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Record W2751896788 · doi:10.1117/12.2283917

A model for exciton formation in organic electroluminescent devices

2017· article· en· W2751896788 on OpenAlexaff
H. L. Wok

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOrganic Light-Emitting Diodes Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsExcitonElectroluminescenceCharge (physics)Charge carrierMaterials scienceOptoelectronicsCharge-carrier densityChemical physicsWork (physics)Condensed matter physicsChemistryPhysicsNanotechnologyThermodynamicsDopingQuantum mechanics

Abstract

fetched live from OpenAlex

This work reports a physical model that relates charge transport to the exciton formation rate in organic electroluminescent device. The model assumes ideal charge density profiles and the existence of an "optimal" charge separation for excitons to be formed. This allows the exciton formation rate to be dependent on the charge density profiles as well as parameters linked to the exciton formation process. Field dependent effect enters into this model through a "localization" parameter, which is related to the carrier mobility. When the model is applied to the ITO/CuPc/NPB/A1q3/Mg system, we have found it possible to address a number of observations not fully explained previously.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.004
Open science0.0030.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.030
GPT teacher head0.280
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2017
Admission routes1
Has abstractyes

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