Paper
16 January 2003 Long-Term Drift Measurements in MEMS-Based Mass Flow Controllers
Elizabeth Lawrence, Albert K. Henning
Author Affiliations +
Proceedings Volume 4980, Reliability, Testing, and Characterization of MEMS/MOEMS II; (2003) https://doi.org/10.1117/12.498239
Event: Micromachining and Microfabrication, 2003, San Jose, CA, United States
Abstract
Micro-electromechanical systems (MEMS) components find increasing use in devices which measure and control gas flow, for medical and industrial use. Little or no information on the reliability of these devices has been published. This work reports the results of long-term performance studies of pressure-based mass flow controllers (MFCs) comprised of MEMS microvalves, pressure sensors, and critical flow orifices. Specifically, the details of long-term drift in the silicon pressure sensors (which comprise the flow sensor) are presented. Generally, pressure-based MFCs using MEMS components retain a flow accuracy of better than 1% of full scale over a 20:1 dynamic range, with response time under 0.5 sec, after more than three million operation cycles. The primary cause of inaccuracy within this dynamic range, and of inaccuracy larger than 1% of full scale beyond this range, is attributable to uncompensated zero-offset drift in the silicon pressure sensors, whose behavior is intrinsic to the flow sensor. Data is presented which details this characteristic, across many MFCs. Mechanical, thermal, fluidic, pneumatic and electronic mechanisms possibly responsible for the drift are also presented. Means to overcome this long-term drift phenomenon in silicon pressure sensors will complete the discussion.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Elizabeth Lawrence and Albert K. Henning "Long-Term Drift Measurements in MEMS-Based Mass Flow Controllers", Proc. SPIE 4980, Reliability, Testing, and Characterization of MEMS/MOEMS II, (16 January 2003); https://doi.org/10.1117/12.498239
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Sensors

Microsoft Foundation Class Library

Reliability

Silicon

Calibration

Microelectromechanical systems

Control systems

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