3D volume reconstructions of porous materials from micro-computed tomography scans and computational geometry scripts in Python 3

Included in this dataset are 3D volume reconstructions processed from micro-computed tomography (µCT) scans of a carbon and a polymer porous scaffold templated using bicontinuous interfacially jammed emulsion gels (bijels), a porous metal, a polymerized high internal phase emulsion (polyHIPE), and a...

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1. Verfasser: Thorson, Todd
Format: Dataset
Sprache:eng
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Zusammenfassung:Included in this dataset are 3D volume reconstructions processed from micro-computed tomography (µCT) scans of a carbon and a polymer porous scaffold templated using bicontinuous interfacially jammed emulsion gels (bijels), a porous metal, a polymerized high internal phase emulsion (polyHIPE), and an inverse opal. Accompanying plain text files list the Cartesian coordinates (x, y, and z in columns 2, 3, and 4, respectively; units of millimeters) of branch points within the pore phase of each material. These branch points represent where lines drawn through the center of the pore phase (i.e. medial axis) branch into connecting pore features. By running the included computational geometry scripts in Python 3, the domain size distributions of the pore and solid phases, curvature of the interior surfaces, connectivity, tortuosity of the pore phase, de-noised branch point positions, and Voronoi tessellation from the de-noised branch point positions can be calculated for each material. These scripts are dependent on the PyMesh and Voro++ external libraries linked below, as well as the included p_fxn.py script.
DOI:10.17632/hpjtgt2847