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Record W3000643650 · doi:10.1002/aelm.201901147

Charge‐Transport Processes in Host–Dopant Organic Semiconductors

2020· article· en· W3000643650 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Electronic Materials · 2020
Typearticle
Languageen
FieldEngineering
TopicOrganic Light-Emitting Diodes Research
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsDopantMaterials scienceOLEDBand offsetOptoelectronicsOrganic semiconductorChemical physicsDopingNanotechnologyChemistryBand gap

Abstract

fetched live from OpenAlex

Abstract Host–dopant systems are the foundation for designing the light‐emission zones of organic light‐emitting diodes (OLEDs). An efficient OLED design has to consider the detailed charge transport processes in a host–dopant system in order to regulate charges for optimal distribution of excitons. It is reported that two charge transport pathways, Frenkel–Poole type transport via either host sites or dopant sites and charge hopping between host and dopant sites, are at play. The activation energy barrier in the hopping transport is identified as the energy level offset at the host–dopant interface, and is found consistent with the energy offset in the highest occupied molecular orbitals directly measured by ultraviolet photoemission spectroscopy. Dopant concentration and the host–dopant energy offset are identified as the key parameters dictating charge conduction path in the system. Practical equations are derived to calculate carrier mobility as a function of dopant concentration and dopant–host molecular energy offset.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.223
Teacher spread0.214 · 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