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Record W2104336154 · doi:10.1109/itherm.2010.5501321

Optical waveguiding through thermal boundary layer development over a microchannel walls

2010· article· en· W2104336154 on OpenAlexaff
Seyed Reza Mahmoudi, Jayshri Sabarinathan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsWestern University
Fundersnot available
KeywordsMicrochannelLaminar flowMaterials scienceCladding (metalworking)Boundary layerRefractive indexHagen–Poiseuille equationTemperature gradientWaveguideOpticsMass flow rateThermalBoundary value problemVolumetric flow rateIsothermal processMechanicsMass flowFlow (mathematics)Composite materialThermodynamicsOptoelectronicsPhysicsNanotechnology

Abstract

fetched live from OpenAlex

A single-liquid-core/liquid-clad optical waveguide whose refractive index changes thermally is proposed and numerically simulated. The waveguide consists of a large aspect ratio- microchannel heated on its both parallel flat walls. The steady state laminar Poiseuille flow of cold water which is introduced to the heated-microchannel forms a stable thermal boundary layer adjacent to the isothermal heated walls. Establishment of the thermal boundary layer causes the lateral refractive index gradient across the microchannel which is enough for waveguiding at and above a particular mass flow rate for a given wall temperature. The thermal boundary layer thickness which operates as a cladding region can be easily reconfigured by surface temperature and mass flow rate. The cutoff frequencies for TE mode of the optical waveguide were calculated at different mass flow rates and wall temperature through the microchannel.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.237
Teacher spread0.222 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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