Phase‐Separated Mo–Ni Alloy for Hydrogen Oxidation and Evolution Reactions with High Activity and Enhanced Stability
Bibliographic record
Abstract
Abstract The development of alkaline polymer electrolyte fuel cells and alkaline water electrolysis requires nonprecious metal catalysts for the hydrogen oxidation reaction (HOR) and hydrogen evolution reaction (HER). Herein, it is reported a phase‐separated Mo–Ni alloy (PS‐MoNi) that is composed of Mo metal and embedded Ni metal nanoparticles. The PS‐MoNi shows excellent hydrogen electrode activity with a high exchange current density (−4.883 mA cm −2 ), which is comparable to the reported highest value for non‐noble catalysts. Moreover, the amorphous phase‐separated Mo–Ni alloy has better structural and electrochemical stability than the intermetallic compound Mo–Ni alloy (IC‐MoNi). The breakdown potential of PS‐MoNi is as high as 0.32 V, which is much higher than that of reported IC‐MoNi. The X‐ray absorption near edge structure (XANES) and density functional theory (DFT) calculations indicate the electrons transfer from Mo to Ni for PS‐MoNi, leading to suitable adsorption free energies of H* (Δ G H* ) on the surface of Mo. This means that the electron density modulation of Mo metal by embedded Ni metal nanoparticles can produce excellent HOR and HER performance.
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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".