Engineering Active Surface Oxygen Sites of Cubic Perovskite Cobalt Oxides toward Catalytic Oxidation Reactions
Bibliographic record
Abstract
Unraveling the role of surface oxygen sites in transition metal oxides during catalytic reactions has always been the focus of environmental and energy chemistry research. Herein, active surface oxygen sites of cubic perovskite cobalt oxide were engineered to comprehend their crucial role and catalytic mechanism at the molecular level. By removing those inert Sr/La–O termination layers, active oxygen sites were exposed on the Co terminated surface of Sr 0.6 La 0.4 CoO 3−δ that furnished the dominant catalytic process of CO oxidation via the Mars–van Krevelen (MvK) mechanism. The fabrication of five-coordinate cobalt ions and the enhanced covalency of Co–O bonds not only optimize the surface electronic structure of Co 3d–O 2p, but also supply active surface oxygen sites, which effectively oxidizes CO to CO 2 with a significantly improved oxidation performance and stability as evidenced by soft/hard XAS, XPS, and O 2 -TPD. Furthermore, online isotopic 18 O 2 mass spectrometry, in situ DRIFTS, and theoretical simulation demonstrate that the activity of surface oxygen sites enhances the kinetics of the MvK reaction, while unsaturated coordination sites from five-coordinate cobalt ions primarily contribute to the activated oxygen molecules and the stable catalytic cycle. The results reported here provide a deep insight into the comprehension of the relationships among active oxygen sites, surface electronic structure, and the reaction mechanism of transition metal oxides necessary for catalytic oxidation reactions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".