Gas-Aggregated Core–Shell ZrN@SiN Nanoparticles with Enhanced Thermal Stability for Plasmonic Applications at High Temperatures
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Group IV metal nitrides are often considered a viable replacement for gold in numerous plasmonic applications that require high temperatures. However, despite exhibiting a high melting point, these materials are prone to oxidation in an oxygen-rich environment, leading to an undesirable change or loss of the plasmonic response. This work developed an environmentally friendly method based on reactive magnetron sputtering of Zr for the synthesis of ZrN nanoparticles (NPs) with their in-flight coating by an rf-sputtered SiN shell. The resultant core–shell NPs are characterized by cubic morphology, with a 15 nm ZrN core enveloped by a 5–15 nm SiN shell. The ZrN@SiN NPs demonstrate localized surface plasmon resonance (LSPR), which can be adjusted from 580 to 850 nm by tuning the porosity and, consequently, the effective refractive index of SiN. The SiN shell attenuates the plasmonic sensitivity of ZrN NPs, but protects them from postdeposition oxidation in air, preserving LSPR at temperatures above 400 °C. Thus, this research proposes a one-step synthesis of ZrN@SiN NPs with controllable optical properties, enhanced thermal stability, and promising features for plasmonic applications at high temperatures.
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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 | 0.000 | 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 | 0.001 | 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) | 0.003 | 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".