Phospholipid Membrane Encapsulation of Nanoparticles for Surface-Enhanced Raman Scattering
Bibliographic record
Abstract
Lipid-encapsulated surface-enhanced Raman scattering (SERS) nanoparticles, with promising applications in biomedical diagnostics, were produced. Gold nanoparticles, 60 nm in diameter, were coated with a ternary mixture of DOPC, sphingomyelin, and cholesterol. The lipid layer is versatile for engineering the chemical and optical properties of the particles. The stability of the lipid-encapsulated particles is demonstrated over a period of weeks. The versatility of the layer is demonstrated by the incorporation of three different Raman-active species using three different strategies. The lipid layer was directly observed by TEM, and the SERS spectrum of the three dye species was confirmed by Raman spectroscopy. UV-vis absorption and dynamic light scattering provide additional evidence of lipid encapsulation. The encapsulation is achieved in aqueous solution, avoiding phase transfer and possible contamination from organic solvents. Furthermore, when fluorescent dye-labeled lipids were employed in the encapsulant, the fluorescence and SERS activity of the particles were controlled by the use of dissolved ions in the preparation solution.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".