Azophenine as Central Core for Efficient Light Harvesting Devices
Bibliographic record
Abstract
Abstract The notoriously non‐luminescent uncycled azophenine (Q) was harnessed with Bodipy and zinc(II)porphyrin antennas to probe its fluorescence properties, its ability to act as a singlet excited state energy acceptor and to mediate the transfer. Two near‐IR emissions are depicted from time‐resolved fluorescence spectroscopy, which are most likely due to the presence of tautomers of very similar calculated total energies (350 cm−1; DFT; B3LYP). The rates for energy transfer, kET(S1), for 1Bodipy*→Q are in the order of 1010–1011 s−1 and are surprisingly fast when considering the low absorptivity properties of the lowest energy charge transfer excited state of azophenine. The rational is provided by the calculated frontier molecular orbitals (MOs) which show atomic contributions in the C6H4C≡CC6H4 arms, thus favoring the double electron exchange mechanism. In the mixed‐antenna Bodipy–porphyrin star molecule, the rate for 1Bodipy*→porphyrin has also been evaluated (≈16×1010 s−1) and is among the fastest rates reported for Bodipy–zinc(II)porphyrin pairs. This astonishing result is again explained from the atomic contributions of the C6H4C≡CC6H4 and C≡CC6H4 arms thus favouring the Dexter process. Here, for the first time, this process is found to be sensitively temperature‐dependent. The azophenine turns out to be excellent for electronic communication.
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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 | 0.001 |
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".