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Record W2067524412 · doi:10.1364/boe.4.001472

Laser-written photonic crystal optofluidics for electrochromatography and spectroscopy on a chip

2013· article· en· W2067524412 on OpenAlexafffund
Moez Haque, Nicole S. Zacharia, Stephen Ho, Peter R. Herman

Bibliographic record

VenueBiomedical Optics Express · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOptofluidicsAnalyteMicrofluidicsMaterials scienceLab-on-a-chipPhotonicsElectrochromatographyLaserFemtosecondOptoelectronicsNanotechnologyCapillary electrochromatographyOpticsCapillary actionChemistryChromatography

Abstract

fetched live from OpenAlex

Femtosecond laser processes were optimized for nonlinear interactions with various optical materials to develop a novel biophotonic lab-on-a-chip device that integrates laser-formed waveguides (WGs), microfluidic channels and photonic crystals (PCs). Such integration seeks the unique demonstration of dual PC functionalities: (1) efficient chromatographic separation and filtration of analytes through a porous PC embedded inside a microfluidic channel and (2) optofluidic spectroscopy through embedded WGs that probe PC stopband shifts as varying analyte concentrations flow and separate. The building blocks together with their integration were demonstrated, providing embedded porous PCs through which electrochromatography drove an accelerated mobile phase of analyte and an optical stopband was probed via integrated buried WGs. Together, these laboratory results underpin the promise of simultaneous chromatographic and spectroscopic capabilities in a single PC optofluidic device.

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 score0.210
Threshold uncertainty score0.757

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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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

Citations11
Published2013
Admission routes2
Has abstractyes

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