Modeling photothermal induced bistability in vanadium dioxide/1D photonic crystal composite nanostructures
Bibliographic record
Abstract
We theoretically investigate the absorption bistability behavior of a nanostructure consisting of a vanadium dioxide (VO2) layer grown on top of a one-dimensional photonic crystal. The proposed structure is illuminated by a continuous wave pump laser, resulting in heat generation within the VO2 layer, and a subsequent phase transition which drastically affects the optical response of the nanostructure. We solve a multiphysics problem containing electromagnetism and thermodynamics in order to show that the optically induced transitions in the VO2 layer can lead to a bistable response in the nanostructure over some ranges of incident intensities during the VO2 heating and cooling modes. Interestingly, when the laser is well set up for an appropriate wavelength, the high contrast of two absorption values in the hysteresis loop indicates bistability and the possibility of achieving near-unity absorption. For example, considering λ = 1025 nm, we get bistability over 1.182 W/cm2 < I < 1.457 W/cm2 which leads to absorption values of about 0.47 and 0.999 for the heating and cooling modes, respectively. The corresponding heat generation for I = 1.3 W/cm2 is 2.41 × 105 W/cm3 and 3.52 × 105 W/cm3, respectively. These properties make our structure promising for designing tunable VO2-based absorbers and optical switching devices.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".