A Porous Pyrochlore Y<sub>2</sub>[Ru<sub>1.6</sub>Y<sub>0.4</sub>]O<sub>7–<i>δ</i></sub> Electrocatalyst for Enhanced Performance towards the Oxygen Evolution Reaction in Acidic Media
Bibliographic record
Abstract
Abstract A robust porous structure is often needed for practical applications in electrochemical devices, such as fuel cells, batteries, and electrolyzers. While templating approach is useful for the preparation of porous materials in general, it is not effective for the synthesis of oxide‐based electrocatalysts owing to the chemical instability of disordered porous materials thus created. Now the synthesis of phase‐pure porous yttrium ruthenate pyrochlore oxide using an unconventional porogen of perchloric acid is presented. The lattice oxygen defects are formed by the mixed‐valence state of Ru4+/5+ through the partial substitution of Ru4+ with Y3+ cations, leading to the formation of mixed B‐site Y2[Ru1.6Y0.4]O7−δ. This porous Y2[Ru1.6Y0.4]O7−δ electrocatalyst exhibits a turnover frequency (TOF) of 560 s−1 (at 1.5 V versus RHE) for the oxygen evolution reaction, which is two orders of magnitude higher than that of the RuO2 reference catalyst (5.41 s−1).
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".