Reliable element-specific d-band analysis of transition metal nanoparticles using X-ray absorption spectroscopy
Bibliographic record
Abstract
Metallic nanoparticles (NPs) have been extensively studied as improved catalysts due to their unique atomic structures and electronic properties. A reliable strategy to characterize the electronic properties, specifically the d-band structure, of metal NPs is challenging. In this work, we present a general strategy for fitting the X-ray absorption near edge spectroscopy (XANES) spectrum to accurately determine the electronic properties in metal NPs, and deduce d-band parameters such as the d-band width and d-band center position. In conjunction with valence band X-ray photoelectron spectroscopy (VBXPS), our fitting analysis reliably calibrates the XANES spectrum such that effects of instrumental and core-hole broadening are minimized, and the d-band structure can be accurately determined. For a series of palladium (Pd) NPs, we use our XANES fitting analysis approach to characterize the Pd d-band, and identify trends in the electronic properties consistent with prior literature reports. In closing, we propose a mechanism in which the Pd d-band changes due to size, and surface effects based on our element-specific XANES fitting analysis within the framework of the popular Nørskov d-band model of transition metal surfaces. We anticipate that this experimental d-band analysis methodology will be useful for studying structure-property relationships and catalysis on monometallic and multimetallic NPs.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".