Design of Highly Active Perovskite Oxides for Oxygen Evolution Reaction by Combining Experimental and ab Initio Studies
Bibliographic record
Abstract
Perovskite oxides (ABO 3 ) have recently attracted attention since tailoring their chemical compositions has resulted in remarkable activity toward oxygen evolution reaction (OER) which governs rechargeability of recently spotlighted metal–air batteries and regenerative fuel cells. For further development of highly OER active perovskite oxides, however, the exact mechanism the OER must be well understood. Herein, we introduce investigation of the OER mechanism of perovskite oxides by ab initio analysis based on well-defined model systems of LaMnO 3 (LMO), LaCoO 3 (LCO), and La 0.5 Sr 0.5 CoO 3 (LSCO). In addition, we have systematically conducted electrochemical experiments from which we have observed an increasing trend in the OER activity in the order of LSCO > LCO > LMO based on the cyclic voltammetry (CV) results obtained in the alkaline medium. To validate the experimental results, free-energy diagrams have been constructed for oxygen intermediates on the surface of the defined models to find the limiting step by changing the B site atom (e.g., Mn and Co) and the partial displacement of Sr atoms in La site. The oxygen adsorption energy of perovskite oxides is found to increase with decreasing number of outer electrons as well as upshifting of the position of the d z 2 orbital toward the Fermi level of B site element. This work demonstrates that highly active OER perovskite oxides can be obtained by modifying the chemical composition to finely tune the oxygen adsorption energy on the catalyst’s surface, confirmed by synergetic approaches of using both experimental and ab initio computational studies.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".