Reversible Alkaline Hydrogen Evolution and Oxidation Reactions Using Ni–Mo Catalysts Supported on Carbon
Bibliographic record
Abstract
Unitized regenerative fuel cells based on hydroxide exchange membranes are attractive for long duration energy storage. This mode of operation depends on the ability to catalyze hydrogen evolution and oxidation reversibly, and ideally using nonprecious catalyst materials. Here we report the synthesis of Ni–Mo catalyst composites supported on oxidized Vulcan carbon (Ni–Mo/oC) and demonstrate their performance for reversible hydrogen evolution and oxidation. For the hydrogen evolution reaction, we observed mass-specific activities exceeding 80 mA/mg at 100 mV overpotential, and additional measurements using hydroxide exchange membrane electrode assemblies yielded full cell voltages that were only ~100 mV larger for Ni–Mo/oC cathodes compared to Pt–Ru/C at current densities exceeding 1 A/cm2. For hydrogen oxidation, Ni–Mo/oC films required <50 mV overpotential to achieve half the maximum anodic current density, but activity was limited by internal mass transfer and oxidative instability. Nonetheless, estimates of the mass-specific exchange current for Ni–Mo/oC from micropolarization measurements showed its hydrogen evolution/oxidation activity is within 1 order of magnitude of commercial Pt/C. Density functional theory calculations helped shed light on the high activity of Ni–Mo composites, where the addition of Mo leads to surface sites with weaker H-binding energies than pure Ni. These calculations further suggest that increasing the Mo content in the subsurface of the catalyst would result in still higher activity, but oxidative instability remains a significant impediment to high performance for hydrogen oxidation.
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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 | 0.001 | 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".