Charge-Transfer Studies of Iron Cyano Compounds Bound to Nanocrystalline TiO<sub>2</sub>Surfaces
Bibliographic record
Abstract
Nanocrystalline (anatase) titanium dioxide films have been sensitized to visible light with K(4)[Fe(CN)(6)] and Na(2)[Fe(LL)(CN)(4)], where LL = bpy (2,2'-bipyridine), dmb (4,4'-dimethyl-2,2'-bipyridine), or dpb (4,4'-diphenyl-2,2'-bipyridine). Coordination of Fe(CN)(6)(4-) to the TiO(2) surface results in the appearance of a broad absorption band (fwhm approximately 8200 cm(-1)) centered at 23800 +/- 400 cm(-1) assigned to an Fe(II)-->TiO(2) metal-to-particle charge-transfer (MPCT) band. The absorption spectra of Fe(LL)(CN)(4)(2-) compounds anchored to TiO(2) are well modeled by a sum of metal-to-ligand charge-transfer (MLCT) bands and a MPCT band. Pulsed light excitation (417 or 532 nm, approximately 8 ns fwhm, approximately 2-15 mJ/pulse) results in the immediate appearance of absorption difference spectra assigned to an interfacial charge separated state [TiO(2)(e(-)), Fe(III)], k(inj) > 10(8) s(-1). Charge recombination is well described by a second-order equal concentration kinetic model and requires milliseconds for completion. A model is proposed wherein sensitization of Fe(LL)(CN)(4)(2-)/TiO(2) occurs by MPCT and MLCT pathways, the quantum yield for the latter being dependent on environment. The solvatochromism of the materials allows the reorganization energies associated with charge transfer to be quantified. The photocurrent efficiencies of the sensitized materials are also reported.
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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".