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Record W2558623945 · doi:10.1021/acs.langmuir.6b03920

Orthogonally Processable Carbazole-Based Polymer Thin Films by Nitroxide-Mediated Polymerization

2016· article· en· W2558623945 on OpenAlexafffund
Owen A. Melville, Benjamin King, Christian J. Imperiale, Benoît H. Lessard

Bibliographic record

VenueLangmuir · 2016
Typearticle
Languageen
FieldEngineering
TopicOrganic Light-Emitting Diodes Research
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials sciencePolymerizationCarbazolePolymerThin filmChemical engineeringNitroxide mediated radical polymerizationIndium tin oxideCopolymerSpin coatingOLEDPolymer chemistrySubstrate (aquarium)Organic electronicsLayer (electronics)Radical polymerizationNanotechnologyPhotochemistryChemistryComposite material

Abstract

fetched live from OpenAlex

Cross-linking of hole-transporting polymer thin films in organic light emitting diodes (OLEDs) has been shown to increase device efficacy when subsequent layers are deposited from solution. This improvement, due to resistance of the films to dissolution, could also be achieved by covalently grafting the polymer film to the substrate. Using nitroxide-mediated polymerization (NMP), we synthesized a novel poly(9-(4-vinylbenzyl)-9H-carbazole) (poly(VBK)) copolymer which can be cross-linked and also developed two simple methods for the grafting-to or grafting-from, also known as surface-initiated polymerization, of poly(VBK) to indium tin oxide (ITO) substrates. All three of these methods produced thin films that could be orthogonally processed; that is, they resisted dissolution when the spin-coating of a subsequent layer was simulated. Similar electrochemical behavior for the poly(VBK) films was observed regardless of the technique used, suggesting that all three techniques could be used in the engineering of organic electronic devices. We expect that all three methods would be worth investigating in the solution-based assembly of OLEDs and other organic electronic devices.

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 score0.015
Threshold uncertainty score0.805

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)0.0010.000

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 head0.004
GPT teacher head0.193
Teacher spread0.189 · 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

Citations9
Published2016
Admission routes2
Has abstractyes

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