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Record W2326479065 · doi:10.1021/ma2024304

π-Conjugated Fluorescent Azomethine Copolymers: Opto-Electronic, Halochromic, and Doping Properties

2012· article· en· W2326479065 on OpenAlexafffund
Satyananda Barik, Thomas Bletzacker, W. G. Skene

Bibliographic record

VenueMacromolecules · 2012
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsBombardier (Canada)Université de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThiopheneTrifluoroacetic acidConjugated systemPhotochemistryChemistryFluoreneFluorescenceProtonationComonomerCopolymerPolymer chemistryPolymerOrganic chemistry

Abstract

fetched live from OpenAlex

A series of new conjugated copolyazomethines consisting of alternating fluorene and thiophenes were prepared. Different thiophenes were incorporated for examining their effect on the polymer’s opto-electronic properties. Blue, red, and green emissions were possible contingent on the thiophene comonomer and the placement of the azomethine nitrogen. Most notably, the polyazomethines were fluorescent both in solution and thin films with measured absolute fluorescent quantum yields (Φ fl ) ca. 10%. Their fluorescence could be enhanced to near unity at 77 K. High Φ fl were also measured with the addition of trifluoroacetic acid (TFA). The polyazomethines’ color could also be reversible altered with protonation/neutralization with TFA/triethylamine. Similar to the halochromic effect, the polyazomethines could be reversibly oxidized/neutralized with FeCl 3 /hydrazine, resulting in reversible color changes between red and blue. The oxidation potentials and the reversibility of the anodic process were contingent on the type of thiophene incorporated into the copolymer. The stability of the electrochemically produced radical cation and the azomethine’s resistance toward hydrolysis were also investigated with a model thiophene–fluorene–thiophene bisazomethine.

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 score0.038
Threshold uncertainty score0.927

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 head0.008
GPT teacher head0.197
Teacher spread0.188 · 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

Citations84
Published2012
Admission routes2
Has abstractyes

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