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Record W2104191382 · doi:10.3390/s130201425

Fiber Optic pH Sensor with Self-Assembled Polymer Multilayer Nanocoatings

2013· article· en· W2104191382 on OpenAlexafffund
Liyang Shao, Ming‐Jie Yin, Hwa‐Yaw Tam, Jacques Albert

Bibliographic record

VenueSensors · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsCarleton University
FundersHong Kong Polytechnic UniversityNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaCanada Research Chairs
KeywordsMaterials scienceRefractive indexFiber Bragg gratingAcrylic acidLayer (electronics)Fiber optic sensorFiberWavelengthOptical fiberOptoelectronicsOpticsPolymerNanotechnologyComposite material

Abstract

fetched live from OpenAlex

A fiber-optic pH sensor based on a tilted fiber Bragg grating (TFBG) with electrostatic self-assembly multilayer sensing film is presented. The pH sensitive polymeric film, poly(diallyldimethylammonium chloride) (PDDA) and poly(acrylic acid) (PAA) was deposited on the circumference of the TFBG with the layer-by-layer (LbL) electrostatic self-assembly technique. The PDDA/PAA film exhibits a reduction in refractive index by swelling in different pH solutions. This effect results in wavelength shifts and transmission changes in the spectrum of the TFBG. The peak amplitude of the dominant spectral fringes over a certain window of the transmission spectrum, obtained by FFT analysis, has a near-linear pH sensitivity of 117 arbitrary unit (a.u.)/pH unit and an accuracy of ±1 a.u. (in the range of pH 4.66 to pH 6.02). The thickness and surface morphology of the sensing multilayer film were characterized to investigate their effects on the sensor's performance. The dynamic response of the sensor also has been studied (10 s rise time and 18 s fall time for a sensor with six bilayers of PDDA/PAA).

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.064
Threshold uncertainty score1.000

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)0.0010.004

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 head0.005
GPT teacher head0.196
Teacher spread0.191 · 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.

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

Citations43
Published2013
Admission routes2
Has abstractyes

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