Surface structural characteristics and tunable electronic properties of wet-chemically prepared Pd nanoparticles
Bibliographic record
Abstract
The ligand substitution reaction, Pd L(3,2,1)-edge and S K-edge x-ray absorption fine structure (XAFS), XAFS simulations, and valence-band and core-level x-ray photoelectron spectroscopy (XPS) have been used to systematically study the surface chemical and electronic properties of wet-chemically prepared Pd nanoparticles of varied size, molecular capping, and metal composition. It was found that the replacement of weakly interacting capping molecules (amine and tetra-alkylphosphonium bromide) with strongly binding thiols caused a considerable change in the surface bonding of Pd nanoparticles. However, the Pd d-electron counts (number of d electrons) remained almost unchanged before and after ligand substitution, which is unexpected since Pd atoms normally lose electrons to the more electronegative S atoms. XAFS results and simulations provided useful insights into the surface structural characteristics of Pd nanoparticles and satisfactorily accounted for the unexpected d-electron behavior involved in the ligand substitution process. XPS valence and core-level spectra further revealed a size-dependent d-band narrowing and presented complementary information to XAFS about the surface electronic properties of Pd atoms. The small weakly bound Pd nanoparticles seem inevitably to have a net d-electron depletion due to the influence of the surface effect (chemical adsorption by oxygen), which is more significant than the d-electron enriching nanosize effect. However, it was demonstrated that by forming Pd-Ag alloy nanoparticles, a net increase of the Pd d-electron counts can be realized. Therefore, it is illustrated that by manipulating the surface, size, and alloying effects, the electronic properties of Pd nanoparticles can be possibly tuned.
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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 | 0.000 | 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) | 0.000 | 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".