Changing the Nature of the Chelating Ligand of Tetracoordinate Boron-Containing PAH Multi-resonant Thermally Activated Delayed Fluorescence Emitters Tunes the Emission from Green to Deep Red
Bibliographic record
Abstract
Multi-resonant thermally activated delayed fluorescence (MR-TADF) materials have attracted considerable attention recently. The molecular design frequently incorporates cycloboration. However, to the best of our knowledge MR-TADF compounds containing nitrogen chelation to boron is still unknown. Reported herein is a new class of tetracoordinate boron-containing MR-TADF emitters bearing a C^N^C- and N^N^N-chelating ligands. We demonstrate that the replacement of B−C covalent bond in C^N^C-chelating ligand by B−N covalent bond affords a regioisomer, which dramatically influences the optoelectronic properties of the molecule. The resulting N^N^N-chelating compounds show bathochromically shifted absorption and emission spectra relative to C^N^C-chelating compounds. The incorporation of tert-butylcarbazole group to the 4-position of the pyridine significantly enhances both the thermal stability and the reverse intersystem crossing rate, yet has a negligible effect on the emission properties. Consequently, high-performance hyperfluorescence organic light-emitting diodes (HF-OLEDs) that utilize these molecules as green and yellow-green emitters show maximum external quantum efficiency (ηext) of 11.5% and 25.1%, and a suppressed efficiency roll-off with ηext of 10.2% and 18.7% at a luminance of 1000 cd m−2, 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 | 0.000 | 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".