Plasmonics of Diffused Silver Nanoparticles in Silver/Nitride Optical Thin Films
Bibliographic record
Abstract
Abstract Metal-dielectric multilayers are versatile optical devices that can be designed to combine the visible transmittance of dielectrics with the electronic properties of metals for plasmonic and meta-material applications. However, their performances are limited by an interfacial optical absorption often attributed entirely to the metal surface roughness. Here, we show that during deposition of AlN/Ag/AlN and SiNx/Ag/SiNx multilayers, significant diffusion of Ag into the top dielectric layer form Ag nanoparticles which excite localized surface plasmon resonances that are primarily responsible for the interfacial optical absorption. Based on experimental depth profiles, we model the multilayer’s silver concentration profile as two complementary error functions: one for the diffused Ag nanoparticles and one for the interface roughness. We apply the Maxwell-Garnett and Bruggeman effective medium theories to determine that diffusion characteristics dominate the experimental absorption spectra. The newfound metal nanoparticle diffusion phenomenon effectively creates a hybrid structure characteristic of both metal-dielectric multilayer and metal-dielectric composite.
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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) | 0.000 | 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".