Three-Dimensional Particle-Discrete Datasets: Enabling Multidimensional Particle System Characterization Using X-Ray Tomography

Abstract

This collection of studies, conducted within the framework of the DFG-funded Priority Program SPP 2045, explores the role of X-ray tomography in advancing the multidimensional characterization of particulate systems, with a strong focus on enhancing 3D particle-discrete data quality. It critically assesses the limitations of traditional particle characterization methods, particularly those reliant on imaging techniques, and demonstrates how advanced methodologies can overcome these constraints by providing highly detailed and accurate geometric and structural 3D data. The research further introduces innovative sample preparation techniques for particle collectives, aiming to reduce post-processing efforts in image analysis. Additionally, the development of a particle database, aligned with FAIR data principles (Findable, Accessible, Interoperable, and Reusable), supports data sharing and collaborative research. Ultimately, this collection underscores the transformative potential of 3D particle-discrete datasets acquired through X-ray tomography in advancing particle technology and improving particle system analyses across diverse scientific and industrial fields.

Keywords

• 3D particle characterization
• particle-discrete data
• X-ray tomography
• multidimensional analysis
• sample preparation
• image processing