Effects of increasing ligand conjugation in Cu( <scp>i</scp> ) photosensitizers on NiO semiconductor surfaces
Bibliographic record
Abstract
Dye-sensitized photoelectrodes may be used as heterogeneous components for fuel-forming reactions in photoelectrochemical cells. There has been increasing interest in developing Earth-abundant cheaper photosensitizers based on first-row transition metals. We describe here the synthesis, characterization, and study of the ground and excited state properties of three Cu(I) complexes bearing ligands with varying electron-accepting capacities and conjugation that may act as photosensitizers for wide bandgap semiconductors. Femtosecond transient absorption studies indicate that the nature of the final excited state is dictated by the extent of conjugation in the electron-accepting ligand, where shorter conjugation leads to the formation of a singly reduced ligand and longer conjugation leads to the formation of a ligand-centered final excited state. These complexes were surface anchored onto nanostructured NiO on conductive fluorine-doped tin oxide glass to fabricate photocathodes. It was found that even though the ligands with increasing conjugation have an effect on the formation of the final excited state in solution, all complexes exhibit similar photocurrents upon white light illumination, suggesting that charge transfer to NiO happens in advance of the formation of the final excited state.
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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 | 0.001 |
| 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 | 0.001 | 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".