Organic Light Emitting Device Materials for Displays
Bibliographic record
Abstract
This chapter introduces organic light emitting device (OLEDs) and organic electroluminescent materials. It highlights some of the most important classes and types of organic electroluminescent materials developed to date and some of the important materials in each case. The chapter also introduces quantum dot (QD)-LEDs, which, because of their unsurpassed color purity signal and their use of organic semiconductors, are seen as an evolutionary extension of OLEDs. OLEDs possess a unique combination of features that position them favorably relative to LCDs and other flat panel displays (FPD) technologies. In an OLED light is produced by a thin layer of an organic electroluminescent material sandwiched between two electrodes. While fabrication of neat emitting OLEDs significantly simplifies the process, doping the emitters into a host matrix has been proven to produce superior devices. Fine metal masks (FMMs) however have several inherent limitations that pose some challenges in manufacturing OLED displays.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.114 | 0.073 |
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".