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Record W4390574965 · doi:10.1021/acsnano.3c07999

Differences in Electron and Hole Injection and Auger Recombination between Red, Green, and Blue CdSe-Based Quantum Dot Light Emitting Devices

2024· article· en· W4390574965 on OpenAlexaff
Mohsen Azadinia, Peter Chun, Quan Lyu, Giovanni Cotella, Hany Aziz

Bibliographic record

VenueACS Nano · 2024
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsHuawei Technologies (Canada)University of Waterloo
Fundersnot available
KeywordsQuantum dotAuger effectElectroluminescenceLight-emitting diodeOptoelectronicsMaterials scienceQuenching (fluorescence)PhotoluminescenceExcitonElectronMicrosecondAugerAtomic physicsPhysicsFluorescenceOpticsNanotechnologyLayer (electronics)Condensed matter physics

Abstract

fetched live from OpenAlex

Despite the significant progress that has been made in recent years in improving the performance of quantum dot light-emitting devices (QLEDs), the effect of charge imbalance and excess carriers on excitons in red (R) vs green (G) vs blue (B) QLEDs has not been compared or systematically studied. In this work we study the effect of changing the electron (e)/hole (h) supply ratio in the QDs emissive layer (EML) in CdSe-based R-, G-, and B-QLEDs with inverted structure in order to identify the type of excess carriers and investigate their effect on the electroluminescence performance of QLEDs of each color. Results show that in R-QLEDs, the e/h ratio in the EML is >1, whereas in G- and B-QLEDs, the e/h ratio is <1 with charge balance conditions being significantly worse in the case of B-QLEDs. Transient photoluminescence (PL) and steady state PL measurements show that, compared to electrons, holes lead to a stronger Auger quenching effect. Transient electroluminescence (TrEL) results indicate that Auger quenching leads to a gradual decline in the EL performance of the QLEDs after a few microseconds, with a stronger effect observed for positive charging versus negative charging. The results provide insights into the differences in the efficiency behavior of R-, G-, and B-QLEDs and uncover the role of excess holes and poor charge balance in the lower efficiency and EL stability of B-QLEDs.

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 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 score0.067
Threshold uncertainty score0.394

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 head0.021
GPT teacher head0.242
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.

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

Citations31
Published2024
Admission routes1
Has abstractyes

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