Analysis of pore space characteristics
PoroDict
Understanding pore space in porous materials is essential to optimizing their performance in key applications including filtration, energy storage, catalysis and materials science. This is exactly where the PoroDict module combined with the MatDict module comes in, providing a powerful solution for the complete characterization and analysis of porous media.
PoroDict enables precise evaluation of porosity, connectivity, and transport properties by extracting essential pore structure properties from 3D models, whether from CT, µCT or FIB/SEM data or from structures generated with GeoDict. This data-driven understanding helps researchers and engineers target materials and improve their performance for specific applications.
PoroDict offers new possibilities for academic research and industrial applications:
In battery technology, it provides critical insights into the complex pore structures of electrodes - with direct implications for energy storage and lifetime.
In fuel cell R&D, it contributes to the analysis of the gas diffusion layer (GDL) by quantifying the relevant transport properties - a lever for increasing efficiency.
In geological sciences, the module enables the assessment of the geometric structure of sandstone, which is essential for the exploration and evaluation of oil and gas deposits.
In filtration, it analyzes the pore and transport properties of woven and nonwoven media, providing the basis for innovation in filter design.
Identify pores and fractures in rocks
- Identify and separate individual pores into
- Fractures (in red)
- Small pores (in white)
- Large pores (caverns) (in dark grey)
- Obtain a range of pore statistics (diameter, sphericity, orientation…)
Figure: Identification of fracture in a digitalized carbonate rock
Pore Identification
- Identify individual pores
- Get complete pore network information
- Obtain statistical pore information e.g.,
pore diameter distribution, sphericities, etc.
Figure: Pore identification analysis on
Gildehauser sandstone, Berg et al. (2016)
Characterizing pore space of
ceramics and rocks
- Geometric Pore Size Distribution (granulometry)
- Pore Size Distribution by Porosimetry
- Largest through pore and corresponding
shortest path
Figure: Largest through pores (Percolation Path) in
a Berea sandstone
Pore throat distribution in MPL-layer
of PEM Fuel Cell
- MPL-layer generated with GrainGeo module
- Simulation of a mercury intrusion experiment
- Color coded size distribution in 3D
Figure: Pore Size Distribution of an MPL-layer in a PEM fuel cell
Compute tortuosity in digitalized
battery electrodes with GeoApp
- Analyze the lithium-ion transport in the electrolyte
- Analyze the electron movement in the active material
and the binder in cathodes - Obtain effective parameters of porous separator
structures for electrochemical simulations
(a) Geodesic tortuosity
(b) Tortuosity from percolation path
(c) Indirect computation from relative diffusivity
ASTM Norm E3278-21: Standard test method for Bubble Point Pressure of woven wire filter cloth
- ASTM Norm standardizes software-based calculations of pore size through bubble point computations.
- Compute hydraulic diameter bubble point pressure, percolation path fitting particle diameter, and pore size calculation factor.
- Results agree with the results of glass bead testing.
“Standard Test Method for Bubble Point Pressure of Woven Wire Filter Cloth,” ASTM.org, 2021. www.astm.org/e3278-21.html (accessed Feb 14, 2025)
Open-cell aluminum foam
during compression simulation
- Identify single pores in the open-cell
foam geometry. - Perform a compression simulation with
the ElastoDict module. - Study the change in shape of pores in each
compression step.
(a) Open-cell aluminum foam with all complete pores
(b) Complete pores at the beginning of compression
(c) Complete pores after compression
PoroDict provides multiple options to compute all relevant properties of the materials pore space.
The Geometric Pore Size Distribution option characterizes the pore radius by fitting spheres into the pore volume. This purely geometric method does not distinguish between through pores, closed pores and blind pores.
Pore size distribution by porosimetry is equivalent to experimental porosimetry methods such as MIP (Mercury Intrusion Porosimetry) or LEP (Liquid Extrusion Porosimetry), where the volume of a non-wetting fluid forced into the medium is calculated. This method works similarly to the geometric pore size distribution, but the connectivity to the intrusion side and closed pores are considered.
The Identify Pores option allows segmentation and analysis of individual pores. This process uses the Watershed algorithm to segment the pore space within a given medium. The segmented data is then used to determine the number and spatial distribution of pores. In addition, various pore properties are analyzed, including sphericity, volume, diameter, orientation, surface area, and contact area.
Open and Closed Porosity calculates the number and volume of open and closed pores. Open pores extend from the surface of the material to the core, forming extensive networks of interconnected pores. Closed or isolated pores do not open to the surface in any direction.
Bubble point pressure can also be calculated based on the largest through pore and the Young-Laplace equation. This feature also provides detailed pore throat analysis including pore throat area, pore throat circumference, and hydraulic diameter.
Percolation Path calculates the maximum diameter of a spherical particle traversing the medium. The corresponding shortest path is also determined. Users can calculate special cases, such as the five largest pores (with their shortest paths) or the eight shortest paths for a given diameter. The movement of spheres along these paths is displayed and animated.
Chord Length Distribution (CLD) allows accurate comparison of porous media geometries. Unlike traditional pore size distribution (PSD) methods, CLD is particularly useful for 2D cross sections where direct PSD measurements are impractical. By analyzing chord lengths - linear segments that traverse pore spaces - it provides insight into pore connectivity, anisotropy, and heterogeneity.
Geodesic Tortuosity quantifies the complexity of transport pathways in porous materials by measuring the ratio of the shortest actual path through the medium to the straight-line distance. It provides insight into fluid flow, diffusion, and connectivity, helping to evaluate permeability and transport efficiency. Higher tortuosity is an indication of more tortuous pathways, which can hinder flow and diffusion.
PoroDict also includes two powerful GeoApps for automated porous materials analysis:
- The Compute Tortuosity GeoApp calculates the tortuosity of materials using several geometric, physical and mixed approaches as described in [1].
- The ASTM Calculation Factor GeoApp simulates the standard woven wire filter bubble point pressure test method as defined in ASTM E3278-21 [2].
GeoDict Online User Guide
References:
[1] L. Holzer, P. Marmet, M. Fingerle, A. Wiegmann, M. Neumann, V. Schmidt, Tortuosity and microstructure effects in porous media: classical theories, empirical data and modern method, 2023, https://doi.org/10.1007/978-3-031-30477-4
[2] “Standard Test Method for Bubble Point Pressure of Woven Wire Filter Cloth,” Astm.org, 2021. https://store.astm.org/e3278-21.html
Following modules are often used in combination with PoroDict:
| Image Processing and Image Analysis | ImportGeo-Vol | |||||
| Material Analysis | MatDict | GrainFind | FiberFind | |||
| Modeling & Design | FiberGeo | GrainGeo | WeaveGeo | FoamGeo | ||
| Simulation & Prediction | FlowDict | ElastoDict | SatuDict | DiffuDict | BatteryDict | FilterDict |
| Interfaces | MeshGeo |
Suitable modules depend on the concrete application.