OpenPNM: A Pore Network Modeling Package

Gostick, Jeff T.; Aghighi, Mahmoudreza; Hinebaugh, James; Tranter, Thomas G.; Hoeh, Michael A.; Day, Harold; Spellacy, Brennan; Sharqawy, Mostafa H.; Bazylak, Aimy; Burns, A. D.; Lehnert, Werner; Pütz, Andreas

doi:10.1109/mcse.2016.49

Cited by 300 publications

(189 citation statements)

References 36 publications

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“…In estimating the rest of the parameters, i.e., saturation, liquid-gas interfacial surface area and average Knudsen radius, information about connectivity is lost in the PSD model as compared to a pore network 53 or micro-scale simulation. 54 The pore geometry which might be important is idealized in all cases (including in micro-structures when a morphological image opening depth is used 53 ). Discrepancies between experimental data and PSD model predictions in Figure 4 and 5 might be due to the lack of consideration of the above features in the PSD model.…”

Section: Resultsmentioning

confidence: 99%

A Mixed Wettability Pore Size Distribution Based Mathematical Model for Analyzing Two-Phase Flow in Porous Electrodes

Zhou

Pütz

Secanell

2017

J. Electrochem. Soc.

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A multi-dimensional, non-isothermal, two-phase membrane electrode assembly (MEA) numerical model is developed where the micro-structure of the porous layers is characterized by a mixed wettability pore size distribution (PSD). The PSD model is used to predict local water saturation based on gas and liquid pressures, and can be used to study the effect of varying pore size and wettability. The MEA model accounts for gas transport via molecular and Knudsen diffusion, liquid water transport, sorbed water transport by back-diffusion, electro-and thermo-osmosis, and heat generation and transport. Multi-step kinetic models are used to predict anode and cathode electrochemical reactions. Local transport losses are accounted for using a local transport resistance. The PSD model is used to predict capillary pressure vs. saturation and saturation vs. relative liquid permeability curves based on PSDs from several GDLs obtained using mercury intrusion porosimetry. The PSD-based MEA model electrochemical performance predictions are also compared to experimental data from the literature. Results show that the numerical model is able to capture the performance changes associated with varying temperate and the introduction of a micro-porous layer. Improving the performance of polymer electrolyte fuel cells (PEFCs) at high current density is critical for reducing stack size, cost and weight in automobile applications. Water accumulation in the electrode however, limits fuel cell performance at high current densities. [1][2][3] In order to mitigate the excessive water buildup in the cell, which hinders mass transport, gas diffusion layer (GDL) and catalyst layer (CL) microstructures and wettabilities must be advanced to achieve sufficient water retention in the electrolyte, reject excess water in vapor form and alleviate complete flooding of the electrode. For example, by modifying the weight percentage (wt%) of the hydrophobic content in the GDL, Wang et al. 4 reported a 10%-20% increase in performance. To understand fuel cell behavior in the two-phase region and optimize the design of GDL and CL, a two-phase model which includes microstructural information of the porous layers is needed.Two approaches have commonly been used to study liquid water transport in fuel cells. The first approach involves the solution of a saturation equation obtained by replacing liquid pressure by saturation in Darcy's law. [5][6][7] In this approach the Levertt J-function is commonly used to relate saturation with capillary pressure. The Leverett J-function is however, an empirically measured curve for a given material and it is obtained from porous media structure analysis. Thus, it is difficult to optimize the structure of the porous layers using Leverett J-functions. The second approach, known as the multi-phase approach, involves solving mass and momentum equations for gas and liquid phases independently and then relating the capillary pressure to saturation using a closure equation based on micro-structural information such as a pore size dist...

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Section: Resultsmentioning

confidence: 99%

A Mixed Wettability Pore Size Distribution Based Mathematical Model for Analyzing Two-Phase Flow in Porous Electrodes

Zhou

Pütz

Secanell

2017

J. Electrochem. Soc.

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“…A pore network extraction algorithm developed by Gostick was used to identify the pores and the throats connecting the pores within the binarized image obtained from the tomography as described above. The transport properties are calculated using an open source pore network modeling package – OpenPNM . The pore size distribution is obtained directly as a result of this algorithm and is presented to demonstrate the difference in structure between the electrodes being studied.…”

Section: Methodsmentioning

confidence: 99%

Comparison of Electrospun Carbon−Carbon Composite and Commercial Felt for Their Activity and Electrolyte Utilization in Vanadium Redox Flow Batteries

et al. 2018

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A low cost highly active carbon−carbon composite fiber felt was produced by electrospinning a mixture of polyacrylonitrile and carbon black powder using poly acrylic acid as a binder for high carbon black loading. The newly designed high‐surface area electrode material showed promising results for use as electrode material for both the negative and positive half‐cell of vanadium redox flow batteries. Battery test results demonstrated promising performance for the electrospun carbon fibers at current densities below 60 mA cm−2, but were less active at higher values. The microstructure of the felt was characterized by X‐ray computed tomography to obtain the porous pathways, which facilitate electrolyte transport. The obtained results will help us to understand the role of porosity in the performance of the battery and to consequently improve the design of the carbon‐filled electrospun material.

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“…The following sections describe the type of information that is extracted, and briefly outlines how it is achieved. GETNET.py in the Supplemental Material [37] is PYTHON code that performs these steps and outputs the data in a format suitable for importing into OPENPNM [46]. It should be stressed that the following interpretation of pore and throat size information represents only the most general approach, and much more sophisticated analyses could be brought to bear [47,48].…”

Section: B Obtaining Pore Network Informationmentioning

confidence: 99%

“…Capillary pressure curves and permeability calculations were performed using OPENPNM, an open-source pore network modeling tool [46].…”

Section: Validationmentioning

confidence: 99%

Versatile and efficient pore network extraction method using marker-based watershed segmentation

2017

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Obtaining structural information from tomographic images of porous materials is a critical component of porous media research. Extracting pore networks is particularly valuable since it enables pore network modeling simulations which can be useful for a host of tasks from predicting transport properties to simulating performance of entire devices. This work reports an efficient algorithm for extracting networks using only standard image analysis techniques. The algorithm was applied to several standard porous materials ranging from sandstone to fibrous mats, and in all cases agreed very well with established or known values for pore and throat sizes, capillary pressure curves, and permeability. In the case of sandstone, the present algorithm was compared to the network obtained using the current state-of-the-art algorithm, and very good agreement was achieved. Most importantly, the network extracted from an image of fibrous media correctly predicted the anisotropic permeability tensor, demonstrating the critical ability to detect key structural features. The highly efficient algorithm allows extraction on fairly large images of 500 3 voxels in just over 200 s. The ability for one algorithm to match materials as varied as sandstone with 20% porosity and fibrous media with 75% porosity is a significant advancement. The source code for this algorithm is provided.

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OpenPNM: A Pore Network Modeling Package

Cited by 300 publications

References 36 publications

A Mixed Wettability Pore Size Distribution Based Mathematical Model for Analyzing Two-Phase Flow in Porous Electrodes

A Mixed Wettability Pore Size Distribution Based Mathematical Model for Analyzing Two-Phase Flow in Porous Electrodes

Comparison of Electrospun Carbon−Carbon Composite and Commercial Felt for Their Activity and Electrolyte Utilization in Vanadium Redox Flow Batteries

Versatile and efficient pore network extraction method using marker-based watershed segmentation

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