Redox Processes of Manganese Oxide in Catalyzing Oxygen Evolution and Reduction: An <i>in Situ</i> Soft X-ray Absorption Spectroscopy Study
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Manganese oxides with rich redox chemistry have been widely used in (electro)catalysis in applications of energy and environmental consequence. While they are ubiquitous in catalyzing the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR), redox processes occurring on the surface of manganese oxides are poorly understood. We report valence changes at OER- and ORR-relevant voltages of a layered manganese oxide film prepared by electrodeposition. X-ray absorption spectra were collected in situ in O 2 -saturated 0.1 M KOH using inverse partial fluorescence yield (IPFY) at the Mn L 3,2 -edges and partial fluorescence yield (PFY) at the O K-edge. Overall, we found reversible yet hysteretic Mn redox and qualitatively reproducible spectral changes by Mn L 3,2 IPFY XAS. Oxidation to a mixed Mn 3+/4+ valence preceded the oxygen evolution at 1.65 V vs RHE, while manganese reduced below Mn 3+ and contained tetrahedral Mn 2+ during oxygen reduction at 0.5 V vs RHE. Analysis of the pre-edge in O K-edge XAS provided the Mn–O hybridization, which was highest for Mn 3+ (e g 1 ). Our study demonstrates that combined in situ experiments at the metal L- and oxygen K-edges are indispensable to identify both the active valence during catalysis and the hybridization with oxygen adsorbates, critical to the rational design of active catalysts for oxygen electrocatalysis.
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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".