Characterization of Particle Morphology in Lunar Regolith Soil Simulants by Automated Particle Analysis using Scanning Electron Microscopy

Particle morphology and elemental composition of lunar and Martian regolith are critical properties to consider for long-duration human and robotic missions. Dust on these planetary surfaces can influence equipment performance, spacesuit integrity, and habitat safety, while also presenting opportunities to be used as an in-situ resource. This study examines six lunar regolith soil simulants supplied by NASA and SolSys Mining using automated particle analysis with scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). The investigation focuses on the coarse particle fraction (20-75 micrometers), a size range that plays a critical role in surface operations and mechanical wear. Coarser particles differ significantly from fine dust in terms of mobility, abrasion potential, and interaction with hardware, making their characterization vital for equipment design and mission planning. The automated particle analysis system collects high-resolution SEM images and elemental spectra for thousands of particles, enabling the correlation of particle morphology (i.e., size, shape, and surface texture) with elemental composition. While a previous study on these simulants focused on the <20 micrometer fraction, where notable differences in morphology were observed compared to published Apollo data, the present study characterizes of the 20-75 µm particles. In this larger fraction, morphologies indicative of heat treatment (e.g., glassy, spherical, and vesicular) are more distinct and readily recognized. Finally, an artificial intelligence (AI) model was developed to test the ability of machine learning to identify and distinguish among these specific particle morphologies using micro-images acquired during the automated SEM analysis.