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Record W2941513309 · doi:10.1088/1367-2630/ab1bb7

Robust nonreciprocal acoustic propagation in a compact acoustic circulator empowered by natural convection

2019· article· en· W2941513309 on OpenAlexafffund
Xingxing Liu, Xiaobing Cai, Qiuquan Guo, Jun Yang

Bibliographic record

VenueNew Journal of Physics · 2019
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsCirculatorPhysicsAcousticsMesoscopic physicsMetamaterialMiniaturizationAeroacousticsAcoustic waveCondensed matter physicsOpticsElectrical engineeringSound pressureEngineering

Abstract

fetched live from OpenAlex

Abstract The development of the quantum Hall effect in condensed matter physics that breaks time-reversal symmetry by magnetic biasing has inspired its analog in classical nonreciprocal acoustics. Nonreciprocal acoustic propagation is highly desirable to control acoustics in isolation, broadband unidirectional transmission, and topologically robust to structural disorders or defects. So far, these fascinating properties have been investigated through fan-induced moving media, acoustic capacitance adjustment and acoustic metamaterials. However, these may be associated with disadvantages including extra noise and limited dynamic controlling performance. Here we overcome these limitations by introducing heat-induced natural convection into acoustic circulator, and demonstrate that the classical acoustic circulator with thermal management can realize robust nonreciprocal acoustic propagation. The concept of combining heat-induced natural convection and aeroacoustics creates a new practical paradigm and increases the feasibility for nonreciprocal acoustics due to merits of dynamic control, versatile topological structures, and miniaturization in the absence of moving parts.

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 score0.029
Threshold uncertainty score0.475

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 head0.023
GPT teacher head0.260
Teacher spread0.237 · 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

Citations15
Published2019
Admission routes2
Has abstractyes

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