Unraveling the Trade‐Off Between Oxygen Vacancy Concentration and Ordering of Perovskite Oxides for Efficient Lattice Oxygen Evolution
Bibliographic record
Abstract
Abstract Oxygen evolution reaction (OER) over perovskite oxides, upon undergoing a lattice oxygen oxidation mechanism, is strongly oxygen vacancy‐correlated as determined by the oxygen ion diffusivity. Despite substantial efforts having been devoted to tuning the oxygen vacancy concentration in perovskite oxides, the impact of the concomitant altering of oxygen vacancy ordering is often underestimated. In particular, the underlying mechanism of how the ordering and the concentration of oxygen vacancy affect the lattice OER, and how to well balance them still remain inadequately understood. Herein, a series of Sr 1− x Ca x Co 0.5 Fe 0.5 O 3− δ with gradually increased oxygen vacancy concentration and ordering are synthesized. Theoretical calculations indicated that a higher oxygen vacancy concentration promoted the lattice oxygen migration, whereas a higher oxygen vacancy ordering impeded it. Particularly, Sr 0.5 Ca 0.5 Co 0.5 Fe 0.5 O 3− δ with a relatively higher oxygen vacancy concentration and a lower ordering displayed the maximum oxygen diffusion rate and the optimal OER activity, affording a current density of 10 mA cm −2 at a quite low overpotential of 310.2 mV, together with a small Tafel slope of 55.87 mV dec −1 . This study sheds light on the critical influence of oxygen vacancy configuration on the lattice OER, and paves a compromised avenue to screen and design advanced electrocatalysts for various electrochemical devices.
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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 | 0.000 |
| 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) | 0.000 | 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".