Single-atom alloy catalysts: structural analysis, electronic properties and catalytic activities
Bibliographic record
Abstract
Monometallic catalysts, in particular those containing noble metals, are frequently used in heterogeneous catalysis, but they are expensive, rare and the ability to tailor their structures and properties remains limited. Traditionally, alloy catalysts have been used instead that feature enhanced electronic and chemical properties at a reduced cost. Furthermore, the introduction of single metal atoms anchored onto supports provided another effective strategy to increase both the atomic efficiency and the chance of tailoring the properties. Most recently, single-atom alloy catalysts have been developed in which one metal is atomically dispersed throughout the catalyst via alloy bonding; such catalysts combine the traditional advantages of alloy catalysts with the new feature of tailoring properties achievable with single atom catalysts. This review will first outline the atomic scale structural analysis on single-atom alloys using microscopy and spectroscopy tools, such as high-angle annular dark field imaging-scanning transmission electron microscopy and extended X-ray absorption fine structure spectroscopy. Next, progress in research to understand the electronic properties of single-atom alloys using X-ray spectroscopy techniques and quantum calculations will be presented. The catalytic activities of single-atom alloys in a few representative reactions will be further discussed to demonstrate their structure-property relationships. Finally, future perspectives for single-atom alloy catalysts from the structural, electronic and reactivity aspects will be proposed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".