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Record W1914320033 · doi:10.1039/c5nr03299g

Nanohybrid conjugated polyelectrolytes: highly photostable and ultrabright nanoparticles

2015· article· en· W1914320033 on OpenAlexfundno aff
Ghinwa H. Darwish, Pierre Karam

Bibliographic record

VenueNanoscale · 2015
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsnot available
FundersThe Academy of Sciences for the Developing WorldMcGill University
KeywordsPolyelectrolyteConjugated systemNanotechnologyNanoparticleMaterials sciencePolymer

Abstract

fetched live from OpenAlex

We present a general and straightforward one-step approach to enhance the photophysical properties of conjugated polyelectrolytes. Upon complexation with an amphiphilic polymer (polyvinylpyrrolidone), an anionic conjugated polyelectrolyte (poly[5-methoxy-2-(3-sulfopropoxy)-1,4-phenylenevinylene]) was prepared into small nanoparticles with exceptional photostability and brightness. The polymer fluorescence intensity was enhanced by 23 -fold and could be easily tuned by changing the order of addition. Single molecule experiments revealed a complete suppression of blinking. In addition, after only losing 18% of the original intensity, a remarkable amount of photons were emitted per particle (∼10(9), on average). This number is many folds greater than popular organic fluorescent dyes. We believe that an intimate contact between the two polymers is shielding the conjugated polyelectrolyte from the destructive photooxidation. The prepared nanohybrid particles will prove instrumental in single particle based fluorescent assays and can serve as a probe for the current state-of-the-art bioimaging fluorescence techniques.

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 score0.005
Threshold uncertainty score0.889

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)0.0000.001

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 head0.016
GPT teacher head0.232
Teacher spread0.216 · 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

Citations18
Published2015
Admission routes1
Has abstractyes

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