Ab initio study of atomically dispersed catalysts on original and B-doped corrugated carbon nitride surface for effective nitrogen reduction
Bibliographic record
Abstract
• Reconfirm the stability of corrugation in graphitic carbon nitride using computational methods. • Theoretically find out the most stable structure of boron-doping. • Screen out prospective single-atom and dual-atom catalysts based on non-precious for electrocatalytic nitrogen reduction. • Provide theoretical guidance for selecting effective highly dispersed catalysts for nitrogen reduction. Highly dispersed metal atoms as active sites of electrocatalysis, including single and dual atoms, have been raising researchers’ interest in applications on ammonia production in recent years. A well-designed catalyst can significantly improve the performance of nitrogen reduction by efficiently activates the dinitrogen (N 2 ) molecules, promotes the protonation steps, and suppresses the hydrogen evolution, making it a possible substitution of the classic Haber process for reducing the energy input and resource consumption. Using first-principles calculations, graphitic carbon nitrides was tested as the substrate of electrocatalysts in this study due to their ability of anchoring dispersed atoms within their electron-rich cavities, and the corrugated structure was proved to be more stable. As a result, several Mo-based atomic catalysts on g-C 3 N 4 , including Mo, MnMo, and FeMo, were screened out as potential candidates due to their lower limiting potential for nitrogen reduction, while the introduction of boron on the substrate could further improve the performance of Mo single-atom catalyst, leading to an excellent theoretical Faradaic efficiency of 86.1 %, even better than the performance of the Ru-based catalyst.
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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) | 0.000 | 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".