Kinetics versus Charge Separation: Improving the Activity of Stoichiometric and Non-Stoichiometric Hematite Photoanodes Using a Molecular Iridium Water Oxidation Catalyst
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Oxygen-deficient iron oxide thin films, which have recently been shown to be highly active for photoelectrochemical water oxidation, were surface-functionalized with a monolayer of a molecular iridium water oxidation cocatalyst. The iridium catalyst was found to dramatically improve the kinetics of the water oxidation reaction at both stoichiometric and nonstoichiometric α-Fe 2 O 3-x surfaces. This was found to be the case in both the dark and in the light as evidenced by cyclic voltammetry, Tafel analysis, and electrochemical impedance spectroscopy (EIS). Oxygen evolution measurements under working conditions confirmed high Faradaic efficiencies of 69–100% and good stability over 22 h of operation for the functionalized electrodes. The resulting ∼200–300 mV shift in onset potential for the iridium-functionalized sample was attributed to improved interfacial charge transfer and oxygen evolution kinetics. Mott–Schottky plots revealed that there was no shift in flat-band potential or change in donor density following functionalization with the catalyst. The effect of the catalyst on thermodynamics and Fermi level pinning was also found to be negligible, as evidenced by open-circuit potential measurements. Finally, transient photocurrent measurements revealed that the tethered molecular catalyst did improve charge separation and increase charge density at the surface of the photoanodes, but only at high applied biases and only for the nonstoichiometric oxygen-deficient iron oxide films. These results demonstrate how molecular catalysts can be integrated with semiconductors to yield cooperative effects for photoelectrochemical water oxidation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".