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Record W2567295759 · doi:10.1021/acsami.6b15062

Degradation Mechanisms in Organic Light-Emitting Diodes with Polyethylenimine as a Solution-Processed Electron Injection Layer

2016· article· en· W2567295759 on OpenAlexafffund
Sebastian Stolz, Yingjie Zhang, Uli Lemmer, Gerardo Hernandez‐Sosa, Hany Aziz

Bibliographic record

VenueACS Applied Materials & Interfaces · 2016
Typearticle
Languageen
FieldEngineering
TopicOrganic Light-Emitting Diodes Research
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaBundesministerium für Bildung und Forschung
KeywordsPolyethylenimineMaterials scienceDegradation (telecommunications)Layer (electronics)DiodeOptoelectronicsOLEDElectronNanotechnologyChemical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

In this work, we investigate the performance and operational stability of solution-processed organic light-emitting diodes (OLEDs), which comprise polyethylenimine (PEI) as an electron injection layer (EIL). We show that the primary degradation mechanism in these OLEDs depends on the cathode metal that is used in contact with the EIL. In the case of Al, the deterioration in OLED performance during electrical driving is mainly caused by excitons which reach and subsequently degrade the emitter/PEI interface. In contrast, in the case of Ag, device performance degradation occurs due to an additional mechanism: hole accumulation at the emitter/PEI interface and a consequent drop in the emitter quantum yield. As a result, the operational lifetime of OLEDs that use PEI as EIL can vary significantly with the cathode material, and at a current density of 20 mA cm –2, LT50 lifetimes of ∼200 h and <10 h are obtained for Al and Ag, respectively. Finally, we show that the first degradation mechanism can be significantly slowed by using a mixture of PEI and ZnO nanoparticles as EIL. As a result, the operational lifetime of OLEDs with an Al cathode is increased to more than 1000 h, without adversely affecting device performance. This lifetime is significantly longer than that of a LiF/Al reference OLED.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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.

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

Citations42
Published2016
Admission routes2
Has abstractyes

Explore more

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