Spectral Characteristics and Photosensitization of TiO<sub>2</sub> Nanoparticles in Reverse Micelles by Perylenes
Bibliographic record
Abstract
We report on the photosensitization of titanium dioxide nanoparticles (TiO2 NPs) synthesized inside AOT (bis(2-ethylhexyl) sulfosuccinate sodium salt) reverse micelles following photoexcitation of perylene derivatives with dicarboxylate anchoring groups. The dyes, 1,7-dibromoperylene-3,4,9,10-tetracarboxy dianhydride (1), 1,7-dipyrrolidinylperylene-3,4,9,10-tetracarboxy dianhydride (2), and 1,7-bis(4-tert-butylphenyloxy)perylene-3,4,9,10-tetracarboxy dianhydride (3), have considerably different driving forces for photoinduced electron injection into the TiO2 conduction band, as estimated by electrochemical measurements and quantum mechanical calculations. Fluorescence anisotropy measurements indicate that dyes 1 and 2 are preferentially solubilized in the micellar structure, creating a relatively large local concentration that favors the attachment of the dye to the TiO2 surface. The binding process was followed by monitoring the hypsochromic shift of the dye absorption spectra over time for 1 and 2. Photoinduced electron transfer from the singlet excited state of 1 and 2 to the TiO2 conduction band (CB) is indicated by emission quenching of the TiO2-bound form of the dyes and confirmed by transient absorption measurements of the radical cation of the dyes and free carriers (injected electrons) in the TiO2 semiconductor. Steady state and transient spectroscopy indicate that dye 3 does not bind to the TiO2 NPs and does not photosensitize the semiconductor. This observation was rationalized as a consequence of the bulky t-butylphenyloxy groups which create a strong steric impediment for deep access of the dye within the micelle structure to reach the semiconductor oxide surface.
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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 | 0.000 |
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".