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Record W2938848929 · doi:10.1063/1.5092979

Highly efficient top-emission organic light-emitting diode on an oxidized aluminum anode

2019· article· en· W2938848929 on OpenAlexafffund
Jaejin Lee, Peicheng Li, Hao‐Ting Kung, Zheng‐Hong Lu

Bibliographic record

VenueJournal of Applied Physics · 2019
Typearticle
Languageen
FieldEngineering
TopicOrganic Light-Emitting Diodes Research
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaCanada Research Chairs
KeywordsAnodeMaterials scienceOptoelectronicsOLEDSiliconUltraviolet photoelectron spectroscopyLight-emitting diodeActive matrixDiodeLuminanceX-ray photoelectron spectroscopyUltravioletElectrodeLayer (electronics)OpticsNanotechnologyThin-film transistorChemistryChemical engineering

Abstract

fetched live from OpenAlex

In today's manufacturing of organic light-emitting diode on silicon for microdisplay technologies, a top-emitting OLED (TEOLED) is required to be fabricated on top of an active-matrix circuitry located on the silicon backplane. This requires a highly reflective anode to enhance the luminance output. However, during the production process of a TEOLED, the hole injection efficiency and electrical conductivity may be suppressed by environmental exposure, in particular, moisture and oxygen. Given this, aluminum is an unfavorable reflective anode due to the primary concern of its native insulating oxide layer. The native oxide tends to grow during the patterning of the metal anode. In this paper, we have discovered that, by utilizing an Al2O3/MoO3 heterojunction anode structure, a highly efficient device can be made to achieve a current efficiency of 94 cd/A at a luminance of 1000 cd/m2. X-ray/ultraviolet photoelectron spectroscopy measurements show the formation of molybdenum gap states and favorable energy level alignment for hole injection.

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 score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.007
GPT teacher head0.229
Teacher spread0.221 · 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

Citations12
Published2019
Admission routes2
Has abstractyes

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