Pressure sensing in vacuum hermetic micropackaging for MOEMS-MEMS
Bibliographic record
Abstract
Packaging constitutes one of the most costly steps of MEMS/MOEMS manufacturing. Uncooled IR bolometers require a vacuum atmosphere below 10 mTorr to operate at their highest sensitivity. The bolometer response is also dependent on the package temperature. In order to minimize cost, real estate and power consumption, temperature stabilization is typically not provided to the package. Hence, long term high sensitivity operation of IR bolometric radiometers requires a calibration as function of in package pressure and temperature. A low-cost and accurate means of measuring the pressure in the package without being affected by the operating temperature is therefore needed. INO has developed a low-cost, low-temperature hybrid vacuum micropackaging technology <sup>1-3</sup>. An equivalent flow rate of 4×10<sup>-14</sup> Torr·L/sec for storage at 80°C has been obtained without getter. Even with such low flow, the long term stabilization of residual pressure variations affects the sensitivity and calibration of the IR bolometers. INO has developed MEMS pressure sensors that allow for real-time measurement of package pressure above 1 mTorr, and can be integrated with the IR bolometers in a die-level packaging process or microfabricated simultaneously on the same die. In this paper, the typical performance and measurement uncertainty of these pressure sensors will be presented along with a reading method that provides a pressure measurement with a dependence on the package temperature as low as 0.7 %/°C. Complex reading circuit or temperature control of the packages are not required, making the pressure sensor well adapted for low-cost high-volume production and integration with IR bolometer arrays.
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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 | 0.001 |
| 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".