Nanoscale displacement measurement of microdevices via interpolation-based edge tracking of optical images

We apply an interpolation-based edge-tracking algorithm to measure nanoscale displacements of microdevices, and further enhance its ability to reject noisy signals using averaging of multiple image frames. We present a simulation of a moving edge, and use this simulation to explore the performance of the algorithm as related to the image acquisition and process parameters. Then, we present the application of this technique to two experiments. First, we demonstrate optical measurement of the motion of a compliant mechanism, and smoothly detect lateral step motion change as small as 30.8 nm s^-1. Second, we measure the anisotropic nanoscale expansion of a liquid crystal network micropillar, which occurs slowly over several minutes. This efficient algorithm can smoothly track motions as small as a few per cent of a pixel, which is equivalent to tens of nanometers using images from a video camera attached to a conventional optical microscope. Therefore, this technique can be widely applied to characterization of nanoscale motions using conventional optics, without requiring special features on the device to enable imaging.