Awarded Grants

National Science Foundation

January 2015 - Sugarcube Systems is a proud winner of the 2015 SBIR Phase 1 award from the National Science Foundation for the feasibility project: Comprehensive Metrology and Control of MEMS.


April 2015 - Sugarcube Systems is a proud winner of a grant from the Indiana Economic Development Corporation and Elevate Ventures.

National Science Foundation

July 2015 - Sugarcube Systems is proud to announce winning (Phase 1B) their second award from the National Science Foundation for the feasibility project: Accurate Calibration for the Atomic Force microscope and other Cantilever-Based Sensors.


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 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 new 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) 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.