Heteroepitaxial Growth of Gold Nanostructures on Silicon by Galvanic Displacement
Bibliographic record
Abstract
This work focuses on the synthesis and interfacial characterization of gold nanostructures on silicon surfaces, including Si(111), Si(100), and Si nanowires. The synthetic approach uses galvanic displacement, a type of electroless deposition that takes place in an efficient manner under aqueous, room-temperature conditions. The case of gold-on-silicon has been widely studied and used for several applications and yet, a number of important, fundamental questions remain as to the nature of the interface. Some studies are suggestive of heteroepitaxial growth of gold on the silicon surface, whereas others point to the existence of a silicon-gold intermetallic sandwiched between the metallic gold and the underlying silicon substrate. Through detailed high resolution transmission electron microscopy (TEM), combined with selected area electron diffraction (SAED) and nanobeam diffraction (NBD), heteroepitaxial gold that is grown by galvanic displacement is confirmed on both Si(100) and Si(111), as well as silicon nanowires. The coincident site lattice (CSL) of gold-on-silicon results in a very small 0.2% lattice mismatch due to the coincidence of four gold lattices to three of silicon. The presence of gold-silicon intermetallics is suggested by the appearance of additional spots in the electron diffraction data. The gold-silicon interfaces appear heterogeneous with distinct areas of heteroepitaxial gold on silicon, and others, less well-defined, where intermetallics may reside. The high resolution cross-sectional TEM images reveal a roughened silicon interface under these aqueous galvanic displacement conditions, which most likely promotes nucleation of metallic gold islands that merge over time: a Volmer-Weber growth mechanism in the initial stages.
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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 | 0.000 |
| 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 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".