Multimodal Spectroscopy Assays for Advanced Nano-Optics Approaches by Tuning Nano-Tool Surface Chemistry and Metal-Enhanced Fluorescence
Bibliographic record
Abstract
In this research work, different chemical modifications were applied to gold nanoparticles and their use in enhanced non-classical light emitters based on metal-enhanced fluorescence (MEF) was evaluated. In order to achieve this, gold core–shell nanoparticles with silica shells were modified via multilayered addition and the incorporation of a covalently linked laser dye to develop MEF. Their inter-nanoparticle interactions were evaluated by using additional silica shell multilayers and modified cyclodextrin macrocycles. In this manner, the sizes and chemical surface interactions on the multilayered nanoarchitectures were varied. These optical active nanoplatforms led to the development of different nanoassembly sizes and luminescence behaviors. Therefore, the interactions and nanoassembly properties were evaluated by using various spectroscopic and nanoimaging techniques. Highly dispersible gold core–shell nanoparticles with diameters of 50–60 nm showed improved colloidal dispersion that led to single ultraluminescent gold core–shell nanoparticles with MEF. Then, the addition of variable silica lengths produced increased interactions and consequent nanoaggregation. However, the silanized nanoparticles were easily dispersible after agitation or sonication. Thus, their sizes were proportional only to the diameter and the van de Waals interaction did not affect their sizes in bulk. Then, the covalent linking of different concentrations of modified cyclodextrins was applied to the chemical surfaces by incorporating additional hydroxyl groups from the glucose monomeric unities of cyclodextrins. In this manner, variable larger-sized and inter-branched grafted gold core–shell silica nanoparticles were generated. The ultraluminescent properties were conserved due to the non-optical activity of the cyclodextrins. However, they generated enhanced ultraluminescence phenomena. Laser fluorescence microscopy nanoimaging showed enhanced resolutions in comparison to non-grafted supramolecular gold core–shell nanoparticles. The differences in their interactions and the sizes of the nanoassemblies were explained by their single nanoparticle diameters and the interacting chemical groups on their nanosurfaces. While the varied luminescence emissions generated were tuned by plasmonics, enhanced plasmonic phenomena and light scattering properties were seen depending on the type of nanoassembly. Thus, optically active and non-optically active materials led to different optical properties in the bright field and enhanced the excited state within the electromagnetic near-field of the gold nanotemplates. In this manner, it was possible to achieve high sensitivity by varying the spacer lengths and optical properties. Therefore, further perspectives regarding the design of nano-tools composed of light for various applications were discussed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".