Breathing mode in Nd-CoOx for active and stable proton exchange membrane water electrolysis
Bibliographic record
Abstract
Proton-exchange membrane water electrolysis in acidic solutions holds great promise for advancing the green-hydrogen economy but limited by using precious-metal catalysts. Here, we develop a low-cost Co3O4-based catalyst with oxygen vacancies and Nd-insertion (Nd-CoOx). This catalyst achieves a low overpotential of 317 mV at 10 mA cm−2 for acidic oxygen evolution reaction and remains stable over 800 h. The oxygen vacancies in Nd-CoOx enhance its catalytic activity, while Nd enables the long-term stability through a flexible “breathing mode” during oxygen evolution reaction, as revealed by in-situ methods such as X-ray absorption spectroscopy and Raman spectroscopy. The presence of Nd also improves the catalytic activity with the oxide path mechanism. This favorable strategy can be extended to other lanthanides. When used as the anode, Nd-CoOx delivers good performance in water electrolysis to achieve 200 mA cm−2 at a low cell voltage of 1.69 V with low degradation over 100 h, and can reach 1 and 2 A cm−2 at 1.93 V and 2.12 V, respectively. Proton-exchange-membrane water electrolysis is crucial for advancing the green-hydrogen economy but is limited by the use of precious-metal catalysts. Here, the authors report a Nd-CoOx catalyst in which Nd confers long-term stability via a flexible atomic “breathing mode.”
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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) | 0.000 | 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 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".