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Pore Network Model Metrics Extraction Tool Using SNOW2 and OpenPNM from Segmented 3D Volumes

Almeida de Campos, Leonardo ORCID iD icon 1; Sheppard, Thomas L. ORCID iD icon; Grunwaldt, Jan-Dierk ORCID iD icon 1
1 Institut für Technische Chemie und Polymerchemie (ITCP), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

This dataset contains a Python-based workflow for extracting pore network model (PNM) metrics from segmented 3D tomographic volumes.

The workflow integrates PoreSpy (SNOW2 algorithm) for pore network extraction and OpenPNM for the computation of structural and transport properties.

The tool allow the calculation of porosity, pore size Distribution, throat size, and coordination number from labeled volumetric data.

Input data must be provided as 3D labeled TIFF volumes, where labels correspond to:
0 = outside domain, 1 = solid phase, and 2 = pore phase.

This repository represents the archived version associated with the corresponding scientific work. The actively maintained version of the code is available in the linked GitHub repository.

LINK: "https://github.com/Leonardolac97/pore-network-model-metrics-extraction-tool-using-snow2-and-openpnm-from-segmented-3d-volumes.git"


Zugehörige Institution(en) am KIT Institut für Technische Chemie und Polymerchemie (ITCP)
Publikationstyp Forschungsdaten
Publikationsdatum 14.04.2026
Erstellungsdatum 01.12.2025 - 08.04.2026
Identifikator DOI: 10.35097/wx033rkaeuzp5ynr
KITopen-ID: 1000192032
Lizenz Creative Commons Namensnennung – Nicht kommerziell 4.0 International
Schlagwörter pore network modeling, SNOW2, OpenPNM, X-ray tomography, porous materials, pore metrics
Liesmich

The workflow is implemented in a Jupyter Notebook and uses a single input file: a 3D TIFF (segmented volume). Data can be loaded from local directories, and an output folder can be specified to generate results (e.g., plots, statistics, and HTML files).

Art der Forschungsdaten Software
KIT – Die Universität in der Helmholtz-Gemeinschaft
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