Structural Self-Regulation-Promoted NO Electroreduction on Single Atoms
Bibliographic record
Abstract
Simultaneously elevating loading and activity of single atoms (SAs) is desirable for SA-containing catalysts, including single-atom catalysts (SACs). However, the fast self-nucleation of SAs limits the loading, and the activity is confined by the adsorption-energy scaling relationships on monotonous SAs. Here, we theoretically design a novel type of SA-containing catalyst generated by two-step structural self-regulation. In the thermodynamic self-regulation step, divacancies in graphene spontaneously pull up SAs from transition metal supports ( dv -g/TM; TM = fcc Co, hcp Co, Ni, Cu), leading to the expectably high loading of SAs. The subsequent kinetic self-regulation step involving an adsorbate-assisted and reversible vacancy migration dynamically alters coordination environments of SAs, helping circumvent the scaling relationships, and consequently, the as-designed dv -g/Ni can catalyze NO-to-NH 3 conversion at a low limiting potential of −0.25 V vs RHE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".