Scalable Super-Resolution Synthesis of Core-Vest Composites Assisted by Surface Plasmons
Bibliographic record
Abstract
The behavior of composite nanostructures depends on both size and elemental composition. Accordingly, concurrent control of size, shape, and composition of nanoparticles is key to tuning their functionality. In typical core-shell nanoparticles, the high degree of symmetry during shell formation results in fully encapsulated cores with severed access to the surroundings. We commingle light parameters (wavelength, intensity, and pulse duration) with the physical properties of nanoparticles (size, shape, and composition) to form hitherto unrealized core-vest composite nanostructures (CVNs). Unlike typical core-shells, the plasmonic core of the resulting CVNs selectively maintains physical access to its surrounding. Tunable variations in local temperature profiles ≳50 °C are plasmonically induced over starburst-shaped nanoparticles as small as 50-100 nm. These temperature variations result in CVNs where the shell coverage mirrors the temperature variations. The precision thus offered individually tailors access pathways of the core and the shell.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".