Characterization and acoustic emission monitoring of AFM nanomachining

This study aims to determine the machining characteristics during nano-scratching of silicon wafers using AFM and to monitor the machining states using acoustic emission (AE). Along with a specially designed AFM experimental setup, simplified geometric models are employed to estimate the friction coefficient and the minimum chip formation depth for nano-machining. In the nano-experiments, with the increase of the engaging depth of an AFM tip, two modes of plastic deformation-ploughing mode and cutting mode-are observed. With the aid of AFM and FE-SEM images, typical features of each mode, such as pile-up and chip formations, are illustrated and analyzed. Moreover, it is shown that pile-up formation is closely related to the deformation characteristics at the corresponding scratching depth, and the ratio of pile-ups to the groove depth can be used as an index to indicate the mode transition. As far as in-process monitoring is concerned, during the ploughing mode, related AE RMS values are relatively low. By contrast, the RMS values during the cutting mode are significantly higher than those during the ploughing mode, with apparent chip formation. In addition, AE count rates show appropriate sensitivity to detect the mode transition. Our results indicate that the proposed scheme can be used to characterize nano-scale machining and to monitor the mode transition