Amorphous SiSn Alloy: Another Candidate Material for Temperature Sensing Layers in Uncooled Microbolometers
Bibliographic record
Abstract
Herein, the prospect of using amorphous Si 1– x Sn x alloys as alternative temperature‐sensing active materials in microbolometers is evaluated by studying their temperature‐dependent resistive properties along with their infrared optical properties. Si 1– x Sn x thin films (200 nm thick), with varying Sn concentrations, are prepared at room temperature by cosputtering from Si and Sn targets using simultaneous radio frequency and DC magnetron sputter deposition. Low beam energy X‐ray microanalysis is used to estimate the atomic concentrations of the prepared films. Atomic force microscopy analysis shows an increase in the root‐mean‐square surface roughness of the prepared Si 1– x Sn x thin films, with increasing Sn content. Sheet resistance versus temperature measurements are performed yielding temperature coefficients of resistance of 3.25, 2.65, and 1.72% K −1 at resistivity values of 116.18, 27.36, and 2.34 Ω cm for Sn concentrations of 35%, 44%, and 48%, respectively. Infrared ellipsometry measurements are performed to extract the optical properties of the Si 1– x Sn x thin films and optical simulations confirm that a Fabry–Pérot cavity microbolometer configuration containing an Si 1– x Sn x thin film can achieve high absorptance in the 8–12 μm band. This study shows that Si 1– x Sn x alloys are a suitable, simple, and low‐cost replacement for thermometer layers used in uncooled infrared microbolometers.
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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) | 0.001 | 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 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".