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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Hassanpour, Ali
in Cooperation with on an Cooperation-Score of 37%
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Publications (7/7 displayed)
- 2022Nano-scale characterization of particulate iron pyrite morphology in shalecitations
- 2022Functionalization of metallic powder for performance enhancementcitations
- 2020Analysis of the osteogenic and mechanical characteristics of iron (Fe2+/Fe3+)-doped β‑calcium pyrophosphatecitations
- 2020Analysis of the osteogenic and mechanical characteristics of iron (Fe 2+ /Fe 3+ )-doped β‑calcium pyrophosphatecitations
- 2020Investigation of powder flowability at low stresses by DEM modellingcitations
- 2020Investigation of powder flowability at low stresses: Influence of particle size and size distributioncitations
- 2018A magnetically separable SO 4 /Fe-Al-TiO 2 solid acid catalyst for biodiesel production from waste cooking oil
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article
Nano-scale characterization of particulate iron pyrite morphology in shale
Abstract
This study analyzes the morphology of iron pyrite particles within a shale sample captured using nano-computed tomography (Nano-CT). The complex, framboidal morphology of the iron pyrite particles is characterized using various metrics, and comparisons are drawn on their effectiveness to quantify their observed morphological characteristics. Then, simplified representations of selected iron pyrite particles are generated to facilitate a sensitivity analysis of the effect of imaging resolution on morphological parameters of particle form. A discussion is developed on the required number of pixels per particle diameter for particle shape characterization. It is shown that shape indices that rely on the simplified main particle dimensions can be accurately calculated even for low fidelity levels of 10 pixels per particle diameter. More complex shape indices that use vertices, volume, and surface area, are more sensitive to image resolution, even for 40 pixels per particle diameter.