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Record W2981602570 · doi:10.1002/adfm.201906742

Highly Efficient Quantum Dot Light‐Emitting Diodes by Inserting Multiple Poly(methyl methacrylate) as Electron‐Blocking Layers

2019· article· en· W2981602570 on OpenAlexafffund
Mohammad Rahmati, Sergey Dayneko, Majid Pahlevani, Yujun Shi

Bibliographic record

VenueAdvanced Functional Materials · 2019
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceQuantum dotElectroluminescenceOptoelectronicsDiodeLight-emitting diodeFabricationElectronMethyl methacrylateOLEDNanotechnologyPolymerPolymerizationLayer (electronics)Composite materialPhysics

Abstract

fetched live from OpenAlex

Abstract This work presents a new device architecture integrating multiple poly(methyl methacrylate) (PMMA) electron‐blocking layers (EBL) in quantum dot light‐emitting diodes (QD‐LEDs). The device utilizes red‐emitting CdSe/ZnS QD with a novel structure where multiple PMMA EBLs are sandwiched between a pair of QD layers. A systematic optimization of QD‐LED structures has shown that a device including two PMMA and three QD layers performs the best, achieving a current efficiency of 17.8 cd A −1 and a luminance of 194 038 cd m −2 . Numerical simulation of a simplified model of the proposed QD‐LED structure verifies that the structure consisting of two PMMA and three QD layers provides significant improvement in electroluminescent intensity. The simulation provides further insight into the origin of the effect of the PMMA EBL by showing that the addition of PMMA EBL reduces the electron leakage from the active QD region and enhances electron confinement, leading to an increased electron concentration in the QD active layers and a higher radiative recombination rate. The experimental and theoretical studies presented in this work demonstrate that multiple layers of PMMA can act as efficient EBLs in the fabrication of QD‐LEDs of improved performance.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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; both teacher heads agree on what is shown here.

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

Citations36
Published2019
Admission routes2
Has abstractyes

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