Ultra-clean wafer-level vacuum encapsulated inertial sensors using a commercial process
Bibliographic record
Abstract
Inertial sensors, such as accelerometers and gyroscopes, have become ubiquitous in our daily lives and are found in a variety of devices and applications that require measurement of motion, direction, vibration and orientation. These integrated sensors benefiting from the tremendous advancements in microfabrication technology continue to grow rapidly providing efficient control and continuous monitoring in a variety of applications including smartdevices, automotive, aerospace, and industrial robotics. Here, both the choice of the fabrication technology and the design of the sensor devices play an important role to develop high performance MicroElectroMechanical Systems (MEMS) inertial sensors to insure stability, repeatability and accuracy of the measurements during operation. Literature review of MEMS inertial sensors reveals that many of these sensors are developed using full custom or proprietary micromachining processes. Till recently, standard pure-play MEMS processes had several limitations including choice of materials and lack of wafer-level vacuum packaging that made them incapable to support development of integrated inertial sensors with high performance specifications. Recently, the availability of standard pure-play MEMS processes that offer excellent advantages in high quality materials and advanced packaging could lead to development of new inertial sensors that can be readily mass-produced. These devices could help towards lowering the cost of devices with increased competition to existing players in the market and pursuing niche application areas that cannot be satisfied by available devices in the market. The present research aims to design, fabricate and characterize high performance novel integrated capacitive inertial sensors including both single axial and multi-axis accelerometer and a multi-axis gyroscope for angular rate measurement. The developed devices are based on two standard pure-play processes offered by Teledyne DALSA Semiconductor Inc. (TDSI). In 2013, TDSI introduced MEMS Integrated Design for Inertial Sensors (MIDIS) process, which is currently the only commercial MEMS process that includes ultra-clean wafer-level vacuum encapsulation of the MEMS devices at 10 mTorr. MIDIS process helps towards achieving a high Quality factor and reducing noise interference on the MEMS sensor devices. The developed inertial sensors in MIDIS process include a uniaxial accelerometer with ultra-low noise performance enabling resolution of 33mg over a high-g range of ±100g, tri-axial accelerometer with very low cross-axis sensitivity of 0.8%, and rate grade gyroscope with high Quality factor (> 50,000). This research is the first demonstration of wafer-level vacuum packaging of MEMS inertial sensors in a high volume pure-play MEMS process.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".