Enhanced Stability and Thickness‐Independent Oxygen Evolution Electrocatalysis of Heterostructured Anodes with Buried Epitaxial Bilayers
Bibliographic record
Abstract
Abstract Achieving high oxygen evolution reaction (OER) activity while maintaining performance stability is a key challenge for designing perovskite structure oxide OER catalysts, which are often unstable in alkaline environments transforming into an amorphous phase. While the chemical and structural transformation occurring during electrolysis at the electrolyte–catalyst interface is now regarded as a crucial factor influencing OER activity, here, using La 0.7 Sr 0.3 CoO 3− δ (LSCO) as an active OER catalyst, the critical influence of buried layers on the oxidation current stability in nanoscopically thin, chemically and structurally evolving, catalyst layers is revealed. The use of epitaxial thin films is demonstrated to engineer both depletion layer widths and chemical stability of the catalyst support structure resulting in heterostructured anodes that maintain facile transport kinetics across the electrolyte–anode interface for atomically thin (2–3 unit cells) LSCO catalyst layers and greatly enhanced oxidation current stability as the perovskite structure OER catalysts chemically and structurally transform. This work opens up an approach to design robust and active heterostructured anodes with dynamically evolving ultrathin OER electrocatalyst layers for future green fuel technologies such as conformal coatings of high‐density 3D anode topologies for water splitting.
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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) | 0.001 | 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 | 0.000 |
| 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".