Metal-Enhanced Fluorescence and FRET in Multilayer Core-Shell Nanoparticles
Bibliographic record
Abstract
In recent years, various methods for the synthesis of fluorescent core-shell nanostructures were developed, optimized, and studied thoroughly in our research group. Metallic cores exhibiting plasmonic properties in the UV and visible regions of the electromagnetic spectrum were used to increase substantially the brightness and stability of organic fluorophores encapsulated in silica shells. Furthermore, the efficiency and range of Förster resonant energy transfer (FRET) between donor and acceptor molecules located in the vicinity of the metallic core was shown to be enhanced. Such multilayer nanoparticle architectures offer, in addition to the aforementioned advantages, excellent chemical and physical stability, solubility in aqueous media, low toxicity, and high detectability. In view of these enviable characteristics, a plethora of applications have been envisioned in biology, analytical chemistry, and medical diagnostics. In this paper, advances in the development of multilayer core-shell luminescent nanoparticle structures and selected applications to bioanalytical chemistry will be described.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".