Publications

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In this paper, we study, analyze, and validate some important zero-dimensional physics-based models for vanadium redox batch cell (VRBC) systems and formulate an adequate physics-based model that can predict the battery performance accurately. In the model formulation process, a systems approach to multiple parameters estimation has been conducted using VRBC systems at low C-rates (∼C/30). In this batch cell system, the effect of ions’ crossover through the membrane is dominant, and therefore, the capacity loss phenomena can be explicitly observed. Paradoxically, this means that using the batch system might be a better approach for identifying a more suitable model describing the effect of ions transport. Next, we propose an efficient systems approach, which enables to help understand the battery performance quickly by estimating all parameters of the battery system. Finally, open source codes, executable files, and experimental data are provided to enable people’s access to robust and accurate models and optimizers. In battery simulations, different models and optimizers describing the same systems produce different values of the estimated parameters. Providing an open access platform can accelerate the process to arrive at robust models and optimizers by continuous modification from the users’ side.

The performances of five commercial anion exchange membranes are compared in aqueous soluble organic redox flow batteries (RFBs) containing the TEMPO and methyl viologen (MV) redox pair. Capacities between RFBs with different membranes are found to vary by >50% of theoretical after 100 cycles. This capacity loss is attributed to crossover of TEMPO and MV across the membrane and is dominated by either diffusion, migration, or electroosmotic drag, depending on the membrane. Counterintuitively, the worst performing membranes display the lowest diffusion coefficients for TEMPO and MV, instead seeing high crossover fluxes due to electroosmotic drag. This trend is rationalized in terms of the ion exchange capacity and water content of these membranes. Decreasing these values in an effort to minimize diffusion of the redox-active species while the RFB rests can inadvertently exacerbate conditions for electroosmotic drag when theRFBoperates.Using fundamental membrane properties, it is demonstrated that the relative magnitude of crossover and capacity loss during RFB operation may be understood.

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Mathematical models of Redox Flow Batteries (RFBs) can be used to analyze cell performance, optimize battery operation, and control the energy storage system efficiently. Among many other models, physics-based electrochemical models are capable of predicting internal states of the battery, such as temperature, state-of-charge, and state-of-health. In the models, estimating parameters is an important step that can study, analyze, and validate the models using experimental data. A common practice is to determine these parameters either through conducting experiments or based on the information available in the literature. However, it is not easy to investigate all proper parameters for the models through this way, and there are occasions when important information, such as diffusion coefficients and rate constants of ions, has not been studied. Also, the parameters needed for modeling charge-discharge are not always available. In this paper, an efficient way to estimate parameters of physics-based redox battery models will be proposed. This paper also demonstrates that the proposed approach can study and analyze aspects of capacity loss/fade, kinetics, and transport phenomena of the RFB system.

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The energy density of nonaqueous redox flow batteries is often limited by the concentration of the redox active species soluble in solution. A possible route to increasing the this energy density is through the use of energy-dense solid materials such as polyoxometalates, LiFePO₄, or Li_xTi0₂. These solid materials can be contained in canisters through which an electrolyte with dissolved redox-active species is flowed. The redox potentials for the flowing species are chosen specifically such that they mediate the chemical reduction and oxidation of the solid components. This strategy is advantageous in that it allows for independent optimization of the flow electrolyte (e.g. for low viscosity, high charging rate) and the solid energy storing media (e.g. high energy density). This report summarizes results using a variety of redox active organic and metalorganic species to mediate the oxidation and reduction of polyoxometalate and Li-ion battery chemistries in a redox flow battery system.

A systematic approach is presented for increasing the concentration of redox-active species in electrolytes for nonaqueous redox flow batteries (RFBs). Starting with an ionic liquid consisting of a metal coordination cation (MetIL), ferrocene-containing ligands and iodide anions are substituted incrementally into the structure. While chemical structures can be drawn for molecules with 10 m redox-active electrons (RAE), practical limitations such as melting point and phase stability constrain the structures to 4.2 m RAE, a 2.3× improvement over the original MetIL. Dubbed “MetILs3,” these ionic liquids possess redox activity in the cation core, ligands, and anions. Throughout all compositions, infrared spectroscopy shows the ethanolamine-based ligands primarily coordinate to the Fe2+ core via hydroxyl groups. Calorimetry conveys a profound change in thermophysical properties, not only in melting temperature but also in suppression of a cold crystallization only observed in the original MetIL. Square wave voltammetry reveals redox processes characteristic of each molecular location. Testing a laboratory-scale RFB demonstrates Coulombic efficiencies >95% and increased voltage efficiencies due to more facile redox kinetics, effectively increasing capacity 4×. Application of this strategy to other chemistries, optimizing melting point and conductivity, can yield >10 m RAE, making nonaqueous RFB a viable technology for grid scale storage.

We seek to optimize Ionic liquids (ILs) for application to redox flow batteries. As part of this effort, we have developed a computational method for suggesting ILs with high conductivity and low viscosity. Since ILs consist of cation-anion pairs, we consider a method for treating ILs as pairs using product descriptors for QSPRs, a concept borrowed from the prediction of protein-protein interactions in bioinformatics. We demonstrate the method by predicting electrical conductivity, viscosity, and melting point on a dataset taken from the ILThermo database on June 18th, 2014. The dataset consists of 4,329 measurements taken from 165 ILs made up of 72 cations and 34 anions. We benchmark our QSPRs on the known values in the dataset then extend our predictions to screen all 2,448 possible cation-anion pairs in the dataset.

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We report a simple method to synthesize V 4+ (VO 2+ ) electrolytes as feedstock for all- vanadium redox flow batteries (RFB). By dissolving V 2 O 5 in aqueous HCl and H 2 SO 4 , subsequently adding glycerol as a reducing agent, we have demonstrated an inexpensive route for electrolyte synthesis to concentrations >2.5 M V 4+ (VO 2+ ). Electrochemical analysis and testing of laboratory scale RFB demonstrate improved thermal stability across a wider temperature range (-10-65 degC) for V 4+ (VO 2+ ) electrolytes in HCl compared to in H 2 SO 4 electrolytes.

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