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Record W2499866862 · doi:10.1002/macp.201600260

Polymeric Photoinitiators: A New Search toward High Performance Visible Light Photoinitiating Systems

2016· article· en· W2499866862 on OpenAlexaff
Jing Zhang, Pu Xiao, Frédéric Dumur, Chang Guo, Wei Hong, Yuning Li, Didier Gigmès, Bernadette Graff, Jean‐Pierre Fouassier, Jacques Lalevée

Bibliographic record

VenueMacromolecular Chemistry and Physics · 2016
Typearticle
Languageen
FieldChemistry
TopicPhotopolymerization techniques and applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhotopolymerCationic polymerizationPolymerizationPhotochemistryPhotoinitiatorMaterials sciencePolymerVisible spectrumDiodePolymer chemistryOptoelectronicsChemistryComposite materialMonomer

Abstract

fetched live from OpenAlex

A series of conjugated polymers and oligomers previously used in organic photovoltaics and organic light‐emitting diodes (OLEDs) have been examined for the first time as photoinitiators of polymerization. They address the present and future challenges facing photopolymerization: requirement of high extinction molar coefficients, absorption over the whole visible spectrum, ability to easily withdraw or release electrons. Interestingly, these compounds initiate the cationic polymerization of epoxides or the free radical polymerization of acrylates upon exposure of the photocurable formulations to a LED emitting at 405 nm. Some of them can potentially operate under blue, green, or red laser diodes. image

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.011
GPT teacher head0.227
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 source (direct Gemma or distilled Codex), 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

Citations21
Published2016
Admission routes1
Has abstractyes

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