SBIR Phase I: Comprehensive Metrology and Control of MEMS

该小型企业创新研究第一阶段项目将建立在MEMS制造过程中测量关键特性的能力，以帮助MEMS代工厂和设计人员构建更精确的传感器，同时缩短设计周期，并将建立电探测自校准有可能取代当前昂贵和繁琐的物理校准方法。MEMS器件的校准目前占制造成本结构的20%以上，并且随着时间的推移一直在稳步增长。在更高性能的设备中，它可以是制造成本的80%。自校准方法的成功演示，其精度等于或大于传统的物理校准方法，不仅使该行业能够消除这种快速增长的成本驱动因素，而且还可以通过动态改变器件的性能来实现按需MEMS器件的新时代。的有效参数和属性，使用电信号来调整测量值的自校准过程中。该项目的智力价值的核心是开发一种电子手段来校准MEMS器件。 与传统的昂贵、繁琐的物理方法相比，这种新方法将提供相等或更高的精度，这些方法限制了MEMS行业。该研究将对多个MEMS工艺制造的许多“自校准”MEMS器件进行测量，从多个铸造厂和多个运行中提供一个强大的数据集，以提供使用自校准的新工艺信息，并建立与传统校准方法的比较结果（技术和经济）。如果成功，这将通过放松物理校准限制，并可能实现全新的MEMS器件性能需求，在MEMS设计和生产中引入一个全新的范例。

This Small Business Innovation Research Phase I project will establish the ability to measure key properties in the MEMS fabrication process to help MEMS foundries and designers build more accurate sensors while shortening the design cycle and will establish that electrically probed self-calibration has the potential to replace the current costly and cumbersome physical calibration approach. Calibration of MEMS devices currently comprises over 20% of the manufacturing cost structure and has been steadily increasing over time. In higher performance devices, it can be 80% of the manufacturing cost. Successful demonstration of self-calibration methods, with accuracy equal to, or greater than, traditional physical calibration methods will not only enable the industry to eliminate this rapidly-growing cost driver, but could also enable a new era of performance-on-demand MEMS devices by that dynamically alter the device?s effective parameters and properties using electrical signals to adjust the values measured in the self-calibration process.The intellectual merit of this project centers on the development of an electronic means to calibrate MEMS devices. This mew method will deliver equal or greater accuracy as compared with traditional costly, cumbersome physical means that are constraining the MEMS industry. The research will take measurements on many "self-calibrating" MEMS devices fabricated across multiple MEMS processes, from multiple foundries and multiple runs to provide a robust data set to provide new process information using self-calibration and also to establish comparative results (both technical and economics) results with traditional calibration approaches. If successful, this could usher in a completely new paradigm in MEMS design and production by relaxing the physical calibration constraints and potentially enabling an entirely new class of performance on demand MEMS devices.