Interfacial Electron Transfer Followed by Photooxidation in <i>N</i>,<i>N</i>-Bis(<i>p</i>-anisole)aminopyridine–Aluminum(III) Porphyrin–Titanium(IV) Oxide Self-Assembled Photoanodes
Bibliographic record
Abstract
Two self-assembled photoanodes have been constructed by exploiting the unique optical and structural properties of aluminum(III) porphyrin (AlPor) in conjunction with TiO 2 nanoparticles as an electron acceptor and bis( p -anisole)aminopyridine (BAA–Py) as an electron donor. AlPor is bound to the TiO 2 surface by either: (i) a benzohydroxamic acid bridge, in which the hydroxamic acid acts as an anchor or (ii) direct covalent binding of Al via an ether bond. The open sixth coordination site of the Al center is then used to coordinate BAA–Py through Lewis acid–base interactions, which results in donor–photosensitizer–semiconductor constructs that can be used as photoanodes. The two photoanodes were characterized by steady-state and transient spectroscopic techniques as well as computational methods. Transient-absorption studies show that in the absence of BAA–Py both the photoanodes exhibit electron injection from AlPor to the conduction band of TiO 2 . However, the injection efficiencies and kinetics are strongly dependent on the linker with faster and more efficient injection occurring when the porphyrin is directly bound. Kinetic results also suggest that the recombination is faster in directly bound AlPor than benzohydroxamic acid bridged AlPor. When BAA–Py is coordinated to AlPor, electron injection from AlPor to TiO 2 is followed by electron transfer from BAA–Py to the oxidized AlPor. The injection efficiencies modeled using density functional theory and semiempirical tight-binding calculations are consistent with experimentally observed trends.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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".