Enhancement of YBCO microbolometer performances with regionally thinned microbridges
Bibliographic record
Abstract
Silicon nitride microbridges (50x50 mm<sup>2</sup>, 0.6 mm thick), suspended over a silicon substrate, were patterned and thinned. These patterns consist of 2 to 12 windows that were thinned to approximately 0.3 mm. Microbolometers were fabricated by sputtering a YBaCuO thin film over the bridges. The experimental results showed that the regionally thinned microbridges have a lower thermal time constants t (about 1.6 ms) than that of the standard pixel configuration (2.6 ms). On the other hand, the fact that the regionally thinned microbolometers having detectivity D* values comparable to or even six times superior than that of the standard pixel showed that the decrease in response time is not penalized by loss of detection performance. The simulation results also show that as the amount of material removed is increased, the thermal time constant drops significantly while the (τ/G)<sup>1/2</sup> ratio (where G is the thermal conductance of the pixel) only decreases slightly, suggesting that the reduced response time will not cause a significant drop in detectivity D*. The simulation results of mechanical integrity show that a specific regionally thinned microbridge design has 22 % higher stiffness than that of a standard pixel design with similar thermal properties. The fact that thick regions remained on the regionally thinned pixels (like the edges of the pixels) provide significant mechanical support to the microstructures. This confirms the validity of the regionally thinned microbridges approach.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".