Robust Analysis of 4e <sup>–</sup> Versus 6e <sup>–</sup> Reduction of Nitrogen on Metal Surfaces and Single-Atom Alloys
Bibliographic record
Abstract
The electrochemical synthesis of hydrazine is an exciting avenue in the sustainable production of commonly used chemicals. Taking inspiration from the mechanistic selectivity of reactions such as the 2e– versus 4e– oxygen reduction reaction (ORR), we explore how to fine-tune catalysts for hydrazine synthesis through the 4e– electrochemical nitrogen reduction reaction (NRR) over the popular 6e– NRR used for ammonia synthesis. Optimal 4e– NRR performance requires sufficient activity as well as selectivity over 6e– NRR, other mechanistic NRR branching points, and the hydrogen evolution reaction (HER). In this study, we perform first-principles calculations in conjunction with uncertainty quantification on various monometallic and single-atom alloy surfaces to study the activity and selectivity of 4e– NRR. Through free energy diagrams, estimation of scaling relations, and a theoretical activity volcano, we observe that catalysts exhibiting low activity due to weak binding for NH3 favor hydrazine synthesis. We also find that single-atom alloys follow the same scaling relations as monometallic surfaces. Through uncertainty quantification, we form distributions of limiting potentials and establish a correlation between the activity of a catalyst with the skewness of its limiting potential distribution. We further quantify the uncertainty of first-principles calculations for branching points within 4e– NRR. Reaction branching point analysis reveals the difficulty of overcoming the HER for weakly binding catalysts and the affinity toward 6e– NRR for stronger binding catalysts. This underlines the significant challenges of pushing NRR toward hydrazine synthesis.
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".