Manganese Compounds as Water-Oxidizing Catalysts: From the Natural Water-Oxidizing Complex to Nanosized Manganese Oxide Structures
Bibliographic record
Abstract
All cyanobacteria, algae, and plants use a similar water-oxidizing catalyst for water oxidation. This catalyst is housed in Photosystem II, a membrane-protein complex that functions as a light-driven water oxidase in oxygenic photosynthesis. Water oxidation is also an important reaction in artificial photosynthesis because it has the potential to provide cheap electrons from water for hydrogen production or for the reduction of carbon dioxide on an industrial scale. The water-oxidizing complex of Photosystem II is a Mn-Ca cluster that oxidizes water with a low overpotential and high turnover frequency number of up to 25-90 molecules of O2 released per second. In this Review, we discuss the atomic structure of the Mn-Ca cluster of the Photosystem II water-oxidizing complex from the viewpoint that the underlying mechanism can be informative when designing artificial water-oxidizing catalysts. This is followed by consideration of functional Mn-based model complexes for water oxidation and the issue of Mn complexes decomposing to Mn oxide. We then provide a detailed assessment of the chemistry of Mn oxides by considering how their bulk and nanoscale properties contribute to their effectiveness as water-oxidizing catalysts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".