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Record W4390113252 · doi:10.3390/molecules29010073

Polymer Dispersed Liquid Crystal Imprinted by Microlens Array for Enhanced Outcoupling Efficiency of Organic Light Emitting Diode

2023· article· en· W4390113252 on OpenAlexaff
Seongmin Lim, Hyeon-Sik Ahn, Eun‐Jeong Jang, So‐Young Boo, Akpeko Gasonoo, Jin‐Seog Gwag, Jae‐Hyun Lee, Yoonseuk Choi

Bibliographic record

VenueMolecules · 2023
Typearticle
Languageen
FieldEngineering
TopicOrganic Light-Emitting Diodes Research
Canadian institutionsUniversity of Calgary
FundersHORIZON EUROPE Research InfrastructuresMinistry of Education, IndiaNational Research Foundation of KoreaMinistry of EducationNational Research Foundation
KeywordsMicrolensOLEDMaterials scienceOptoelectronicsLiquid crystalDiodePolymerQuantum efficiencyCoatingOpticsNanotechnologyLayer (electronics)Lens (geology)Composite material

Abstract

fetched live from OpenAlex

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 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)
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 score0.103
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)0.0000.000

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 head0.006
GPT teacher head0.233
Teacher spread0.227 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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