Atomic Ensemble and Electronic Effects in Ag-Rich AgPd Nanoalloy Catalysts for Oxygen Reduction in Alkaline Media
Bibliographic record
Abstract
The ability to design and characterize uniform, bimetallic alloy nanoparticles, where the less active metal enhances the activity of the more active metal, would be of broad interest in catalysis. Herein, we demonstrate that simultaneous reduction of Ag and Pd precursors provides uniform, Ag-rich AgPd alloy nanoparticles (~5 nm) with high activities for the oxygen reduction reaction (ORR) in alkaline media. The particles are crystalline and uniformly alloyed, as shown by X-ray diffraction and probe corrected scanning transmission electron microscopy. The ORR mass activity per total metal was 60% higher for the AgPd(2) alloy relative to pure Pd. The mass activities were 2.7 and 3.2 times higher for Ag(9)Pd (340 mA/mg(metal)) and Ag(4)Pd (598 mA/mg(metal)), respectively, than those expected for a linear combination of mass activities of Ag (60 mA/mg(Ag)) and Pd (799 mA/mg(Pd)) particles, based on rotating disk voltammetry. Moreover, these synergy factors reached 5-fold on a Pd mass basis. For silver-rich alloys (Ag(≥4)Pd), the particle surface is shown to contain single Pd atoms surrounded by Ag from cyclic voltammetry and CO stripping measurements. This morphology is favorable for the high activity through a combination of modified electronic structure, as shown by XPS, and ensemble effects, which facilitate the steps of oxygen bond breaking and desorption for the ORR. This concept of tuning the heteroatomic interactions on the surface of small nanoparticles with low concentrations of precious metals for high synergy in catalytic activity may be expected to be applicable to a wide variety of nanoalloys.
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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".