Using fundamental studies of friction to predict the performance of MEMS devices

The design of reliable MEMS devices that involve sliding surfaces requires a predictive capability for friction and wear. We use atomic force microscopy (AFM) to resolve critical roughness features of silicon MEMS surfaces. From this, we derive surface roughness parameters that are used as inputs to predict the interfacial mechanics using random and fractal surface models. This allows us to determine parameters such as the real contact area as a function of the applied pressure. Using silicon surfaces coated with hydrophobic monolayers, we measure single-asperity constitutive laws using AFM. Combining the calculations of the contact area with the measured nanoscale friction laws, we make predictions for MEMS friction behavior. We discuss the validation of these predictions with reference to multi-asperity MEMS friction test device experiments. This work was supported by the US Department of Energy, BES-Materials Sciences, under Contract DE-FG02-02ER46016 and by Sandia National Laboratories. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under contract DE-AC04-94AL85000.