SBIR-STTR Award

MEMS with sensors, actuators and control functions in a large network system often needs to work in a harsh environment involving changes in mechanical, chemical, and electromagnetic loading at high frequencies and high intensities. The objectives of this SBIR Program are: (1) to develop a MEMS simulator that can provide simulated and accelerated environment/loading conditions for accurate assessment of MEMS reliability; (2) to achieve high reliability by developing the first generation self-diagnosis and self-recovery MEMS packaging technique. To achieve these objectives, in phase-1 and option phase, the key loading parameters and related testing techniques will be identified, and MEMS testing will be performed to establish database. In addition, the technique of using embedded sensor array inside MEMS will be developed for load monitoring and MEMS self-diagnosis. Predictive damage models will be developed for reliability assessment. The results will lead to a prototype design of MEMS simulator, to be implemented and commercialized in Phase-2. In addition, the project attempts to develop self-recovery function by using two types of smart materials with self-recovery and self-healing functions. The new concept of self-recovery MEMS will be verified in Phase-1 and option, and commercialized for dual application in Phase II

MEMS with sensors, actuators and control functions in a large network system often needs to work in a harsh environment involving changes in mechanical, chemical, and electromagnetic loading in wide ranges of frequencies and at high intensities. The main objectives of this SBIR program are to develop a MEMS simulator that can provide simulated loading/environment for accurate assessment of MEMS reliability, and to achieve high reliability by developing a new MEMS packaging technique with self-diagnosis and self-recovery functions. This is achieved by the application of smart materials that can automatically respond to external loading, thus, reducing the tendency of microstructural damage. In addition, new testing methodology will be developed with use of embedded sensors and with wireless communication capability in monitoring packaging process and operation. The developed understanding, technology and testing simulator will be beneficial to the growing MEMS industry and users, including the automotive, aerospace, biochemical and consumer sectors.

Keywords:
Mems Packaging, Advanced Testing, Smart Materials, Shape Memory Effect, Displacement Measurement