<b>Imidazophenothiazine-Based Thermally Activated Delayed Fluorescence Materials with Ultra-Long-Lived Excited States for Energy Transfer Photocatalysis</b>
Bibliographic record
Abstract
Triplet-triplet energy transfer (EnT) is a powerful activation pathway in photocatalysis that unlocks new organic transformations and improves the sustainability of organic synthesis. Many current examples, however, still rely on platinum-group metal complexes as photosensitizers, with associated high costs and environmental impacts. Photosensitizers that exhibit thermally activated delayed fluorescence (TADF) are attractive fully organic alternatives in EnT photocatalysis. However, TADF photocatalysts incorporating heavy atoms remain rare, despite their utility in inducing efficient spin-orbit-coupling, intersystem-crossing, and consequently a high triplet population. Here, we describe the synthesis of imidazo-phenothiazine (IPTZ), a sulfur-containing heterocycle with a locked planar structure and a shallow LUMO level. This acceptor is used to prepare seven TADF-active photocatalysts with triplet energies up to 63.9 kcal mol –1 . We show that sulfur incorporation improves spin-orbit coupling and increases triplet lifetimes up to 3.64 ms, while also allowing for tuning of photophysical properties via oxidation at the sulfur atom. These IPTZ materials are applied as photocatalysts in five seminal EnT reactions: [2 + 2] cycloaddition, the disulfide-ene reaction, and Ni-mediated C–O and C–N cross-coupling to afford etherification, esterification, and amination products, outcompeting the industry-standard TADF photocatalyst 2CzPN in four of the five studied scenarios. Detailed photophysical and theoretical studies are used to understand structure–activity relationships and to demonstrate the key role of the heavy atom effect in the design of TADF materials with superior photocatalytic performance.
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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) | 0.002 | 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".