Robot‐Assisted Automated Serial‐Sectioning and Imaging for 3D Microstructural Investigations
Year: 2025
Type: article
Abstract: Comprehensive materials characterization requires precise structural knowledge beyond traditional methods. The robot‐assisted automated serial‐sectioning and imaging (RASI) platform, developed at BAM, provides automated 3D metallographic reconstructions, enabling detailed microstructural analysis of technical materials. This article showcases RASI's capabilities through several case studies, including characterization of lamellar graphite in gray cast iron, porosity in sintered steel, melt pool morphology in additively manufactured 316L stainless steel, defects in metal‐ceramic packages, and oxidation behavior in an Fe‐12Cr‐2Co alloy. By automating sample handling, mechanical serial‐sectioning, etching, and optical imaging, RASI captures complex 3D microstructures with high precision and at high speed. This approach reveals microstructural features missed by 2D analysis, even using stereological assumptions. Specifically, statistically rare and large microstructural features, such as secondary phases or interconnected pores, become apparent, which 2D methods cannot reveal. The generated volumetric data can furthermore serve as quantitative reference datasets (i.e., the ‘ground truth’) essential for validating other 3D characterization techniques and computational models, helping to bridge the gap between predictive simulations and real‐world material behavior. RASI's modular design makes it a flexible tool that provides realistic 3D insights into materials, which can be used for advanced materials research, process optimization, and quality control.
Source: Advanced Engineering Materials
Authors: Michael Moschetti, Anton Lemiasheuski, Evgenia Bajer, Ilja Porohovoj, Artur Göbel, Anja Pfennig, Dirk Bettge, Robert Maaß
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,520
OpenAlex ID: W4416851967