2019
DOI: 10.1016/j.apgeochem.2018.12.024
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Characterization of spatial porosity and mineral distribution of crystalline rock using X-ray micro computed tomography, C-14-PMMA autoradiography and scanning electron microscopy

Abstract: The spatial porosity and mineral distribution of geological materials strongly affects transport processes in them.X-ray micro computed tomography (X-μCT) has proven to be a powerful tool for characterizing the spatial mineral distribution of geological samples in 3-D. However, limitations in resolution prevent an accurate characterization of pore space especially for tight crystalline rock samples and 2-D methods such as C-14polymethylmethacrylate (C-14-PMMA) autoradiography and scanning electron microscopy (… Show more

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Cited by 26 publications
(14 citation statements)
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“…In the laboratory WPDE for PGR, the effect of anion exclusion was not observed. In previous studies by Sammaljärvi et al [37] and Voutilainen et al [58], it has been shown that VGN and PGR samples from REPRO site differ considerably with respect to pore space and mica and clay mineral content. In VGN, the pore space consists mostly of inter-lamellar pores in mica minerals (biotite, muscovite and chlorite).…”
Section: Discussionmentioning
confidence: 89%
“…In the laboratory WPDE for PGR, the effect of anion exclusion was not observed. In previous studies by Sammaljärvi et al [37] and Voutilainen et al [58], it has been shown that VGN and PGR samples from REPRO site differ considerably with respect to pore space and mica and clay mineral content. In VGN, the pore space consists mostly of inter-lamellar pores in mica minerals (biotite, muscovite and chlorite).…”
Section: Discussionmentioning
confidence: 89%
“…(2018) have shown that the samples studied in the here have a volumetric porosity ranging from 0.1% to 0.3%. In intact samples, the interfaces of the pores and minerals of the rock form the inner surface area that is available for sorption of radionuclides (Voutilainen et al., 2019b). The specific inner surface area (S i) was estimated in the following way:The grains were assumed to be spheres with a mean diameter of grains (d).…”
Section: Methodsmentioning
confidence: 99%
“…Previously Voutilainen et al [30] have resolved the 3D mineral structure of the samples with X-μCT and determined the porosity distribution with C-14-PMMA autoradiography. Furthermore, they have constructed 3D grain maps of the samples by first segmentating different main mineral phases from each other by their X-ray attenuation coefficient and then grains from mineral phases by running a watershed algorithm on 3D mineral phase images.…”
Section: Rock Samplesmentioning
confidence: 99%
“…Here a numerical method will be used to analyze grain properties by considering one gray scale value at the time and then add up a range of gray scale values to get the properties of a mineral phase. The starting point of the procedure is the 3D grain maps obtained by Voutilainen et al [30]. The analysis is carried out using the numerical groundwater flow and solute transport code DarcyTools [20,21].…”
Section: Grain and Mineral Surface Analysismentioning
confidence: 99%
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