Nanoscale manipulating plasmonic silver adatoms for dynamic light modulation
Bibliographic record
Abstract
Plasmonic colors have gained significant interest for flat panel displays due to their broad color gamut and high subwavelength resolution. The reversible metal deposition, having tunable nanostructures, along with their localized surface plasmon resonance (LSPR), is considered as a promising strategy for dynamic color displays. Herein, a demonstration of the manipulation of plasmonic silver adatoms through reversible metal deposition is presented for dynamic light modulation. The voltage-activated reversible silver nanoparticles deposition enables a wide range of dynamic plasmonic color change of 100 nm, and also facilitates a size and shape control of the grown silver nanoparticles. The silver nanoparticles interact with visible light through LSPR, the size and shape of the particles affect their optical properties. Our findings provide a favorable and novel platform for low energy-consumption tunable photonic and nanoplasmonic devices, as well as provide a simple and reliable process for rapid, scalable, and green preparation of tunable plasmonic Ag nanoparticles.
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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 | 0.000 |
| 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".