The Effect of Deposition Rate on the Morphology of Fe Nanoparticles on Highly Oriented Pyrolytic Graphite, As Studied by X-ray Photoelectron Spectroscopy and Atomic Force Microscopy
Bibliographic record
Abstract
The effect of deposition rate on the morphology of Fe nanoparticles (NPs) on highly oriented pyrolytic graphite (HOPG) surfaces has been studied by atomic force microscopy (AFM) and in situ X-ray photoelectron spectroscopy (XPS). AFM provided the NP dimensions and the extent of surface coverage, while XPS (both core and valence levels) indicated the interaction of Fe NPs with the HOPG substrate and showed the evolutions of binding energies, full widths at half-maxima, and component peak intensity ratios, all as a function of deposition rate. The results indicate that Fe NPs react with both substrate and residual gases in the high vacuum of the instrument, forming carbide and oxide surface contaminant layers around the NPs. The NP dimensions are essentially independent of deposition rate and of the amount deposited, but the NP surface coverage is inversely related to the deposition rate, with a higher rate resulting in a lower surface coverage. Combining the NP surface coverage and the XPS peak intensity ratios, we find a relationship between deposition rate and surface contaminant layer thickness.
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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 | 0.002 |
| 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) | 0.001 | 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 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".