Influence of ceramic package internal components on the performance of vacuum sealed uncooled bolometric detectors
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Bibliographic record
Abstract
INO has developed a hermetic vacuum packaging technology for uncooled bolometric detectors based on ceramic leadless chip carriers (LCC). Cavity pressures less than 3 mTorr are obtained. Processes are performed in a state-of-the art semi-automated vacuum furnace that allows for independent activation of non-evaporable thin film getters. The getter activation temperature is limited by both the anti-reflection coated silicon or germanium window and the MEMS device built on CMOS circuits. Temperature profiles used to achieve getter activation and vacuum sealing were optimized to meet lifetime and reliability requirements of packaged devices. Internal package components were carefully selected with respect to their outgassing behavior so that a good vacuum performance was obtained. In this paper, INO’s packaging process is described. The influence of various package internal components, in particular the CMOS circuits, on vacuum performance is presented. The package cavity pressure was monitored using INO’s pressure microsensors and the gas composition was determined by internal vapor analysis. Lifetime was derived from accelerated testing after storage of packaged detectors at various temperatures from room temperature to 120°C. A hermeticity yield over 80% was obtained for batches of twelve devices packaged simultaneously. Packaged FPAs submitted to standard MIL-STD-810 reliability testing (vibration, shock and temperature cycling) exhibited no change in IR response. Results show that vacuum performance strongly depends on CMOS circuit chips. Detectors packaged using a thin film getter show no change in cavity pressure after storage for more than 30 days at 120°C. Moreover, INO’s vacuum sealing process is such that even without a thin film getter, a base pressure of less than 10 mTorr is obtained and no pressure change is observed after 40 days at 85°C.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it