Characterizing vibration-assisted atomic force microscopy (AFM)-based nanomachining via perception of acoustic emission phenomena using a sensor-based real-time monitoring approach

Abstract

The emerging atomic force microscope (AFM)-based nanolithography offers promising opportunities for nanopatterning applications. However, critical issues reside in the nanomachining process because the heterogeneous material properties and machine tool (AFM tip) quality variations can create significant uncertainties at this nanoscale. Therefore, in-process monitoring is essential for timely anomaly detection and real-time process characterizations. This paper reports a sensor-based monitoring approach that allows classifications of different conditions of vibration-assisted nanopatterning in real-time by automatically selecting acoustic emission spectral responses that distinguish different amounts of material removal. It opens up an avenue toward process characterizations and mechanisms discovery in vibration-assisted nanoscale manufacturing.