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Record W2917125846 · doi:10.1038/s41598-019-39451-4

Improved hole injection for blue phosphorescent organic light-emitting diodes using solution deposited tin oxide nano-particles decorated ITO anodes

2019· article· en· W2917125846 on OpenAlexafffund
Seung Il Lee, Geum Jae Yun, Jin Wook Kim, Gregory Hanta, Kunyu Liang, Lazar Kojvic, Lok Shu Hui, Ayse Turak, Woo Young Kim

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldEngineering
TopicOrganic Light-Emitting Diodes Research
Canadian institutionsMcMaster University
FundersNational Research Foundation of KoreaKorea Institute for Advancement of TechnologyOntario Ministry of Research, Innovation and ScienceMinistry of SMEs and StartupsCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaNational Research Foundation
KeywordsPhosphorescenceAnodeTinTin oxideNano-Materials scienceDiodeOptoelectronicsLight-emitting diodeOxideIndium tin oxideOLEDNanotechnologyChemical engineeringElectrodeChemistryThin filmMetallurgyOpticsComposite materialDopingLayer (electronics)PhysicsFluorescencePhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Blue phosphorescent organic light-emitting diodes (PHOLEDs) were fabricated with tin oxide (SnO x ) nano-particles (NPs) deposited at the ITO anode to improve their electrical and optical performances. SnO x NPs helped ITO to increase the work function enhancing hole injection capability. Charge balance of the device was achieved using p- and n-type mixed host materials in emissive layer and the devices’ luminance and maximum external quantum efficiency (EQE) increased about nearly 30%. Tuning the work function using solution processed NPs allows rapid optimization of device efficiency.

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)0.002
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 score0.243
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.012
GPT teacher head0.240
Teacher spread0.227 · 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

Citations29
Published2019
Admission routes2
Has abstractyes

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