Polymer Dispersed Liquid Crystal Imprinted by Microlens Array for Enhanced Outcoupling Efficiency of Organic Light Emitting Diode
Bibliographic record
Abstract
In this paper, we demonstrate the use of polymer dispersed liquid crystal (PDLC) imprinted with a microlens array (MLA) via solution process to improve the outcoupling efficiency of organic light emitting diodes (OLEDs). The PDLC, well known for its scattering effect, is an excellent technology for improving the outcoupling efficiency of OLEDs. Additionally, we introduce a simple spin-coating process to fabricate PDLC which is adaptable for future solution-processed OLEDs. The MLA-imprinted PDLC applied OLED shows an enhancement factor of 1.22 in outcoupling efficiency which is a 37.5% increase compared to the existing PDLC techniques without changing the electrical properties of the OLED. Through this approach, we can expect the roll-to-roll based extremely flexible OLED, and with further research on pattering PDLC by various templates, higher outcoupling efficiency is achievable through a simple UV irradiation process.
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 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".