Thermal Cross-linked Electron Transport Polymers for Suppressing Efficiency Roll-off in Green Solution-Processed Inverted OLEDs
Bibliographic record
Abstract
Solution-processed phosphorescent inverted organic light-emitting diodes (s-IOLEDs) have garnered significant attention due to their excellent stability and high performance. However, frequently used inorganic electron transport layers usually cause exciton dissociation at the emitting layer interface, leading to low device efficiency and severe efficiency roll-off. In this work, we designed a cross-linkable triazine-grafted electron transport copolymer (PPDPT- co -PBCB) with a high triplet energy (3.11 eV) to suppress this exciton dissociation. Balance between electron transport ability and cross-linkability was controlled by varying the ratios between PPDPT and PBCB (9:1 and 8:2), resulting in significantly improved device efficiency. Our s-IOLED incorporating PPDPT- co -PBCB (8:2) achieved a current efficiency of 59.85 cd A –1 and an external quantum efficiency (EQE) of 16.17% with a minimal efficiency roll-off (1.05%) at a luminance of 5000 cd/m 2 . Furthermore, estimations of the recombination zone width and interfacial mixing width revealed that the device with PPDPT- co -PBCB (8:2) featured a relatively broad recombination zone, a weak triplet–triplet annihilation, and a narrow interfacial mixing width, contributing to its enhanced efficiency and reduced roll-off.
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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".