Unlocking the potential: analyzing 3D microstructure of small-scale cement samples from space using deep learning.

ABSTRACT: Due to the prohibitive cost of transporting raw materials into Space, in-situ materials along with cement-like binders are poised to be employed for extraterrestrial construction. A unique methodology for obtaining microstructural topology of cement samples hydrated in microgravity environment at the International Space Station (ISS) is presented here. Distinctive Scanning Electron Microscopy (SEM) micrographs of hardened tri-calcium silicate (C₃S) samples were used as exemplars in a deep learning-based microstructure reconstruction framework. The proposed method aids in generation of an ensemble of microstructures that is inherently statistical in nature, by utilizing sparse experimental data such as the C₃S samples hydrated in microgravity. The hydrated space-return

SUBMITTER: Saseendran V 

PROVIDER: S-EPMC11381549 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature