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Record W3040994752

Theoretical study of a phononic structure for bio-sensing applications

2019· article· en· W3040994752 on OpenAlexaff
Jérémy Bonhomme, Mourad Oudich, Pedro Alberto Segura Chavez, Lucile Olive, D. Beyssen, Paul G. Charette, F. Sarry

Bibliographic record

VenueIEEE Conference Proceedings · 2019
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMaterials scienceSensitivity (control systems)FabricationAperture (computer memory)RADIUSStackingOpticsSubstrate (aquarium)WavelengthBand gapOptoelectronicsAcousticsElectronic engineeringPhysicsEngineeringComputer science
DOInot available

Abstract

fetched live from OpenAlex

In this work, we investigate the evolution of the properties of a pillar phononic crystal in order to simplify the fabrication process by reducing the thickness of the layer. The structure is constructed by stacking alternate layers of SiO2 and Tungsten. The reduction of the dimensions moves the band gap to the upper frequencies and it is possible to adjust its aperture with the ratio comparing the radius of the cylinder with the layers’ thickness. On a substrate, the pillars give resonant modes that can be excited by shear surface waves and gives a sharp peak in the transmission spectrum of the surface wave with a very high quality factor. We also study the theoretical mass sensitivity of the device and we propose a numerical method to determine the theoretical maximum sensitivity that could be obtain by the pillars system. This pillar based metasurface presents a very promising mass sensitivity and a possible way to increase the performance of SAW bio-sensors.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.015
GPT teacher head0.256
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2019
Admission routes1
Has abstractyes

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