Temporal Analysis of Photo‐Thermally Induced Reconfigurability in a 1D Gold Grating Filled with a Phase Change Material
Bibliographic record
Abstract
Abstract In this study, the finite‐element method is used to numerically calculate a photo‐thermally induced reconfigurability in a 1D gold grating structure filled with the phase change material Ge2Sb2Se4Te1 (GSST). GSST features a reversible and stable phase change between amorphous and crystalline phases around a critical temperature of 410 K with broadband low optical loss. In this study, the required heating for the transition between phases is provided by a nanosecond Gaussian pulse laser through a photo‐thermal absorption process. A comprehensive heat transfer analysis is performed to investigate the thermal characterizations of the proposed structure. The results show that in the amorphous state, the structure has a near unity absorption band in the infrared region. As the temperature increases during the pulse, the GSST undergoes the amorphous to crystalline phase change. In the intermediate states (partial crystallization) of the GSST two resonance peaks are excited and the absorption finally reaches its minimum value of 0.2 in the GSST crystalline phase. The findings of this study not only provide the fundamental concepts for the suggested tunable structure, but also have potential applications in a variety of nanophotonic devices including thermal emission controllers, sensors, and optical detection 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 | 0.000 |
| 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".