Highly Efficient Deep‐Blue Electrophosphorescent Pt(II) Compounds with Non‐Distorted Flat Geometry: Tetradentate versus Macrocyclic Chelate Ligands
Bibliographic record
Abstract
A new class of deep blue electrophosphorescent Pt(II) emitters have been designed and synthesized. This new class of deep blue Pt(II) emitters employ tetradentate and macrocyclic chelate chromophores to constrain the Pt(II) molecules in a non‐distorted flat geometry in both the ground state and the excited state. The new deep blue emitters do not produce excimer emission, with emission quantum efficiency as high as 95% in 10% doped PMMA (poly(methyl methacrylate) films, and excellent UV stability, compared to the corresponding bidentate Pt(II) emitters. The macrocyclic tetradentate chelate Pt(II) compounds are the first examples of fully sterically constrained deep blue Pt(II) emitters that do not display structural distortion and have a higher thermal stability and a higher emission quantum efficiency than the corresponding non‐macrocyclic tetradentate Pt(II) analogues. A computational study supports that the macrocylic Pt(II) compounds are structurally more stable than the tetradentate Pt(II) molecules. Bright and efficient deep blue electrophosphorescent devices using a macrocyclic Pt(II) emitter have been successfully fabricated with a maximum brightness of 10 680 cd m−2, maximum external quantum efficiency of 15.4% (at 490 cd m−2), and Commission Internationale de L'Eclairage (1931) coordinates (x + y) of less than or near 0.30, respectively.
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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 | 0.001 | 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".