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Due to the lack of sophisticated component libraries for microelectromechanical systems (MEMS), highly optimized MEMS sensors are currently designed using a polygon driven design flow. The advantage of this design flow is its accurate mechanical simulation, but it lacks a method for an efficient and accurate electrostatic analysis of parasitic effects of MEMS. In order to close this gap in the polygon-driven design flow, we present a customized electrostatic analysis flow for such MEMS devices. Our flow features a 2.5D fabrication-process simulation, which simulates the three typical MEMS fabrication steps (namely deposition of materials including topography, deep reactive-ion etching, and the release etch by vapor-phase etching) very fast and on an acceptable abstraction level. Our new 2.5D fabrication-process simulation can be combined with commercial field-solvers such as they are commonly used in the design of integrated circuits. The new process simulation enables a faster but nevertheless satisfactory analysis of the electrostatic parasitic effects, and hence simplifies the electrical optimization of MEMS.
A new method for the analysis of movement dependent parasitics in full custom designed MEMS sensors
(2017)
Due to the lack of sophisticated microelectromechanical systems (MEMS) component libraries, highly optimized MEMS sensors are currently designed using a polygon driven design flow. The strength of this design flow is the accurate mechanical simulation of the polygons by finite element (FE) modal analysis. The result of the FE-modal analysis is included in the system model together with the data of the (mechanical) static electrostatic analysis. However, the system model lacks the dynamic parasitic electrostatic effects, arising from the electric coupling between the wiring and the moving structures. In order to include these effects in the system model, we present a method which enables the quasi dynamic parasitic extraction with respect to in-plane movements of the sensor structures. The method is embedded in the polygon driven MEMS design flow using standard EDA tools. In order to take the influences of the fabrication process into account, such as etching process variations, the method combines the FE-modal analysis and the fabrication process simulation data. This enables the analysis of dynamic changing electrostatic parasitic effects with respect to movements of the mechanical structures. Additionally, the result can be included into the system model allowing the simulation of positive feedback of the electrostatic parasitic effects to the mechanical structures.
Due to the lack of sophisticated component libraries for microelectromechanical systems (MEMS), highly optimized MEMS sensors are currently designed using a polygon driven design flow. The advantage of this design flow is its accurate mechanical simulation, but it lacks a method for analyzing the dynamic parasitic electrostatic effects arising from the electric coupling between (stationary) wiring and structures in motion. In order to close this gap, we present a method that enables the parasitics arising from in-plane, sensor-structure motion to be extracted quasi-dynamically. With the method's structural-recognition feature we can analyze and optimize dynamic parasitic electrostatic effects.