Selective doping of multilayer organic light emitting devices
Bibliographic record
Abstract
Doping of organic light emitting diodes (OLEDs) has well-established benefits such as tuning emission wavelengths, as well as enhancing device lifetime and quantum efficiency. The use of low percentage doping within the emissive layer is an established tool for the study of energy transfer processes in OLEDs, allowing one to trace electron and hole movement and exciton formation. Delta doping, in which a thin layer of the dopant material alone is incorporated in the device, has the added advantage of a thinner sensing layer and an electroluminescence spectrum distinct from that of the host material. In an ongoing effort to further our understanding of electroluminescent emission processes, we have fabricated multilayer OLEDs which incorporate a narrow (<1 nm) delta-doped DCM region within the emissive layer. The devices studied were deposited on indium tin oxide (ITO) on glass substrates using thermal evaporation, with a structure of ITO, TPD (40 nm)/selectively doped Alq3 (40 nm)/Al (100 nm). The relationship between the doping profile and the emission characteristics will be discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".