Imaging of Non-conducting Beam Sensitive Materials using Scanning Electron Microscopy: Practical Applications of ESEM and LVSEM

Non-conducting and beam sensitive materials like polymers are utilized extensively in modern industry. With growing interest in leveraging the capabilities of these materials by optimizing their morphological and structural characteristics, scanning electron microscopy (SEM) is becoming an increasingly important tool. Despite the advancement of SEM and advent of high caliber instrumentation, numerous challenges impede the imaging and study of beam sensitive materials using SEM. This thesis focuses on Environmental SEM and Low Voltage SEM and attempts to showcase their characterization capabilities through practical examples of respirators/facemasks, and microplastics. A set of characterization protocols for evaluating the structure, chemistry, moisture retention, and wetting properties of face masks and respirators are presented in Chapter 3. Chapter 4 presents efforts undertaken for capturing and compiling SEM images to form the first open-source SEM datasets for microplastics segmentation through deep learning methods. The promising result facilitates automatic quantification and classification of microplastics.