Large-scale dewetting assembly of gold nanoparticles for plasmonic enhanced upconversion nanoparticles
Bibliographic record
Abstract
Plasmonic nanostructures have been broadly investigated for enhancing many photophysical properties of luminescent nanomaterials. Precisely controlling the distance between the plasmonic nanostructure and the luminescent material is challenging particularly for the large-scale production of individual nanoparticles. Here we report an easy and reliable method for the large-scale dewetting of plasmonic gold nanoparticles onto core-shell (CS) upconversion nanoparticles (UCNPs). A commensurate NaYF4 shell with a thickness between 5 nm and 15 nm is used as a tunable spacer to control the distance between the UCNP and the plasmonic gold nanoparticles. The upconversion emission intensity of single gold decorated core-inert shell (Au-CS) UCNPs is quantitatively characterized using a scanning confocal microscope. The results demonstrate the highest feasible enhancement of upconversion emission and a record reduction in lifetime for UCNPs fabricated in this manner. The Au-CS UCNPs are further investigated by simulation and synchrotron near edge X-ray absorption fine structure (NEXAFS) analysis.
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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 | 0.001 | 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 | 0.001 |
| 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".