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Record W4205471114 · doi:10.1002/adom.202101117

Label‐Free Spontaneous Raman Sensing in Photonic Crystal Fibers with Nanomolar Sensitivity

2022· article· en· W4205471114 on OpenAlex
Basil G. Eleftheriades, Emily E. Storey, Amr S. Helmy

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Optical Materials · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpectroscopy Techniques in Biomedical and Chemical Research
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceRaman spectroscopyPolystyreneThermophoresisPhotonic-crystal fiberNanoparticlePhotonic crystalSensitivity (control systems)Deposition (geology)OptoelectronicsEvaporationNanotechnologyFiberPolymerOpticsComposite material

Abstract

fetched live from OpenAlex

Abstract An approach to significantly enhance spontaneous Raman sensitivity through the formation of a thin film via thermophoresis along with evaporation at the facet of a hollow‐core photonic crystal fiber is reported for the first time. Sensitivity of detection is increased by more than 6 orders of magnitude for both organic and inorganic nanoparticles, facilitating the search for trace analytes in solution. Detection of two nanoparticles, alumina and polystyrene, is demonstrated down to 392 nM without the use of surface‐enhanced Raman spectroscopy or other chemical‐based procedures. This new thin‐film deposition approach simplifies the simultaneous detection and analysis of small trace compounds, a previously arduous task using conventional spontaneous Raman.

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.

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 score0.019
Threshold uncertainty score0.654

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 science0.0000.001
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 head0.006
GPT teacher head0.264
Teacher spread0.258 · 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