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Robust MEMS Viscosity Meter for Condition-based Maintenance

Award Information
Agency: Department of Commerce
Branch: N/A
Contract: N/A
Agency Tracking Number: 600-1
Amount: $0.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 2003
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
30-H Sixth Road, Woburn, MA, 01801
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jeffrey Chan
 () -
Business Contact
Phone: () -
Research Institution
N/A
Abstract
In this NIST SBIR program Boston MicroSystems develops MEMS-based fluid viscosity-density sensors which can be installed in refrigerant system compressors to monitor, in real time, refrigerant system health. Such sensors will provide early detection of water contamination, lubricant degradation and other problems which can lead to catastrophic refrigerant system failure if left uncorrected. Such sensors will also allow scheduling of system maintenance on an as-needed basis, and will reduce system downtime, lower operating costs, and improve system reliability. Boston MicroSystems' proprietary technologies for micromachining harsh environment compatible SiC and AlN materials now allow, for the first time, fabrication of small and inexpensive fluid viscosity and density sensors that can operate in the harsh environments inside refrigeration systems and other machinery. In Phase 1, Boston MicroSystems tested the suitability of three of its already developed SiC-AlN MEMS sensors (microresonators, SAWs and FPWs) for this application, and demonstrated that FPW (flexural plate wave) sensors meet the required performance specifications. In Phase 2, we will develop, characterize and deliver to NIST fully functional prototype refrigerant system health monitors based on our FPW sensors, including packaging for installation into refrigerant system compressors and electronics and software to convert sensor response into system health data.

* Information listed above is at the time of submission. *

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