In-situ polarization modulation IRRAS investigation of ammonia electrooxidation on Pt-Ir and Pt-Ru nanoparticles prepared on engineered catalyst supports
Bibliographic record
Abstract
The catalytic activity and surface reactivity of monometallic Pt and bimetallic Pt-Ir and Pt-Ru nanoparticles , supported on two distinct Engineered Catalyst Supports (ECSs), were investigated for the Ammonia Electrooxidation Reaction (AmER) in alkaline media. XRD measurements confirmed alloy formation between Pt-Ir and Pt-Ru nanoparticles, as indicated by the shift of the (111) reflection to higher 2θ values. Cyclic voltammetry, linear sweep voltammetry, and chronoamperometry experiments were conducted to assess the catalytic activity of the Pt, Pt-Ir, and Pt-Ru electrocatalysts. All bimetallic catalysts exhibited lower onset potentials compared to Pt. The differing Tafel slopes between Pt (74 mV dec⁻¹), Pt-Ir (152 mV dec⁻¹), and Pt-Ru (118–197 mV dec⁻¹) suggest that alloying Pt with Ir or Ru alters the reaction mechanisms. Furthermore, the bimetallic Pt-Ir and Pt-Ru catalysts demonstrated greater tolerance for concentrated ammonia solutions relative to Pt. In-situ Polarization Modulation Infrared Reflection Absorption Spectroscopy (PM-IRRAS) provided insights into the formation of N-H species, azide anions (N₃⁻), and N-O compounds. For the Pt-Ru catalyst, an additional peak around ∼3600 cm⁻¹ was observed, corresponding to OH⁻ species. The PM-IRRAS results align with the Gerischer–Mauerer mechanism, indicating that partially dehydrogenated ammonia adsorbates act as active intermediates in the oxidation of ammonia over Pt-Ir and Pt-Ru catalysts.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".