Multiscale Tomographic Analysis for Micron-Sized Particulate Samples

Abstract

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PARROT: A Pilot Study on the Open Access Provision of Particle-Discrete Tomographic Datasets

“…Table 1 summarizes some aspects of data exchange between the working areas (i)-(v) within this database, distinguishing between write accesses (database filling) and read accesses (database query). More precisely, the PARROT database will contain metadata on sample preparation procedures (working area (i)) which can depend on the particle system under consideration (including, for example, dry dispersion or extraction only to avoid fragmentation) and the required analysis volume (ideally matching the FOV of the measurement) (Ditscherlein et al, 2020a(Ditscherlein et al, , 2020b. In addition, the metadata of the image acquisition (working area (ii)) can provide indications of possible artifacts (Boas & Fleischmann, 2012) in the subsequent image processing of the image stack which is uploaded to an external archive (OpARA) and linked via a digital object identifier (DOI) to the PARROT database.…”

“…To begin with, particle systems can be efficiently characterized by modeling the distribution of individual particle characteristics using univariate parametric probability distributions (Johnson et al, 1994(Johnson et al, , 1995. Moreover, the particle-discrete vectors of characteristics allow for the modeling of multivariate distributions which capture the correlation structure of considered characteristics (Ditscherlein et al, 2020a;Furat et al, 2019a), see Appendix A-2 of the Supplementary Material. Besides this, the segmented tomographic image data can be used to calibrate stochastic geometry models.…”

“…More precisely, univariate distributions do not provide any information on whether and how particle characteristics are correlated with each other (for example, if larger particles are more spherically shaped, etc.). Therefore, we deploy multivariate parametric distributions for modeling the joint distribution of characteristicsthus, capturing the correlation between characteristics (Furat et al, 2019a(Furat et al, , 2021aDitscherlein et al, 2020a). Then, the considered particle system can be described by just a few model parameters.…”

“…The related application for particle characterization originally comes from the field of geology (Carlson & Denison, 1992; Cnudde & Boone, 2013) but is increasingly used for the analysis of particulate and porous materials in mechanical process engineering (Leißner et al, 2020). Depending on the selected particle system, a reasonable analysis often requires a multiscale approach, for example, for composite particles and/or particles the sizes of which cover various length scales (Ditscherlein et al, 2020 a ). In this pilot study, however, we restrict ourselves to single-phase particle systems with a relatively narrow particle size distribution, for which the analysis can be performed without the correlation of measurements on multiple length scales.…”

Mounted Single Particle Characterization for 3D Mineralogical Analysis—MSPaCMAn

“…The ideal sample described here is difficult to achieve in practice [27]. Deviations from the ideal standard may be corrected on the next steps of the workflow or could otherwise add uncertainty to phase classification [28,29].…”