Nanostructured and Spiky Gold Shell Growth on Magnetic Particles for SERS Applications
Bibliographic record
Abstract
Multifunctional micro- and nanoparticles have potential uses in advanced detection methods, such as the combined separation and detection of biomolecules. Combining multiple tasks is possible but requires the specific tailoring of these particles during synthesis or further functionalization. Here, we synthesized nanostructured gold shells on magnetic particle cores and demonstrated the use of them in surface-enhanced Raman scattering (SERS). To grow the gold shells, gold seeds were bound to silica-coated iron oxide aggregate particles. We explored different functional groups on the surface to achieve different interactions with gold seeds. Then, we used an aqueous cetyltrimethylammonium bromide (CTAB)-based strategy to grow the seeds into spikes. We investigated the influence of the surface chemistry on seed attachment and on further growth of spikes. We also explored different experimental conditions to achieve either spiky or bumpy plasmonic structures on the particles. We demonstrated that the particles showed SERS enhancement of a model Raman probe molecule, 2-mercaptopyrimidine, on the order of 104. We also investigated the impact of gold shell morphology—spiky or bumpy—on SERS enhancements and on particle stability over time. We found that spiky shells lead to greater enhancements, however their high aspect ratio structures are less stable and morphological changes occur more quickly than observed with bumpy shells.
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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".