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Nano‐Scale Characterization of Particulate Iron Pyrite Morphology in Shale
Author(s) -
Angelidakis Vasileios,
Nadimi Sadegh,
Garum Mohamed,
Hassanpour Ali
Publication year - 2022
Publication title -
particle and particle systems characterization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 56
eISSN - 1521-4117
pISSN - 0934-0866
DOI - 10.1002/ppsc.202200120
Subject(s) - pyrite , particle (ecology) , characterization (materials science) , oil shale , mineralogy , materials science , particle size , pixel , morphology (biology) , resolution (logic) , nanotechnology , chemistry , geology , optics , physics , computer science , artificial intelligence , paleontology , oceanography
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.