Rational design and characterization of bimetallic gold‐palladium nanoparticle catalysts
Bibliographic record
Abstract
This feature article covers a long‐term project in our laboratory at the University of Saskatchewan towards the rational synthesis of controlled‐architectures of gold‐palladium bimetallic nanoparticle catalysts for use as low‐temperature alcohol oxidation catalysts. Syntheses involve controlled growth of nanoparticle architectures via solution‐based nanoparticle synthetic strategies, followed by deposition of the designed particles onto solid supports. In addition, characterization methods used to elucidate structures of the synthesized particles before and after activation for catalysis will be discussed. This includes traditional characterization methods such as transmission electron microscopy and X‐ray absorption fine structure spectroscopy (EXAFS), but also includes, more recently, the use of in situ X‐ray absorption spectroscopy studies of gold‐palladium nanoparticle catalysts. Strategies and challenges towards the rational synthesis of heterogeneous supported‐nanoparticle catalysts based on bimetallic nanoparticle precursors will be detailed and contrasted with more traditional routes to synthesize such catalytic materials.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".