Trends in Catalysis and Catalyst Cost Effectiveness for N<sub>2</sub>H<sub>4</sub>Fuel Cells and Sensors: a Rotating Disk Electrode (RDE) Study
Bibliographic record
Abstract
Hydrazine (N 2 H 4 ) is a promising high-power energy carrier for fuel cells, combining the energy density of methanol (MeOH) with the rapid oxidation kinetics of hydrogen (H 2 ). N 2 H 4 does not require expensive Pt group metals nor Au for low-potential (high voltage) oxidation, offering significantly lower fuel cell materials costs compared to H 2, MeOH, ethanol (EtOH), and ammonia (NH 3 ). In our study, we use rotating disk electrode (RDE) voltammetry to explore N 2 H 4 oxidation at a wide variety of catalysts, including first-row transition metals (Co, Ni), coinage metals (Ag, Au) and Pt group metals (Ru, Rh, Pd, Ir, Pt). While several groups have focused on Co, Ni, or CoNi alloys, we find that other metals, including Ag, Ru, and Pd, offer much higher electron recovery and have more stable reactions, and still cost far less than Pt, Au, Rh, or Ir. We analyze our findings in terms of cost vs performance for the metals, developing a guide for the design of N 2 H 4 fuel cell systems and sensors to suit various application spaces. The many metals studied also reveal an important trend for the theoretical understanding of catalysis: the onset and passivation of N 2 H 4 oxidation in nearly every system were directly tied to the appearance or disappearance of specific metal surface states (e.g., hydrides and oxides). Indeed, metals with multiple surface states frequently showed multiple mechanisms for N 2 H 4 oxidation, each with separate values for electron recovery. These observations provide support for the continued development of electrocatalytic theory in which different metal surface states are treated as independent materials with distinct reaction mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".