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Record W2043135978 · doi:10.1021/ma802460q

Fiber-Optic Detection of Explosives Using Readily Available Fluorescent Polymers

2009· article· en· W2043135978 on OpenAlexaff
Huy Nguyen, Xianzhen Li, Ning Wang, Zhi Yuan Wang, Jianjun Ma, Wojtek J. Bock, Dongge Ma

Bibliographic record

VenueMacromolecules · 2009
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsCarleton UniversityUniversité du Québec en Outaouais
Fundersnot available
KeywordsPolymerFluorescenceFluoreneExplosive detectionAnalyteFiberExplosive materialChemistryMaterials scienceAnalytical Chemistry (journal)Quenching (fluorescence)PhotochemistryPolymer chemistryOrganic chemistryChromatographyOptics

Abstract

fetched live from OpenAlex

A series of simple fluorescent polymers were readily synthesized by palladium-catalyzed Suzuki coupling reactions of dibromoterephthalates containing the small methyl and large cholesteryl esters with bisboronic esters derived from alkylated fluorene and N -hexyldiphenylamine. The polymers had an inherent viscosity ranging from 0.25 to 0.74 dL/g and were characterized by spectroscopic methods. The glass transition temperatures for these polymers ranged from 90 to 104 °C, and the decomposition temperatures were in a range of 291−435 °C in nitrogen. All the polymers emit around 450−530 nm with the absolute fluorescence quantum efficiencies up to 61%. The polymers were tested for detection of the vapor of explosive analyte (2,4-dinitrotoluene) as a thin film coated on glass substrate and on optic-fiber tips. Explosive detection using the polymer-coated optic-fiber probe has been demonstrated to be fast and sensitive, with the fluorescence quenching efficiency reaching 48% within 25 s or 61% within the first minute.

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 categoriesInsufficient 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 score0.003
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)0.0010.001

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 head0.019
GPT teacher head0.243
Teacher spread0.224 · 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

Citations47
Published2009
Admission routes1
Has abstractyes

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