Tuning the Oxygen Reduction Reactivity of Layered Perovskites Using the Jahn–Teller Effect
Bibliographic record
Abstract
Compositional tuning of layered perovskite oxides provides a means of systematically studying how local distortions affect fundamental aspects of electrochemical reaction pathways. Structural analysis of a family of samples La 1.2 Sr 0.8 Ni 1– y Co y O 4 shows that Ni-rich compositions have an expanded crystalline c axis, which is anisotropically compressed by systematic Co incorporation. Raman spectra reveal the strong growth of a symmetry forbidden mode, which suggests that Co acts through localized distortions. Crystallographic and spectroscopic parameters describing this structural distortion correlate to the measured Tafel slopes for the oxygen reduction reaction for all Ni-containing samples, which is attributed to the distortion of potential energy surfaces by the Jahn–Teller expansion of d 7 Ni(III) cations. Incorporation of Co not only minimizes the distortion but alters the apparent selectivity of the oxygen reduction reaction away from H 2 O 2 and toward H 2 O. Rotating ring-disk electrochemical measurements, however, indicate that the apparent change in selectivity is due to activation of a first-order chemical disproportionation of H 2 O 2 that is activated by Co in the lattice. These outcomes will support efforts to design electrocatalysts and reactors for the electrochemical synthesis of H 2 O 2 .
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".