Multiscale Tomographic Analysis for Micron-Sized Particulate Samples. (August 2020)

• Record Type: Journal Article
• Authors: Ditscherlein, Ralf; Furat, Orkun; de Langlard, Mathieu; Martins de Souza e Silva, Juliana; Sygusch, Johanna; Rudolph, Martin; Leißner, Thomas; Schmidt, Volker; Peuker, Urs A.
• Is Part Of: Microscopy and microanalysis. Volume 26:Number 4(2020)
• Page Start: 676
• Page End: 688
• Publication Date: 2020-08
• Subjects: multidimensional particle characterization, -- multiscale X-ray tomography, -- parametric copula, -- statistical image analysis; Microscopy -- Periodicals; Microchemistry -- Periodicals; 502.82
• DOI: 10.1017/S1431927620001737
• Languages: English
• ISSNs: 1431-9276

Abstract

Abstract: Abstract : The three-dimensional characterization of distributed particle properties in the micro- and nanometer range is essential to describe and understand highly specific separation processes in terms of selectivity and yield. Both performance measures play a decisive role in the development and improvement of modern functional materials. In this study, we mixed spherical glass particles (0.4–5.8 μ m diameter) with glass fibers (diameter 10 μ m, length 18–660 μ m) to investigate a borderline case of maximum difference in the aspect ratio and a significant difference in the characteristic length to characterize the system over several size scales. We immobilized the particles within a wax matrix and created sample volumes suitable for computed tomographic (CT) measurements at two different magnification scales (X-ray micro- and nano-CT). Fiber diameter and length could be described well on the basis of the low-resolution micro-CT measurements on the entire sample volume. In contrast, the spherical particle system could only be described with sufficient accuracy by combining micro-CT with high-resolution nano-CT measurements on subvolumes of reduced sample size. We modeled the joint (bivariate) distribution of fiber length and diameter with a parametric copula as a basic example, which is equally suitable for more complex distributions of irregularly shaped particles. This enables us to capture the multidimensional correlation structure of particle systems with statistically representative quantities.