Dependence of light outcoupling in organic light-emitting devices on ITO thickness and roughness
Bibliographic record
Abstract
The efficiency of organic light-emitting devices (OLEDs) is shown to significantly depend on both the thickness and roughness of the indium tin oxide (ITO) anode. The effects of changing the ITO thickness from 45 nm to 130 nm are found to be able to vary the current efficiency by 40%. The underlying mechanism is studied and revealed to be related to microcavity effects. The transmittance of the ITO substrate changes significantly with the ITO thickness, resulting in variations in microcavity, and thus light outcoupling efficiency. On the other hand, the effects of increasing the ITO roughness (rms) from 3.3 nm to 8.5 nm are found to increase light scattering at the ITO/organic interface, thus improving extraction of light trapped in the organic/ITO wave-guided mode. In addition to the enhancement in current efficiency, the device fabricated on rough ITO shows similar driving voltage to that made on smooth ITO, indicating that charge balance is not altered by ITO roughness. Contrary to common belief in the community, the lifetime of the OLED is not affected when using rough ITO. The results demonstrate the significant efficiency benefits of using ITO with optimal thicknesses and higher roughness in OLEDs.
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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 | 0.001 |
| 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".