Confinement

2025· article· en· W4408319875 on OpenAlexafffund
Kan Singh, Gabe Willson, J. A. H. Stotz

Bibliographic record

Venuephysica status solidi (b) · 2025
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsQueen's University
FundersCMC Microsystems
KeywordsAcoustic waveWaveguideSurface acoustic wavePhysical acousticsOpticsCoupling (piping)Materials sciencePiezoelectricityAcousticsPhysics

Abstract

fetched live from OpenAlex

Through the use of strain and induced piezoelectric fields, surface acoustic waves (SAWs) have been shown to control quantum information processes, such as single photon emission and the coherent transport of electron spins. Regarding the latter, systems using plane surface waves have provided suitable demonstration systems, but to build complexity, more control over the acoustic wave may be required. One method for acoustic control is the use of phononic crystals consisting of periodic arrays of nanofabricated holes on the surface of a device. These inclusions form a metamaterial‐like layer with properties different from the host material to dictate the physics of wave motion. Exploiting these surface properties can lead to acoustic waveguides, which can be designed to control the path of the SAWs. The design parameters of a new type of phononic crystal waveguide are explored that use twofold elliptical cylinder inclusions to create a slow region that also limits coupling and radiative loss to bulk acoustic modes. Such a waveguide will be the foundational piece in an acoustic circuit that can then mediate complex spin transport geometries.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.915
Threshold uncertainty score1.000

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 head0.019
GPT teacher head0.271
Teacher spread0.253 · 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.

Study designSimulation or modeling
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

Citations1
Published2025
Admission routes2
Has abstractyes

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