Selectively Coupling Ru Single Atoms to PtNi Concavities for High‐Performance Methanol Oxidation via <i>d</i>‐Band Center Regulation
Bibliographic record
Abstract
Abstract Single atom tailored metal nanoparticles represent a new type of catalysts. Herein, we demonstrate a single atom‐cavity coupling strategy to regulate performance of single atom tailored nano‐catalysts. Selective atomic layer deposition (ALD) was conducted to deposit Ru single atoms on the surface concavities of PtNi nanoparticles (Ru‐ca‐PtNi). Ru‐ca‐PtNi exhibits a record‐high activity for methanol oxidation reaction (MOR) with 2.01 A mg −1 Pt . Also, Ru‐ca‐PtNi showcases a significant durability with only 16 % activity loss. Operando electrochemical Fourier transform infrared spectroscopy (FTIR) and theoretical calculations demonstrate Ru single atoms coupled to cavities accelerate the CO removal by regulating d ‐band center position. Further, the high diffusion barrier of Ru single atoms in concavities accounts for excellent stability. The developed Ru‐ca‐PtNi via single atom‐cavity coupling opens an encouraging pathway to design highly efficient single atom‐based (electro)catalysts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".