Electronic Backflow Through Oxygen Bridge in RuO <sub>x</sub> ‐Graphdiyne for Stable Acidic Water Oxidation
Bibliographic record
Abstract
Abstract Developing cost‐effective and stable catalysts for oxygen evolution reaction (OER) in proton exchange membrane water electrolyzers (PEMWE) remains a significant challenge. Although RuO 2 shows promise as an alternative to the expensive IrO x , its large‐scale application is hindered by the over‐oxidation of Ru into soluble high‐valent species (> +4). In this work, the in situ growth of RuO x species on graphdiyne (GDY) is reported, establishing strong electronic metal‐support interaction to form the Ru─O─C oxygen bridge structure. Interestingly, in situ X‐ray absorption spectroscopy (XAS) at Ru K ‐edge reveals an unexpected electronic backflow on the Ru sites under positive potential during OER, leading to a stable low chemical state of Ru. As another aspect, in situ XAS at C K ‐edge shows the process of GDY losing electrons during OER, confirming the electron injection from C to Ru through the oxygen bridge structure. This electronic backflow process can block the over‐oxidation of Ru. As a result, the RuO x ‐GDY catalyst exhibits a low overpotential of 193 mV at 10 mA cm −2 with remarkable stability over 300 h (a degradation rate of only 0.13 mV h −1 ). In the PEMWE, the catalyst achieves a cell voltage of 1.72 V at 1 A cm −2 , outperforming the conventional RuO 2 (1.91 V).
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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 | 0.000 |
| 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".