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The redox flow battery is a promising energy storage technology for managing the inherent uncertainty of renewable energy sources. At present, however, they are too expensive and thus economically unattractive. Optimizing flow batteries is thus an active area of research, with the aim of reducing cost by maximizing performance. This work addresses microstructural electrode optimizations by providing a modeling framework based on pore-networks to study the multiphysics involved in a flow battery, with a specific focus on pore-scale structure and its impact on transport processes. The proposed pore network approach was extremely cheap in computation cost (compared to direct numerical simulation) and therefore was used for parametric sweeps to search for optimum electrode structures in a reasonable time. It was found that that increasing porosity generally helps performance by increasing the permeability and flow rate at a given pressure drop, despite reducing reactive surface area per unit volume. As a more nuanced structural study, it was found that aligning fibers in the direction of flow helps performance by increasing permeability but showed diminishing returns beyond slight alignment. The proposed model was demonstrated in the context of a hydrogen bromine flow battery but could be applied to any system of interest.) unless CC License in place (see abstract). ecsdl.org/site/terms_use address. Redistribution subject to ECS terms of use (see 128.41.35.179 Downloaded on 2019-07-09 to IP A2122 Journal of The Electrochemical Society, 166 (10) A2121-A2130 (2019) ) unless CC License in place (see abstract). ecsdl.org/site/terms_use address. Redistribution subject to ECS terms of use (see 128.41.35.179 Downloaded on 2019-07-09 to IP ) unless CC License in place (see abstract). ecsdl.org/site/terms_use address. Redistribution subject to ECS terms of use (see 128.41.35.179 Downloaded on 2019-07-09 to IP

A general framework based on pore network modeling is presented for simulation of reactive transport in a porous catalyst with a hierarchy of porosity. The proposed framework is demonstrated in the context of steady state reactive transport inside a nanoporous catalyst particle interlaced with macropores that result from the use of pore-formers. A comprehensive parametric study was performed to examine the influence of structural features namely macroporosity, pore size ratio, and the particle size, as well as transport properties namely pore Damköhler number, on the net reaction rate inside the particle. The results showed that depending on the Damköhler number, increasing the macroporosity does not necessarily improve the catalytic activity of the particle. It was also shown that particles with lower pore size ratios are more kinetically active. The key finding of this work was to demonstrate and quantify how microstructure influences the reactivity of hierarchical porous catalyst particles.

A pore network model has been applied to a both sides of a fuel cell membrane electrode assembly. The model includes gas transport in the gas diffusion layers and catalyst layers, proton transport in the catalyst layers and membrane, and percolation of liquid water. This paper presents an iterative algorithm to simulate a steady state isothermal cell with a 3D pore network model for constant voltage boundary condition. The proposed algorithm provides a simple method to couple the results of the anode and the cathode sides by iteratively solving the uncoupled equations of the transport processes. It was found that local water blockages at the GDL/CL interface not only affect concentration polarization, but also might change ohmic polarization of the cell. Depending on the liquid water configuration in the porous electrodes, the protons generated in the anode need to travel longer paths to reach the active sites of the cathode; consequently, the IR loss will be increased in the presence of liquid water. This finding highlights the strength of pore network models which resolve discrete water blockages in the electrodes. Polymer electrolyte membrane fuel cells are one of the key technologies required to realize a sustainable energy economy because they provide energy storage. A typical PEMFC is a stack of electrochemical cells, and the heart of each is a sandwich of several porous layers around a thin polymer electrolyte membrane, referred to as a membrane-electrode assembly (MEA). In the typical arrangement each side consists of a gas diffusion layer (GDL), and a catalyst layer (CL). The GDL is usually a carbon-fiber based paper and acts as a spacer to allow gaseous reactants to reach regions of the catalyst layer under the flow field ribs, and as a bridge to allow electron access to catalyst sites over the flow field channels. The CL is composed of a mixture of ionomer such as Nafion and carbon-supported platinum catalyst particles, and is adhered to the surface of the membrane as a porous coating around 10-20 μm thick. The ionomer phase in the CL allows protons to reach the catalyst sites, while the carbon particles provide pathways for electrons, and the porosity allows transport of gaseous reactants (oxygen and hydrogen) and product (water). Under some conditions the cathode produces liquid water, which can accumulate in the pore spaces, blocking the access to the reaction sites. Liquid water can also be found on the anode side, for instance if temperature fluctuations occur since the hydrogen is humidified. Understanding the role of liquid water and its impact on fuel cell operation has been a longstanding challenge for the industry.1-3 Complete water removal from the cell is not an option because the currently used membrane materials must be hydrated to function.When electrical current is drawn, several sources of voltage loss are incurred due to the inefficiencies of current generation and transport processes. Voltage losses can be broken into three categories: activation polarization η act , ohmic polarizat...

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An open source pore network modeling framework has been developed. Written in Python with Scipy, this framework was designed with flexibility in mind so networks of any topology and dimensionality can be represented. The package includes numerous network generation and manipulation functions, as well as a variety of physical simulations like invasion percolation and diffusivity. A graphical user interface is also presented.

Pore network modeling was applied to a full PEM membrane electrode assembly sandwich. This model included liquid water percolation and gas transport in the gas diffusion and catalyst layers, and ionic transport in the catalyst layers and membrane. The ability of pore network models to resolve discrete water clusters played a key role in the electrochemical simulations. It was found that local water blockages not only cause concentration polarization, but also that the protons generated in the anode must travel longer paths to reach an active site on the cathode not masked by a discrete water. Consequently, the iR polarization was actually increased in the presence of liquid water. This behavior is not typically observed in continuum models since they do not treat water treated as explicit blockages and hence do not see the increased transport lengths resulting from the localized production and consumption of protons.

Polymer electrolyte membrane fuel cells are one of the best candidates to replace internal combustion engines. The key requirement for commercial success of PEMFCs is to demonstrate optimal performance at high current density. However, because of liquid water generation, the power density is reduced by mass transport limitations at the cathode. Accordingly, precise modeling of mass transfer inside the porous structure of fuel cell electrodes is crucial. Ordinary diffusion is the most commonly considered diffusion model for PEMFC in the literature. In most of these studies, the gas transport is considered as a binary system of oxygen diffusing through nitrogen (and sometimes water vapor). However, realistic simulation of fuel cell operation requires simultaneous modeling of both oxygen and water vapor transport in a stagnant film of nitrogen. In multicomponent diffusion, the fluxes of all of the species are important to consider since they might affect the diffusive transport of the other species. A pore network modeling has been developed using the Stefan-Maxwell approach, to simulate the diffusion of gases mixtures inside fuel cell electrodes. Pore network models (PNM) provide an alternative approach for the continuum modeling in porous media. Rather than using finite element models of transport in the pore space, PNMs use pore-to-pore nodal balances to model species transport. They also enable the structural properties of the porous material to be incorporated directly into the model, rather than through constitutive relationships. The SM model is notoriously difficult to solve numerically for pore networks, but some simplifications and solution schemes have been proposed in the literature [1,2] based on decomposing Jacobian matrix of the equations, which are less computationally expensive. In this work, these methods have been evaluated to determine an appropriate solution algorithm for the pore network. These advantages come at the expense of rigorous transport phenomena calculations since some simplification to the SM model are made. References 1. Wood, J., L. Gladden, and F. Keil, Chemical Engineering Science, 2002. 57(15): p. 3047-3059. 2. Rieckmann, C. and F.J. Keil, 1997. 36(8): p. 3275-3281. Acknowledgements This work was funded by AFCC and the NSERC CRD program.