Understanding reactive mass transport in redox flow reactors is key to improving performance, yet conventional characterization techniques often rely on cell-averaged metrics and fail to resolve local transport phenomena. In this study, we employ operando neutron radiography to visualize concentration distributions in redox flow cells with non-aqueous electrolytes, leveraging the high attenuation of hydrogen-containing organic molecules and boron-containing supporting ions. Symmetric flow cell experiments were conducted with three electrode types (paper, cloth, and a hierarchical porous electrode fabricated via non-solvent induced phase separation), and two flow field designs (parallel and interdigitated). We find that for kinetically facile electrolytes with low ionic conductivity and with parallel flow fields, electrodes with large pores in the though-plane direction (i.e., carbon cloth) augment the current output. Additionally, interdigitated flow fields sustain higher currents than parallel flow fields at a fixed potential and flow rate due to enhanced convective transport. Despite significant differences in macroscopic performance among the studied materials, the concentration profiles within the cell showed only minor variations within the studied operating conditions and imaging configuration. The cloth electrode and interdigitated flow field exhibited slightly more uniform concentration profiles across the electrode thickness compared to the paper electrode with the parallel flow field. In contrast, the phase-separation electrode displayed more steep concentration profiles and a stronger dependency on polarity reversal. Neutron radiography further uncovered critical secondary effects, including salt precipitation and flow field underutilization. These findings highlight the potential of operando imaging to inform the design and operation of electrochemical reactors for a range of technologies.

Carbon-based porous electrodes are commonly employed in electrochemical technologies as they provide a high surface area for reactions, an open structure for fluid transport, and enable compact reactor architectures. In electrochemical cells that sustain liquid electrolytes (e.g., redox flow batteries, CO₂ electrolyzers, capacitive deionization), the nature of the interaction between the three phases – solid, liquid and gas – determines the accessible surface area for reactions, which fundamentally determines device performance. Thus, it is critical to understand the correlation between the electrolyte infiltration in the porous electrode and the resulting accessible surface area in realistic reactor architectures. To tackle this question, here we simultaneously perform neutron radiography with electrochemical measurements to correlate macroscopic electrode saturation/wetting with accessible surface area. We find that for untreated electrodes featuring neutral wettability with water, the electrode area remains underutilized even at elevated flow rates, both for interdigitated and parallel flow fields. Conversely, increasing the electrode hydrophilicity results in an order-of-magnitude increase in accessible surface area at comparable electrode saturation, and is less influenced by the electrolyte flow rate. Ultimately, we reveal useful correlations between reactor architectures and electrode utilization and provide a method that is broadly applicable to flow electrochemical reactors.

Advanced electrochemical systems, such as redox flow batteries, rely on porous electrodes, which determine the system performance and costs. Conventional porous electrodes currently used in convection-enhanced technologies are fibrous carbonaceous materials developed for low-temperature fuel cells; as such, their microstructure and surface chemistry are not suited for redox flow batteries. Thus, there is a need for targeted synthesis and engineering of porous electrodes with tailored properties to meet the requirements of liquid-phase electrochemistry. Specifically, the three-dimensional structure of the electrode is critical as it determines the available surface area for electrochemical reactions, electrolyte transport, fluid pressure drop, and electronic and thermal conductivity. However, the role of the electrode microstructure and, consequently, the optimal design for specific flow battery chemistries remains unknown. Hence, a multi-variable optimization problem at different length scales must be solved with highly coupled transport phenomena and kinetics. In this doctoral dissertation, a novel framework is developed to design and synthesize electrode structures from the bottom up, tailored to emerging electrochemical technologies with a focus on redox flow batteries. In this thesis, fundamental structure-function-performance relationships are elucidated by imaging and modeling commercial electrodes, which are used to design hierarchically organized porous electrodes through topology optimization and to manufacture model grid structures with 3D printing.

In Chapter 1, redox flow batteries are introduced as a technology that is promising for large-scale energy storage to bridge the temporal and geographical gaps between energy demand and supply. Thereafter, the transport phenomena and cell overpotentials in redox flow batteries are discussed in detail. Furthermore, experimental diagnostics, electrode manufacturing, multiphysics simulations, and computational electrode optimization strategies are introduced to aid the theoretical understanding and design of advanced electrode structures, as the empirical design process alone is time- and resource-intensive, limiting exploration of the wider design space. Finally, the scope of the doctoral dissertation is presented based on four objectives.

In Chapter 2, the developed pore network model is explained, which is a simulation framework for flow batteries that is microstructure-informed and electrolyte-agnostic, constructed using an open-access platform (OpenPNM), and validated with experimental data. The model utilizes a network-in-series approach to account for species depletion over the entire length of the electrode, enabling the simulation of large electrode sizes. To validate the robustness of the modeling framework, single-electrolyte flow cell experiments were performed for two distinct electrolytes – aqueous and non-aqueous – and two types of porous electrodes – carbon paper and -cloth, extracted using X-ray computed tomography and converted into a pore network. The electrochemical model solves the electrolyte fluid transport and couples both half-cells by iteratively solving the species and charge transport at a low computational cost. The electrochemical performance of the non-aqueous electrolyte is well captured by the model without fitting parameters, allowing rapid benchmarking of porous electrode microstructures. For the aqueous electrolyte, it is found that incomplete wetting of the electrode results in overprediction of the electrochemical performance. Finally, a parametric sweep is discussed for the identification of operation envelopes.

In Chapter 3, the pore network model of Chapter 2 is used, together with experimental techniques, to investigate the effect of stacking electrode layers for two prevailing commercial electrodes and flow fields. To this end, the pore network model is extended to simulate an interdigitated flow field design, and thickness-structure-performance relationships are obtained for specific electrode-flow field configurations. By stacking commercial electrodes, for example, two carbon paper electrodes with a flow-through configuration, the overall reactor efficiency can be enhanced. Furthermore, both the electrochemical power and pressure drop are improved, providing a facile strategy to enhance the performance of flow batteries.

In Chapters 4 and 5, a genetic algorithm is developed and coupled with the pore network model of Chapter 2 for the bottom-up design of electrode structures. Using this approach, the electrode microstructure evolves driven by a fitness function that minimizes the pumping power and maximizes the electrochemical power, requiring only the electrolyte chemistry, initial electrode morphology, and flow field geometry as inputs. Thus, making it a versatile framework that can be applied to other electrochemical systems. In Chapter 4, the principle of the genetic algorithm is introduced, where a flow-through cubic lattice structure with fixed pore positions is analyzed and shows significant improvement in the fitness function over 1000 generations. The evolution results in a structure with a bimodal pore size distribution containing longitudinal electrolyte flow pathways of large pores, significantly reducing the pumping requirements. Additionally, an increase in surface area at the membrane-electrode interface is found, resulting in an enhancement of the electrochemical performance.

In Chapter 5, the genetic algorithm is extended to allow for more evolutionary freedom during the optimization process by evolving structures beyond fixed flow-through cubic lattice designs. To this end, pore merging and splitting are incorporated to allow larger geometrical flexibility. In addition, the optimization of complex structures is investigated by the implementation of Voronoi networks and X-ray tomography extracted off-the-shelf fibrous electrodes as starting networks. Subsequently, the effect of operational conditions is analyzed by evaluating two chemistries and two prevailing flow field geometries. Furthermore, optimization definitions (fitness function and geometrical definitions) are elaborated upon to inform about their importance and to show the flexibility of the algorithm.

In Chapter 6, a new neutron radiography approach is introduced to quantify concentration distributions in operando redox flow cells, providing a new diagnostic tool to better understand reactive transport phenomena in electrochemical reactors. The presented approach is developed for a non-aqueous model redox system where the attenuation comes from the hydrogen or boron atoms that compose redox active molecules or supporting ions in non-aqueous electrolytes. Concentration profiles are resolved across the electrode thickness by employing in-plane imaging and are correlated to the cell performance with polarization measurements under various operating conditions. Two neutron imaging methods are used, where first the combined attenuation of the active species and supporting salt is examined over the electrode thickness. Thereafter, a time-of-flight neutron imaging approach is used to analyze deconvoluted active species and supporting ion transport over time. With this approach, the transport of species in the reactor under a voltage bias is revealed, gaining insights into reactive transport phenomena within an operating flow cell.

In Chapter 7, the neutron radiography approach of Chapter 6 is utilized to study local transport properties and concentration distributions in the porous electrode for three distinct electrode structures and with two flow field designs. By tracking the cumulative active species movement, it is found that, for electrolytes with facile kinetics and low ionic conductivity, an electrode structure with a bimodal pore size distribution with large through-plane voids is favorable combined with parallel flow fields because of the high through-plane hydraulic conductance and effective diffusivity, enhancing the current output. Comparably, interdigitated flow fields feature higher reaction rates and current output compared to parallel designs because of forced convection. Moreover, neutron radiography is proven useful in the detection of system secondary phenomena including salt precipitation and underutilization of flow field channels.

In Chapter 8, the manufacturing of porous electrodes using 3D printing is presented. Model grid structures were manufactured with stereolithography followed by carbonization to tune the physicochemical properties of electrodes. A suite of microscopy, tomography, spectroscopy, fluid dynamics, and electrochemical diagnostics was employed to evaluate the thermal behavior, manufacturing fidelity, and fluid and mass transport performance of ordered lattice structures in non-aqueous redox flow cells. The influence of the pillar geometry, printing orientation regarding the printing platform, and flow field design on the electrode performance is investigated. It is found that although commercial electrodes feature a greater internal surface area and therefore better performance, the area-normalized mass transfer coefficient is improved and the pressure drop is reduced by utilizing 3D-printed electrodes.

Finally, the main findings of this work are summarized in Chapter 9, and future research directions to accelerate and broaden the design and fabrication processes of advanced electrode structures are provided.

Electrochemical flow reactors are increasingly relevant platforms in emerging sustainable energy conversion and storage technologies. As a prominent example, redox flow batteries, a well-suited technology for large energy storage if the costs can be significantly reduced, leverage electrochemical reactors as power converting units. Within the reactor, the flow field geometry determines the electrolyte pumping power required, mass transport rates, and overall cell performance. However, current designs are inspired by fuel cell technologies but have not been engineered for redox flow battery applications, where liquid-phase electrochemistry is sustained. Here, we leverage stereolithography 3D printing to manufacture lung-inspired flow field geometries and compare their performance to conventional flow field designs. A versatile two-step process based on stereolithography 3D printing followed by a coating procedure to form a conductive structure is developed to manufacture lung-inspired flow field geometries. We employ a suite of fluid dynamics, electrochemical diagnostics, and finite element simulations to correlate the flow field geometry with performance in symmetric flow cells. We find that the lung-inspired structural pattern homogenizes the reactant distribution throughout the porous electrode and improves the electrolyte accessibility to the electrode reaction area. In addition, the results reveal that these novel flow field geometries can outperform conventional interdigitated flow field designs, as these patterns exhibit a more favorable balance of electrical and pumping power, achieving superior current densities at lower pressure loss. Although at its nascent stage, additive manufacturing offers a versatile design space for manufacturing engineered flow field geometries for advanced flow reactors in emerging electrochemical energy storage technologies.

The microstructure of porous electrodes determines multiple performance-defining properties, such as the available reactive surface area, mass transfer rates, and hydraulic resistance. Thus, optimizing the electrode architecture is a powerful approach to enhance the performance and cost-competitiveness of electrochemical technologies. To expand our current arsenal of electrode materials, we need to build predictive frameworks that can screen a large geometrical design space while being physically representative. Here, we present a novel approach for the optimization of porous electrode microstructures from the bottom-up that couples a genetic algorithm with a previously validated electrochemical pore network model. In this first demonstration, we focus on optimizing redox flow battery electrodes. The genetic algorithm manipulates the pore and throat size distributions of an artificially generated microstructure with fixed pore positions by selecting the best-performing networks, based on the hydraulic and electrochemical performance computed by the model. For the studied VO²⁺/VO₂⁺ electrolyte, we find an increase in the fitness of 75 % compared to the initial configuration by minimizing the pumping power and maximizing the electrochemical power of the system. The algorithm generates structures with improved fluid distribution through the formation of a bimodal pore size distribution containing preferential longitudinal flow pathways, resulting in a decrease of 73 % for the required pumping power. Furthermore, the optimization yielded an 47 % increase in surface area resulting in an electrochemical performance improvement of 42 %. Our results show the potential of using genetic algorithms combined with pore network models to optimize porous electrode microstructures for a wide range of electrolyte composition and operation conditions.

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.

Förster resonance energy transfer (FRET) is important, not only in the fields of biology and biophysics but also in optoelectronics and light guiding systems. Different matrixes are being investigated that facilitate FRET, including zeolites and metal–organic frameworks. In this work, a matrix for FRET generation is proposed: nanoporous liquid crystal networks. These liquid crystal networks can be easily processed and can align dichroic fluorescent dyes. A base treatment can create nanopores in the network, which are then able to absorb a second fluorescent dye in an aqueous phase while still retaining good alignment. Using lifetime measurements, we provide proof that even in this nonoptimized system, around 70% of the energy was transferred via the FRET mechanism from one dye to the other. Liquid crystal networks have many advantages over current matrixes as they are easy to fabricate as well as flexible and could be modified to selectively and reversely absorb dyes, allowing many applications.