Tuning the Excited State Character of Amine/Carbonyl Thermally Activated Delayed Fluorescence Emitters with Ring Fusion
Bibliographic record
Abstract
Multiple resonance thermally activated delayed fluorescence (MR-TADF) emitters exhibit short-range charge transfer (SRCT) and have narrow emission, whereas donor-acceptor TADF emitters show long-range charge transfer (LRCT) and rapid reverse intersystem crossing (RISC). While some work has been done to create intermediate-type materials with narrow emission and rapid RISC simultaneously, no studies of structurally comparable donor-acceptor versus MR-TADF systems have been described. Here we report two TADF emitters, Acr-DiKTa and Iso-DiDiKTa, to examine the effect of ring fusion on LRCT and SRCT character. Acr-DiKTa appends an acridone moiety to quinolino[3,2,1-de]acridine-5,9-dione to create a donor-acceptor-type structure, while a carbonyl bridge fuses these moieties in Iso-DiDiKTa to give an MR-TADF structure. Acr-DiKTa emits blue-green in toluene with a full width at half maximum (FWHM) of 38 nm whereas Iso-DiDiKTa emits green-yellow with a FWHM of 34 nm. Calculated orbital distributions show SRCT in the first excited state for both compounds. Both compounds are TADF active in doped films, and derived rate constants show that RISC is four times more rapid in Acr-DiKTa. This study shows that while ring fusion enhances color purity, donor-acceptor structures can achieve comparable FWHMs and rapid RISC through dominant SRCT supported by LRCT for best performance in TADF materials.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".