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Record W3015266138 · doi:10.1364/ol.392511

Microfluidic flow direction and rate vector sensor based on a partially gold-coated TFBG

2020· article· en· W3015266138 on OpenAlexaff
Changyu Shen, Dejun Liu, Xiaokang Lian, Tingting Lang, Chunliu Zhao, Yuliya Semenova, Jacques Albert

Bibliographic record

VenueOptics Letters · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsCarleton University
FundersNational Natural Science Foundation of China
KeywordsMaterials scienceFiber Bragg gratingWavelengthOpticsMicrofluidicsVolumetric flow rateGratingOptoelectronicsNanotechnology

Abstract

fetched live from OpenAlex

In microfluidic chips applications, the monitoring of the rate and the direction of a microfluidic flow is very important. Here, we demonstrate a liquid flow rate and a direction sensor using a partially gold-coated tilted fiber Bragg grating (TFBG) as the sensing element. Wavelength shifts and amplitude changes of the TFBG transmission resonances in the near infrared reveal the direction of the liquid flowing along the fiber axis in the vicinity of the TFBG due to a nanoscale gold layer over part of the TFBG. For a device length of 10 mm (and a diameter of 125 µm for easy insertion into microfluidic channels), the flow rates and the direction can be detectable unequivocally. The TFBG waveguiding properties allow such devices to function in liquids with refractive indices ranging from 1.33 to about 1.40. In addition, the proposed sensor can be made inherently temperature-insensitive by referencing all wavelengths to the wavelength of the core mode resonance of the grating, which is isolated from the fiber surroundings.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
Threshold uncertainty score0.974

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 head0.011
GPT teacher head0.195
Teacher spread0.185 · 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 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

Citations36
Published2020
Admission routes1
Has abstractyes

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