MétaCan
Menu
Back to cohort
Record W2028498486 · doi:10.1021/ja042854f

A New Approach to Highly Electrooptically Active Materials Using Cross-Linkable, Hyperbranched Chromophore-Containing Oligomers as a Macromolecular Dopant

2005· article· en· W2028498486 on OpenAlexaff
Yaowen Bai, Naiheng Song, Jian Gao, Xun Sun, Xiaomei Wang, Guomin Yu, Zhi Yuan Wang

Bibliographic record

VenueJournal of the American Chemical Society · 2005
Typearticle
Languageen
FieldMaterials Science
TopicNonlinear Optical Materials Research
Canadian institutionsCarleton University
Fundersnot available
KeywordsChromophoreDopantOligomerMacromoleculePolymerPolingChemistryDopingPolymer chemistryChemical engineeringMaterials sciencePhotochemistryOrganic chemistryOptoelectronicsDielectric

Abstract

fetched live from OpenAlex

A new, practical approach to a variety of highly electrooptically active polymers for device development is described. It involves the use of a new thermally cross-linkable, hyperbranched oligomer containing nonlinear optical (NLO) chromophores as a macromolecular dopant in a common host polymer. A series of NLO polymeric blends were readily formulated and showed large and stable electrooptic (EO) coefficients (up to 65 pm/V). In comparison with previously studied linear NLO polyimides and guest-host polymers doped with molecular chromophores and even linear NLO analogous oligomers, this new approach offers clear advantages for device development in terms of improved poling efficiency, larger EO coefficients, good temporal stability, and versatile material formulation.

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)0.000
metaresearch head score (Gemma)0.000
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: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.314
Teacher spread0.297 · 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
GenreMethods

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

Citations143
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Chemical SocietySame topicNonlinear Optical Materials ResearchFrench-language works237,207