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Compressing porous carbon electrodes is a common approach to improve flow battery performance, but the resulting impact on electrode structure, fluid dynamics, and cell performance is not well understood. Herein, microtomographic imaging, load cell testing, and flow cell diagnostics are employed to characterize how compression-induced changes impact pressure drop, polarization, and mass-transfer scaling. Five different compressions are tested, spanning ranges typically used in literature, for AvCarb 1071 cloth (0%, 9%, 20%, 25%, 32%) and Freudenberg H23 paper (0%, 8%, 12%, 17%, 22%). It is found that the two electrode structures have distinct responses to compression, resulting in differing optimal conditions identified for each material; specifically, the Freudenberg H23 exhibits lower combined ohmic, charge-transfer, and mass-transport values at 8% compression, resulting in improved electrochemical performance across all compressive values, as compared to the optimal AvCarb 1071 compression (20%). Overall, Freudenberg H23 exhibits a greater sensitivity to compression with peak electrochemical activity correlating with increased permeability, whereas AvCarb 1071 is insensitive to compressive loads but produces lower electrochemical performance. Herein, the trade-offs of mechanical robustness on fluid-dynamic and electrochemical performance between the two electrodes are demonstrated by the aforementioned findings, suggesting each could be used for specific operating environments.

Redox flow batteries are a nascent, yet promising, energy storage technology for which widespread deployment is hampered by technical and economic challenges. A performance-determining component in the reactor, present-day electrodes are often borrowed from adjacent electrochemical technologies rather than specifically designed for use in flow batteries. A lack of structural diversity in commercial offerings, coupled with the time constraints of wet-lab experiments, render broad electrode screening infeasible without a modeling complement. Herein, an experimentally validated model of a vanadium redox flow cell is used to generate polarization data for electrodes with different macrohomogeneous properties (thickness, porosity, volumetric surface area, and kinetic rate constant). Using these data sets, we then build and train a neural network with minimal average root-mean squared testing error (17.9 ± 1.8 mA cm−2) to compute individual parameter sweeps along the cell polarization curve. Finally, we employ a genetic algorithm with the neural network to identify electrode property values for improving cell power density. While the developed framework does not supplant experimentation, it is generalizable to different redox chemistries and may inform future electrode design strategies.

High-dimensional models typically require a large computational overhead for multiphysics applications, which hamper their use for broad-sweeping domain interrogation. Herein, we develop a modeling framework to capture the through-plane fluid dynamic response of electrodes and flow fields in a redox flow cell, generating a computationally inexpensive two-dimensional (2D) model. We leverage a depth-averaging approach that also accounts for variations in out-of-plane fluid motion and departures from Darcy's law that arise from averaging across three-dimensions (3D). Our resulting depth-averaged 2D model successfully predicts the fluid dynamic response of arbitrary in-plane flow field geometries, with discrepancies of <5% for both maximum velocity and pressure drop. This corresponds to reduced computational expense, as compared to 3D representations (<1% of duration and 10% of RAM usage), providing a platform to screen and optimize a diverse set of cell geometries.

© 2020 A method for the preparation of electrospun with fibers possessing a ribbon-like cross-sectional shape was developed. These materials could prove beneficial as flow-through electrodes, since ribbons provide a higher surface-to-volume ratio compared to fibers, thereby providing higher reactive surface area at a given porosity. Fabrication of these materials was accomplished by electrospinning a coaxial fiber with a polystyrene core and polyacrylonitrile shell, followed by leaching of the core material leading to the collapse of the shell into a flat ribbon. The surviving shell was then carbonized to make an electrically conductive and electrochemically reactive fibrous structure. Analysis by x-ray computed tomography showed that ribbons of approximately 400 nm × 800 nm were produced, and experimental characterization revealed that they did indeed offer higher volumetric surface area than previously reported electrospun cylindrical fiber electrodes. The electrodes were characterized for various physical and transport properties and compared to commercial Freudenberg H23 carbon paper in terms of performance in a vanadium redox flow battery. The ribbon-based electrode had better performance and higher power density than commercial Freudenberg H23 electrode in the activation region, though suffered early onset of mass transfer limitations.

© The Author(s) 2017. Engineering the electrochemical reactor of a redox flow battery (RFB) is critical to delivering sufficiently high power densities, as to achieve cost-effective, grid-scale energy storage. Cell-level resistive losses reduce RFB power density and originate from ohmic, kinetic, or mass transfer limitations. Mass transfer losses affect all RFBs and are controlled by the active species concentration, state-of-charge, electrode morphology, flow rate, electrolyte properties, and flow field design. The relationship among flow rate, flow field, and cell performance has been qualitatively investigated in prior experimental studies, but mass transfer coefficients are rarely systematically quantified. To this end, we develop a model describing one-dimensional porous electrode polarization, reducing the mathematical form to just two dimensionless parameters. We then engage a single electrolyte flow cell study, with a model iron chloride electrolyte, to experimentally measure cell polarization as a function of flow field and flow rate. The polarization model is then fit to the experimental data, extracting mass transfer coefficients for four flow fields, three active species concentrations, and five flow rates. The relationships among mass transfer coefficient, flow field, and electrolyte velocity inform engineering design choices for minimizing mass transfer resistance and offer mechanistic insight into transport phenomena in fibrous electrodes.

Abstract Redox flow batteries (RFBs) are an emerging electrochemical technology suitable for energy-intensive grid storage, but further cost reductions are needed for broad deployment. Overcoming cell performance limitations through improvements in the design and engineering of constituent components represent a promising pathway to lower system costs. Of particular relevance, but limited in study, are the porous carbon electrodes whose surface composition and microstructure impact multiple aspects of cell behavior. Here, we systematically investigate woven carbon cloth electrodes based on identical carbon fibers but arranged into different weave patterns (plain, 8-harness satin, 2 × 2 basket) of different thicknesses to identify structure–function relations and generalizable descriptors. We first evaluate the physical properties of the electrodes using a suite of analytical methods to quantify structural characteristics, accessible surface area, and permeability. We then study the electrochemical performance in a diagnostic flow cell configuration to elucidate resistive losses through polarization and impedance analysis and to estimate mass transfer coefficients through limiting current measurements. Finally, we combine these findings to develop power law relations between relevant dimensional and dimensionless quantities and to calculate extensive mass transfer coefficients. These studies reveal nuanced relationships between the physical morphology of the electrode and its electrochemical and hydraulic performance and suggest that the plain weave pattern offers the best combination of these attributes. More generally, this study provides physical data and experimental insights that support the development of purpose-built electrodes using a woven materials platform.

© 2020 The Royal Society of Chemistry. In this article, the different approaches reported in the literature for modelling electrode processes in redox flow batteries (RFBs) are reviewed. RFB models vary widely in terms of computational complexity, research scalability and accuracy of predictions. Development of RFB models have been quite slow in the past, but in recent years researchers have reported on a range of modelling approaches for RFB system optimisation. Flow and transport processes, and their influence on electron transfer kinetics, play an important role in the performance of RFBs. Macro-scale modelling, typically based on a continuum approach for porous electrode modelling, have been used to investigate current distribution, to optimise cell design and to support techno-economic analyses. Microscale models have also been developed to investigate the transport properties within porous electrode materials. These microscale models exploit experimental tomographic techniques to characterise three-dimensional structures of different electrode materials. New insights into the effect of the electrode structure on transport processes are being provided from these new approaches. Modelling flow, transport, electrical and electrochemical processes within the electrode structure is a developing area of research, and there are significant variations in the model requirements for different redox systems, in particular for multiphase chemistries (gas-liquid, solid-liquid, etc.) and for aqueous and non-aqueous solvents. Further development is essential to better understand the kinetic and mass transport phenomena in the porous electrodes, and multiscale approaches are also needed to enable optimisation across the relevent length scales.

The vanadium redox flow battery (VRFB) is a promising energy storage technology for stationary applications (e.g., renewables integration) that offers a pathway to cost-effectiveness through independent scaling of power and energy as well as longevity. Many current research efforts are focused on improving battery performance through electrode modifications, but high-throughput, laboratory-scale testing can be time- and material-intensive. Advances in multiphysics-based numerical modeling and data-driven parameter identification afford a computational platform to expand the design space by rapidly screening a diverse array of electrode configurations. Herein, a 3D VRFB model is first developed and validated against experimental results. Subsequently, a new 2D model is composed, yielding a computationally-light simulation framework, which is used to span bounded values of the electrode thickness, porosity, volumetric area, fiber diameter, and kinetic rate constant across six cell polarization voltages. This 2D model generates a dataset of 7350 electrode property combinations for each cell voltage, which is used to evaluate the effect of these structural properties on the pressure drop and current density. These structure-performance relationships are further quantified using Kendall τ rank correlation coefficients to highlight the dependence of cell performance on bulk electrode morphology and to identify improved property sets. This statistical framework may serve as a general guideline for parameter identification for more advanced electrode designs and redox flow battery stacks.

Redox flow batteries (RFBs) are an emerging electrochemical technology suitable for energy-intensive grid storage, but further cost reductions are needed for broad deployment. Overcoming cell performance limitations through improvements in the design and engineering of constituent components represent a promising pathway to lower system costs. Of particular relevance, but limited in study, are the porous carbon electrodes whose surface composition and microstructure impact multiple aspects of cell behavior. Here, we systematically investigate woven carbon cloth electrodes based on identical carbon fibers but arranged into different weave patterns (plain, 8-harness satin, 2 × 2 basket) of different thicknesses to identify structure–function relations and generalizable descriptors. We first evaluate the physical properties of the electrodes using a suite of analytical methods to quantify structural characteristics, accessible surface area, and permeability. We then study the electrochemical performance in a diagnostic flow cell configuration to elucidate resistive losses through polarization and impedance analysis and to estimate mass transfer coefficients through limiting current measurements. Finally, we combine these findings to develop power law relations between relevant dimensional and dimensionless quantities and to calculate extensive mass transfer coefficients. These studies reveal nuanced relationships between the physical morphology of the electrode and its electrochemical and hydraulic performance and suggest that the plain weave pattern offers the best combination of these attributes. More generally, this study provides physical data and experimental insights that support the development of purpose-built electrodes using a woven materials platform.