Active infrared tuning of metal–insulator-metal resonances by VO2 thin film
Bibliographic record
Abstract
VO 2 is a promising phase change material offering a large contrast of electric, thermal, and optical properties when transitioning from semiconductor to metallic phase. Here we show that a hybrid metamaterial obtained by proper combination of a VO 2 layer and a nanodisk gold array provides a tunable plasmonic gap resonance in the infrared range. Specifically, we have designed and fabricated a metal–insulator-metal gap resonance by inserting sub-wavelength VO 2 film between a flat gold layer and a gold nanodisk resonator array. The resonance of the hybrid metamaterial is centered in the useful 3–5 μm range when VO 2 is in its semiconductor state. The experimental study highlights a monotonical spectral tuning of the resonance when increasing temperature up to 50 °C above the room temperature, providing a continuous resonance shift of almost 1 μm in the mid-infrared range. Wavelength range and intensity tunability can be further optimized by modifying the thicknesses of the layers and metamaterial parameters.
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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".