Preparation techniques for micron-sized particulate samples in X-ray microtomography

Ditscherlein, Ralf; Leißner, Thomas; Peuker, Urs A.

doi:10.1016/j.powtec.2019.06.001

Cited by 13 publications

(10 citation statements)

References 31 publications

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“…Figure 2a shows the sample preparation procedure beginning with a cylindrical shape (2 mm diameter, a-1) for low-resolution scans, that is manually sliced down (a-3 and a-4) to a bar for medium- and high-resolution scans (≈0.5 mm diameter, a-5). In previous studies (Ditscherlein et al, 2019), we showed that the particles are homogeneously distributed over the sample height. Thus, considering two of these different positions from the cylindrical sample was sufficient for the current study.…”

Section: Methodssupporting

confidence: 51%

“…Practical approaches to calculate a minimum number of particles based on statistical models are given in the literature (Koglin et al, 1974; Vigneau et al, 2000). We determined the optimal volume concentration of spherical particles, immobilized and embedded in a matrix, in prestudies with 10 vol% (Ditscherlein et al, 2019). The minimum concentration c min is given by the ratio of the total particle volume V Particle and the volume of the sample cylinder V Cylinder , i.e.,with the number of particles n Particle , equivalent spherical particle diameter x , the number of vertical stitches n Stitch (in this study, equal to 1), diameter d C , and height h C of the sample cylinder.…”

Section: Methodsmentioning

confidence: 99%

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Multiscale Tomographic Analysis for Micron-Sized Particulate Samples

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Section: Methodssupporting

confidence: 51%

Section: Methodsmentioning

confidence: 99%

Multiscale Tomographic Analysis for Micron-Sized Particulate Samples

et al. 2020

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“…To validate the XRM data, we also carried out experiments on a laboratory scale at 500 hPa with a standardized laboratory pressure nutsch (VDI-2762/1 2006). Detailed information about the experimental setup and the measurement principle is available in (Ditscherlein et al 2020;Löwer et al 2020b). Figure 3 illustrates both experimental setups schematically.…”

Section: Experimental Procedures and Setupmentioning

confidence: 99%

Neighborhood Relationships of Widely Distributed and Irregularly Shaped Particles in Partially Dewatered Filter Cakes

2021

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A more thorough understanding of the properties of bulk material structures in solid–liquid separation processes is essential to understand better and optimize industrially established processes, such as cake filtration, whose process outcome is mainly dependent on the properties of the bulk material structure. Here, changes of bulk properties like porosity and permeability can originate from local variations in particle size, especially for non-spherical particles. In this study, we mix self-similar fractions of crushed, irregularly shaped Al2O3 particles (20 to 90 µm and 55 to 300 µm) to bimodal distributions. These mixtures vary in volume fraction of fines (0, 20, 30, 40, 50, 60 and 100 vol.%). The self-similarity of both systems serves the improved parameter correlation in the case of multimodal distributed particle systems. We use nondestructive 3D X-ray microscopy to capture the filter cake microstructure directly after mechanical dewatering, whereby we give particular attention to packing structure and particle–particle relationships (porosity, coordination number, particle size and corresponding hydraulic isolated liquid areas). Our results reveal widely varying distributions of local porosity and particle contact points. An average coordination number (here 5.84 to 6.04) is no longer a sufficient measure to describe the significant bulk porosity variation (in our case, 40 and 49%). Therefore, the explanation of the correlation is provided on a discrete particle level. While individual particles < 90 µm had only two or three contacts, others > 100 µm took up to 25. Due to this higher local coordination number, the liquid load of corresponding particles (liquid volume/particle volume) after mechanical dewatering increases from 0.48 to 1.47.

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“…The investigation of structure and texture of ores is a pretty new but fast growing application area of CT [36,37]. While a number of publications support the usefulness of applying CT for analyzing mineral structures is still missing, a comparison with results acquired by traditional methods, e.g., optical microscopy.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Microstructural Analysis and X-ray Computed Tomography of Ores and Rocks—Comparison of Results

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Profound knowledge of the structure and texture of rocks and ores as well as the behavior of the materials under external loads is essential to further improvements in size reduction processes, particularly in terms of liberation size. New analytical methods such as computer tomography (CT) were adopted to improve the understanding of material characteristics in rocks and ores relevant to mineral processing, particular the crushing and grinding and the modelling/simulation thereof. Results obtained on the texture and structure of identical samples of rather different rocks and ores (copper ore, granodiorite, kimberlite) are compared by CT with quantitative results from traditional optical microscopy obtained by quantitative microstructural analysis (QMA). While the two approaches show a good agreement of the results in many areas, the measurements with the two different methods also exhibit remarkable differences in other areas, which are discussed further. In conclusion, both methods have their specific advantages starting from sample preparation to the accuracy of information obtained concerning certain parameters of mode and fabric. While sample preparation is faster with CT and information on special distribution of metal minerals is more reliable, the information on mode, grain size and clustering seem to be more precise with QMA. Based on the results, it can be concluded that both methods are comparable in many areas, but in in the field of spatial distribution, they are merely complementary.

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Preparation techniques for micron-sized particulate samples in X-ray microtomography

Cited by 13 publications

References 31 publications

Multiscale Tomographic Analysis for Micron-Sized Particulate Samples

Multiscale Tomographic Analysis for Micron-Sized Particulate Samples

Neighborhood Relationships of Widely Distributed and Irregularly Shaped Particles in Partially Dewatered Filter Cakes

Quantitative Microstructural Analysis and X-ray Computed Tomography of Ores and Rocks—Comparison of Results

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