Recent Progress in Organic TADF Emitters Containing Heavy Atoms
Bibliographic record
Abstract
Abstract All organic compounds exhibiting thermally activated delayed fluorescence (TADF) are useful materials for applications in organic light‐emitting diodes (OLED), bioimaging, and photocatalysis. In addition to their low cost, organic TADF materials can have high brightness, excellent colour purity, and good stability. Despite this, many emitters still suffer from slow TADF which can reduce the operational lifetime of TADF‐based OLEDs due to biexcitonic processes that lead to decomposition of the emitters. In recent years, the incorporation of heavy elements into organic TADF emitters has emerged as a useful strategy for accelerating both forward and reverse intersystem crossing through the heavy atom effect. This approach can increase device efficiencies and lifetimes, but relies on a detailed, and often subtle, understanding of molecular design. This review summarizes recent advances in the use of the heavy atom effect in organic TADF systems, providing a detailed overview of the photophysics and, where applicable, OLED performance of the studied materials. Design principles, challenges, and opportunities for heavy atom incorporation in TADF systems are also discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".