High-Fidelity Morphological and Mineralogical Reconstruction of Chang’E-5 Lunar Regolith Grains

Abstract

The complex structure and physicochemical properties of lunar soil particles form a critical foundation for future lunar exploration and in-situ resource utilization. To address the distortion introduced by oversimplified particle morphology and composition assumptions in conventional modeling approaches, we propose a high-fidelity morphological and mineralogical reconstruction method of Chang’E-5 lunar regolith grains using micro-CT characterization and advanced image processing. Twenty-one representative lunar particles were selected and subjected to high-resolution X-ray computed tomography (X-CT) scanning for comprehensive characterization of their 3D internal structures. A segmentation workflow was developed to achieve precise particle identification and mesh model generation, integrating unsupervised clustering, morphological optimization, and voxel-to-mesh conversion. Scanning electron microscopy and energy-dispersive spectroscopy were employed to identify mineral phases and reconstruct their spatial distribution within the particles. Based on these characterizations, models applicable to the discrete element method and finite element method were constructed. This work forms a comprehensive digital lunar particle dataset encompassing optical images, X-CT 3D images, mesh models, discrete element and finite element models. This integrated approach enables high-fidelity representation of morphology, internal structure, and mineralogical composition of particles, significantly enhancing modeling accuracy and simulation scalability compared to previous methods. The digital model repository established in this study provides standardized and extensible data resources to support mechanical simulations, in-situ resource evaluation, and the design of lunar detection devices.