Processing of Electron Microscope Images of Complex Nanoscale Devices and Materials

Material studies with imaging have been actively employed over the past few decades for fabrication and characterization applications in the nanotechnology field. This paper presents an automated analysis method for detecting the nanoscale and microscale structures and determining their sizes from scanning electron microscope (SEM) images. The MATLAB-based numerical image processing techniques introduced in this work can accurately detect the edges of material and device structures or their defects from the varying monochromatic contrast of different imaged materials. This proposed image processing technique can precisely compute the centroid, area, perimeter, and other relevant dimensional parameters of the structure of interest. The algorithm encompasses image binarizing with adaptive thresholding, grayscale conversion, and filtering to isolate the specific desired structures. We showed the detection of voids in a Ge<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>Sb<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>Te<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</inf> nanodevice and computed the centroid, area, and perimeter for each detected void. We compared the voids' area calculated using MATLAB image processing with those computed in GoExplore and ImageJ tools to validate the image processing method presented in this work. We repeated the detection procedures of various types of circular and elliptical voids and hexagonal structures from the SEM images from published works to evaluate the efficacy of the detection method. With minimal adjustment of the image processing parameters, the top view plane of all structures could be identified accurately. This study opens up new possibilities for finite element method analysis in materials research with exact modeling of the geometries of materials and devices utilizing the automated and precise evaluations of multiple complex structures from SEM images.