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Record W4360946369 · doi:10.1038/s41467-023-37414-y

D-O-A based organic phosphors for both aggregation-induced electrophosphorescence and host-free sensitization

2023· article· en· W4360946369 on OpenAlexaff
Lulin Xu, Yuhang Mo, Ning Su, Changshen Shi, Ning Sun, Yuewei Zhang, Lian Duan, Zheng‐Hong Lu, Junqiao Ding

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldEngineering
TopicOrganic Light-Emitting Diodes Research
Canadian institutionsUniversity of Toronto
FundersYunnan UniversityNational Natural Science Foundation of China
KeywordsPhosphorPhosphorescenceOptoelectronicsAcceptorMaterials scienceElectroluminescenceQuantum efficiencyOLEDDiodePhotochemistryChemistryNanotechnologyFluorescenceOptics

Abstract

fetched live from OpenAlex

Pure organic phosphors capable of room-temperature phosphorescence show a great potential in organic light-emitting diodes, while it is limited by the big challenge to realize efficient electroluminescence under electric excitation. Herein, we develop a class of organic phosphors based on acridine as the electron donor, triazine as the electron acceptor and oxygen as the bridge between them. Benefitting from the characteristic donor-oxygen-acceptor geometry, these compounds are found to behave an exciting aggregation-induced organic room-temperature electrophosphorescence, and achieve a record-high external quantum efficiency of 15.8% for non-doped devices. Furthermore, they can sensitize multi-resonant emitters in the absence of any additional wide bandgap host, leading to an effective narrowband emission with a peak external quantum efficiency of 26.4% and a small full-width at half maximum of 26 nm. The results clearly indicate that donor-oxygen-acceptor geometry is a promising strategy to design organic phosphors suitable for organic light-emitting diodes.

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)0.001
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 score0.393
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.270
Teacher spread0.256 · 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

Citations44
Published2023
Admission routes1
Has abstractyes

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