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Record W3197962240 · doi:10.3390/polym13172914

Structural Geometry Variation of 1,4-Naphthalene-Based Co-Polymers to Tune the Device Performance of PVK-Host-Based OLEDs

2021· article· en· W3197962240 on OpenAlexaff
Qian Liu, Dhanashree Moghe, Gopa Sardar, Sergei Manzhos, Steven E. Bottle, Aung Ko Ko Kyaw, Dinesh Kabra, Prashant Sonar

Bibliographic record

VenuePolymers · 2021
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsInstitut National de la Recherche Scientifique
FundersScience and Engineering Faculty, Queensland University of TechnologyAustralian Research CouncilBasic and Applied Basic Research Foundation of Guangdong ProvinceSouthern University of Science and Technology
KeywordsMaterials scienceTriphenylamineOLEDFluoreneThermal stabilityPolymerCarbazoleCopolymerSuzuki reactionPolymer chemistryElectroluminescenceArylOptoelectronicsPhotochemistryChemical engineeringComposite materialChemistryOrganic chemistryLayer (electronics)

Abstract

fetched live from OpenAlex

Blue-color-emitting organic semiconductors are of significance for organic light-emitting diodes (OLEDs). In this study, through Suzuki coupling polymerization, three 1,4-naphthalene-based copolymers-namely, PNP(1,4)-PT, PNP(1,4)-TF, and PNP(1,4)-ANT-were designed and synthesized. The variation of comonomers, phenothiazine (PT), triphenylamine substituted fluorene (TF), and anthanthrene (ANT), effectively tuned the emitting color and device performance of poly(9-vinyl carbazole) (PVK)-based OLEDs. Especially, the polymer PNP(1,4)-TF, bearing perpendicular aryl side groups, showed a most twisted structural geometry, which enabled an ultra-high thermal stability and a best performance with blue emitting in PVK-host-based OLEDs. Overall, in this work, we demonstrate a promising blue-color-emitting polymer through structural geometry manipulation.

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 score0.024
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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