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Record W4386250535 · doi:10.1364/oe.497679

In-situ monitoring of refractive index change during water-ice phase transition with a multiresonant fiber grating

2023· article· en· W4386250535 on OpenAlexafffund
Yan Zhou, Wenjun Zhou, Ziqiao Ren, Yang Zhang, Huaping Gong, Changyu Shen, Rui‐Pin Chen, Jacques Albert

Bibliographic record

VenueOptics Express · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsCarleton University
FundersNational Key Research and Development Program of ChinaNatural Sciences and Engineering Research Council of CanadaNatural Science Foundation of Liaoning ProvinceNational Natural Science Foundation of China
KeywordsMaterials scienceRefractive indexFiber Bragg gratingOpticsPhase transitionGratingWavelengthOptical fiberPhase (matter)FiberLong-period fiber gratingFiber optic sensorGraded-index fiberOptoelectronicsPhysicsComposite material

Abstract

fetched live from OpenAlex

In-situ monitoring of refractive index changes during a liquid-solid phase transition is achieved by measurement of the transmission spectrum from a single tilted fiber Bragg grating immersed in water. Differential wavelength shifts of multiple mode resonances are used to eliminate cross-talk from temperature, throughout the phase transition, and from strains occurring after solidification. The measured sudden shift of refractive index at the phase transition is shown to be consistent with the expected difference from water to ice, in spite of the observed onset of compressive strain on the fiber by the frozen water. Beyond the obvious application to research on the dynamics of liquid-solid phase transitions, this work demonstrates the multiparameter measurement capabilities of multiresonant gratings.

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 score0.130
Threshold uncertainty score0.687

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 head0.021
GPT teacher head0.265
Teacher spread0.244 · 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

Citations6
Published2023
Admission routes2
Has abstractyes

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