Real-Time Machine Learning Aided Feature Characterization in Scanning Transmission Electron Microscopy (STEM) Images of MoS₂

This abstract has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).<br/>Recent advances in application of machine learning techniques towards materials science has attracted significant interest in autonomous experiments (AE) on microscopy. However, the incorporation of AE in microscopy often requires fast and automated identification of features/regions of interest and subsequent operations on these features/regions. In this talk, using monolayer MoS₂ as the material of example, we showcase a machine learning-based, automated workflow of atomic feature identifications and structural manipulations via electron beam irradiation on scanning transmission electron microscopes (STEM). Based on High-Angle Annular Dark Field (HAADF) image of MoS₂ acquired real-time on STEM, we first use convolutional neural networks (CNN) trained from the Ensemble Learning Iterative Training (ELIT) approach to identify locations of atoms. We then apply graph-based encoders to classify elements, anomalies, defects, and nanostructures, which allows the final step of atomic fabrications with precise beam control on or near desired atoms and nanostructures. Through this example, we show how machine learning techniques can be combined with advanced instrument control and domain knowledge to create automated, real-time, and customized STEM workflow that is efficient and intelligent.<br/>Microscopy research was performed at the Center for Nanophase Materials Sciences at Oak Ridge National Laboratory, which is a US Department of Energy (DOE), Office of Science User Facility.