Concentration Effects of Co and Cu Dopants in β-Ni(OH) <sub>2</sub> on Ammonia Oxidation Activity and Selectivity
Bibliographic record
Abstract
The electrochemical ammonia oxidation reaction offers a potential approach for energy generation or remediation of aqueous nitrogenous waste. The development of affordable and stable electrocatalysts is needed for the widespread use of the AOR. Ni-based electrodes offer a cheaper alternative to other electrocatalysts while having moderate activity and long-term stability. This work uses density functional theory to investigate the effect of Co and Cu surface dopants at varying concentrations in β-Ni(OH) 2 and their impact on ammonia oxidation activity and selectivity. The introduction of Co doping to β-Ni(OH) 2 reduced the *NH 2 to *NH free energy, leading to lowered limiting potentials for N 2 ( g ) formation. Cu doping led to the reduction in energy required for the hydroxylation of *NO to *NO 2 H. This hydroxylation step is the typical limiting potential step for the production of NO 2 – ( aq ) and suggests that Cu doping may impact the selectivity toward NO 2 – ( aq ) production. This work begins to understand the effect of surface doping β-Ni(OH) 2 in differing ratios in an attempt to improve the performance of Ni-based 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 | 0.000 |
| 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".