Thermally activated delayed fluorescence materials as organic photosensitizers
Bibliographic record
Abstract
Photosensitizer molecules play a crucial role in materials and life sciences. Efforts to improve their performance and reduce the associated costs are therefore vital for advancing environmentally friendly light-driven technologies. In this Feature Article, we describe the use of photosensitizers that make use of thermally activated delayed fluorescence (TADF), their benefits compared to conventional fluorescent and phosphorescent sensitizers, and the efforts of our group and others to develop emitters with application-tailored properties. The key feature is the diversity of accessible excited state pathways, which may be tuned by molecular and supramolecular approaches to suit a particular problem. This unique property has allowed TADF emitters to become competitive for applications including TADF-sensitized fluorescence in light emitting diodes and chemical sensing, organic long persistent luminescence, photodynamic therapy, and non-coherent photon upconversion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| 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 teacher head, 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".