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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗
DOE OSTI2024

Physics-Guided Continual Learning for Predicting Emerging Aqueous Organic Redox Flow Battery Material Performance

Aqueous organic redox flow batteries (AORFBs) have gained popularity in renewable energy storage due to their low cost, environmental friendliness and scalability. The rapid discovery of aqueous soluble organic (ASO) redox-active materials necessitates efficient machine learning surrogates for predicting battery performance. The physics-guided continual learning (PGCL) method proposed in this study can incrementally learn data from new ASO electrolytes while addressing catastrophic forgetting issues in conventional machine learning. Using a AORFB database with a thousand potential materials generated by a 780 $\text{cm}^2$ interdigitated cell model, PGCL incorporates AORFB physics to optimize the continual learning task formation and training strategies to retain previously learned battery material knowledge. Finally, the trained PGCL demonstrates its capability in assessing emerging ASO materials within the established parameter space when evaluated with the dihydroxyphenazine isomers.

25 ENERGY STORAGE↗
DOE OSTI2020

Electrolyte Lifetime in Aqueous Organic Redox Flow Batteries: A Critical Review

Aqueous organic redox flow batteries (RFBs) could enable widespread integration of renewable energy, but only if costs are sufficiently low. Because the levelized cost of storage for an RFB is a function of electrolyte lifetime, understanding and improving the chemical stability of active reactants in RFBs is a critical research challenge. We review known or hypothesized molecular decomposition mechanisms for all five classes of aqueous redox-active organics and organometallics for which cycling lifetime results have been reported: quinones, viologens, aza-aromatics, iron coordination complexes, and nitroxide radicals. We collect, analyze, and compare capacity fade rates from all aqueous organic electrolytes that have been utilized in the capacity-limiting side of flow or hybrid flow/nonflow cells, noting also their redox potentials and demonstrated concentrations of transferrable electrons. We categorize capacity fade rates as being “high” (>1%/day), “moderate” (0.1–1%/day), “low” (0.02–0.1%/day), and “extremely low” (≤0.02%/day) and discuss the degree to which the fade rates have been linked to decomposition mechanisms. Capacity fade is observed to be time-denominated rather than cycle-denominated, with a temporal rate that can depend on molecular concentrations and electrolyte state of charge through, e.g., bimolecular decomposition mechanisms. We then review measurement methods for capacity fade rate and find that simple galvanostatic charge–discharge cycling is inadequate for assessing capacity fade when fade rates are low or extremely low and recommend refining methods to include potential holds for accurately assessing molecular lifetimes under such circumstances. We consider separately symmetric cell cycling results, the interpretation of which is simplified by the absence of a different counter-electrolyte. We point out the chemistries with low or extremely low established fade rates that also exhibit open circuit potentials of 1.0 V or higher and transferrable electron concentrations of 1.0 M or higher, which are promising performance characteristics for RFB commercialization. We indicate important directions for future research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

In situ electrochemical recomposition of decomposed redox-active species in aqueous organic flow batteries

Aqueous organic redox flow batteries (AORFBs) offer a safe and potentially inexpensive solution to the problem of storing massive amounts of electricity produced from intermittent renewables. However, molecular decomposition is the major barrier preventing AORFBs from being commercialized. Structural modifications can improve molecular stability at the expense of increased synthetic cost and molecular weight. Utilizing 2,6-dihydroxy-anthraquinone (DHAQ), without further structural modification, we demonstrate that electrochemical regeneration could be a viable route to achieve low-cost, long-lifetime AORFBs. In situ (online) NMR and EPR and complementary electrochemical analyses reveal that decomposition compounds i.e., 2,6-dihydroxy-anthrone (DHA) and its tautomer, 2,6-dihydroxy-anthranol (DHAL), can be converted back to DHAQ in two steps: first DHA(L) 2- are oxidized to the dimer (DHA) 2 4- at - 0.32 V vs. SHE by one-electron transfer; subsequently, the (DHA) 2 4- is oxidized to DHAQ 2- at +0.57 V vs. SHE by three-electron transfer. Electrochemical regeneration rejuvenates not only DHAQ 2- , but also the positive electrolyte – rebalancing the states of charge of both electrolytes without introducing extra ions. We demonstrate the repeated capacity recovery with DHAQ | potassium ferro-/ferricyanide flow battery in basic conditions, and show the approach is also effective for anthraquinone-2,7-disulfonate in acid. Electrochemical regeneration strategies may extend the useful lifetime of many water-soluble organic molecules with anthraquinone core structures in electrochemical cells.

25 ENERGY STORAGE↗
DOE OSTI2022

Characterization of Electrochemical Behavior for Aqueous Organic Redox Flow Batteries

Use of aqueous redox flow batteries with organic redox-active materials holds great promise for large-scale and sustainable energy storage. The development of low-cost, highly efficient aqueous redox flow batteries lies in a comprehensive understanding of the electrochemical behaviors of redox-active compounds. In this work, an alkaline redox battery with organic dihydroxyphenazine sulfonate (DHPS) anolyte and ferro-/ferricyanide (Fe(CN) 6 ) catholyte is investigated as a typical example of aqueous redox flow batteries using organic redox-active materials. The electrochemical kinetics of DHPS and Fe(CN) 6 are separately characterized using the symmetrical cell design. The resistance components are calculated directly from the experimental measurement. The key kinetic parameters are extracted and compared for DHPS and Fe(CN) 6 electrolytes. The extracted parameters are validated with symmetrical and full flow cell simulations at different operating conditions. Key parameters and internal loss are also compared with all-vanadium redox flow batteries, representing current state of the art. In addition, our extracted key parameters from a symmetrical flow cell are compared with the measured key parameters by cyclic voltammetry, a widely deployed electroanalytical technique. The cell performance prediction of DHPS anolyte on a 780 cm 2 interdigitated cell is made and found the power density is peaked at 475 mW cm -2 at our measurement condition.

25 ENERGY STORAGE↗
DOE OSTI2021

A Stable, Low Permeable TEMPO Catholyte for Aqueous Total Organic Redox Flow Batteries

We report aqueous organic redox flow batteries (AORFBs) are highly attractive for large-scale energy storage because of their nonflammability, low cost, and sustainability. (2,2,6,6-Tetramethylpiperidin-1-yl)oxyl (TEMPO) derivatives, a class of redox active molecules bearing air-stable free nitroxyl radicals and high redox potential (>0.8 V vs NHE), has been identified as promising catholytes for AORFBs. However, reported TEMPO based molecules are either permeable through ion exchange membranes or not chemically stable enough for long-term energy storage. Herein, a new TEMPO derivative functionalized with a dual-ammonium dicationic group, N 1 , N 1 , N 1 , N 3 , N 3 , 2, 2, 6, 6-nonamethyl-N 3 -(piperidinyloxy)propane-1,3-bis(ammonium) dichloride (N 2 -TEMPO) as a stable, low permeable catholyte for AORFBs is reported. Ultraviolet–visible (UV–vis) and proton nuclear magnetic resonance ( 1 H-NMR) spectroscopic studies reveal its exceptional stability and ultra-low permeability (1.49 × 10 -12 cm 2 s -1 ). Coupled with 1,1'-bis[3-(trimethylammonio)propyl]-4,4'-bipyridinium tetrachloride ((NPr) 2 V) as an anolyte, a 1.35 V N2-TEMPO/(NPr)2V AORFB with 0.5 m electrolytes (9.05 Wh L -1 ) delivers a high power density of 114 mW cm -2 and 100% capacity retention for 400 cycles at 60 mA cm-2. At 1.0 m electrolyte concentrations, the N 2 -TEMPO/(NPr) 2 V AORFB achieves an energy density of 18.1 Wh L -1 and capacity retention of 90% for 400 cycles at 60 mA cm -2 .

TEMPO↗
DOE OSTI2025

Modulating Solvation Structure in Concentrated Aqueous Organic Redox Flow Battery Electrolyte for Solubility and Transport Enhancement via Polycomplex Ion

Aqueous organic redox flow batteries hold great promise as a technology for creating economical grid energy storage using sustainable materials. Nonetheless, the solubility limit presents a universal barrier for all redox-active organic molecules. In this paper, a new approach is proposed to surpass the solubility limit by manipulating the solvation structure with polycomplex ion additives (PIA). Using poly(3,4-ethylenedioxythiophene) polystyrenesulfonate colloids as one example, its role in dismantling the rigid supramolecular clusters within the highly concentrated 7,8-dihydroxyphenazine-2-sulfonic acid electrolyte is investigated. 1 H and 23 Na NMR spectra and molecular dynamics simulation studies demonstrate that the bipolar structure of the PIA effectively disrupts the aggregations of DHPS and Na + ion in the highly concentrated anolyte, thus rendering a more flexible solvation structure and less restrictive ion transport, leading to substantially improved battery performance of an AORFB cell. The anolyte with PIA achieved 1.6 M and 74.3 Ah L –1 anolyte energy capacity.

25 ENERGY STORAGE↗
DOE OSTI2021

Reversible Ketone Hydrogenation and Dehydrogenation for Aqueous Organic Redox Flow Batteries

Compared to traditional transition metal ion-based counterparts, the realization of organics in aqueous redox flow batteries offers an environmentally benign, tunable, and safe route to large-scale energy storage systems. But development so far has been limited to a small palette of organics that are aqueous soluble and tend to display the necessary redox reversibility within the water stability window. Here we show how molecular engineering of fluorenone enables the alcohol electro-oxidation needed for reversible ketone hydrogenation and dehydrogenation at room temperature without the use of a catalyst. Flow batteries based on these new fluorenone derivative anolytes operate efficiently and exhibit stable long-term cycling at ambient and mildly elevated temperatures in air. These results not only expand the palette to include reversible ketone/alcohol conversion but also suggest the potential for identifying other atypical organic redox couple candidates.

Ketone, Fluorenone, Hydrogenation / Dehydrogenatio↗
DOE OSTI2024

Evaluating large scale aqueous organic redox flow battery performance with a hybrid numerical and machine learning framework

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low-capacity degradation in 10 cm$^2$ cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier to commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm$^2$ DHP-based AORFB by combining a physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. Such combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗
DOE OSTI2021

Symmetry-Breaking Design of an Organic Iron Complex Catholyte for a Long Cyclability Aqueous Organic Redox Flow Battery

The limited availability of a high-performance catholyte has hindered development of aqueous organic redox flow batteries (AORFB) that are environmentally benign, have tunable structures, and are safer than their traditional transition metal ion-based counterparts for large-scale energy storage. In this paper, a symmetry-breaking design of iron complexes with 2,2’-bipyridine-4,4’-dicarboxylic (Dcbpy) acid and cyanide ligands is described. By introducing two ligands to the metal center, the complex compounds (M4[FeII(Dcbpy)2(CN)2], M = Na, K) exhibited 4.2 times higher solubility (1.22 M, 33 Ah/L) and a 50% increase in potential compared with the widely used ferrocyanide. The symmetry-breaking, iron complex catholyte-based AORFBs were demonstrated at a concentration near the solubility limit (1.02 M Na4[FeII(Dcbpy)2(CN)2]) with a 1:1 catholyte:anolyte electron ratio. The AORFBs achieved a cell voltage of 1.2 V and a demonstrated energy density of 12.5 Wh/L. This symmetry-breaking design paves the way for development of metal complexes for high-energy-density AORFBs.

Li, Xiang↗
DOE OSTI2021

Electrochemical implications of modulating the solvation shell around redox active organic species in aqueous organic redox flow batteries

Significance The development of cost-effective batteries for long-duration grid scale energy storage will be accelerated using frameworks to rapidly screen and select battery components. Herein, we show that the solvent reorganization energy calculated from the Born equation (with reference to an electrolyte’s composition) is predictive of the electrolytes’ device level performance. This descriptor was found to correlate with key transport and kinetic properties over a range of electrolyte compositions and pH values, succinctly capturing the multicomponent interactions between the electrolyte salts and solvent. This enables the initial high-throughput screening of electrolyte candidates with minimal experimentation. Applied to aqueous redox flow batteries employing organic redox active species, we predict high-performance electrolyte compositions, enabling significantly enhanced device performance.

Sharma, Kritika↗
DOE OSTI2025

Computationally efficient models for aqueous organic redox flow batteries

The rising usage of intermittent energy has garnered the need for large scale energy storage systems. Redox flow batteries (RFB) based energy storage system shows promising potential. Numerical simulations and machine learning approaches have been widely used to study RFB performance. The development of autonomous material discovery framework and digital twin of energy storage system usually needs to query cell performance through fast response models. In this study, two computationally efficient models are introduced: a physics-based analytical flow battery model (EZBattery), and a machine learning operator model (Deep Operator Network, denoted by DeepONet). Both models can provide cell performance near instantly, and prediction accuracy was systematically examined on an application of evaluating the performances of a 780 cm 2 aqueous organic redox flow battery (AORFB), using potential anolyte candidates in dihydroxyphenazine (DHP)-based family of organic materials. A validated computationally expansive 3-dimensional multi-physics finite element model by COMSOL was used as the ground truth and provided the training data set for the DeepONet. 1280 samples were generated with 10 properties to mimic the different possible anolyte candidates, and the cell performances were evaluated under 10 different combined operating conditions. The accuracy comparisons for the two computationally efficient models show that both models can provide comparable accuracy in predicting cell charging/discharging voltage curves. DeepONet can provide slightly higher overall accuracy than EZBattery with faster calculation speed, but highly relies on the training dataset. EZBattery does not need a training dataset and can provide interpretable physics-based explanations of the results, while being more flexible to adjust to adapt any different cell designs, flow battery architectures, and electrolyte materials.

Analytical model↗
DOE OSTI2023

High-Throughput Electrochemical Characterization of Aqueous Organic Redox Flow Battery Active Material

The development of redox-active organics for flow batteries providing long discharge duration energy storage requires an accurate understanding of molecular lifetimes. Herein we report the development of a high-throughput setup for the cycling of redox flow batteries. Using common negolyte redox-active aqueous organics, we benchmark capacity fade rates and compare variations in measured cycling behavior of nominally identical volumetrically unbalanced compositionally symmetric cells. We propose figures of merit for consideration when cycling sets of identical cells, and compare three common electrochemical cycling protocols typically used in battery cycling: constant current, constant current followed by constant voltage, and constant voltage. Redox-active organics exhibiting either high or low capacity fade rates are employed in the cell cycling protocol comparison, with results analyzed from over 50 flow cells.

Electrochemistry↗
DOE OSTI2022

SOMAS: a platform for data-driven material discovery in redox flow battery development

Abstract Aqueous organic redox flow batteries offer an environmentally benign, tunable, and safe route to large-scale energy storage. The energy density is one of the key performance parameters of organic redox flow batteries, which critically depends on the solubility of the redox-active molecule in water. Prediction of aqueous solubility remains a challenge in chemistry. Recently, machine learning models have been developed for molecular properties prediction in chemistry and material science. The fidelity of a machine learning model critically depends on the diversity, accuracy, and abundancy of the training datasets. We build a comprehensive open access organic molecular database “Solubility of Organic Molecules in Aqueous Solution” (SOMAS) containing about 12,000 molecules that covers wider chemical and solubility regimes suitable for aqueous organic redox flow battery development efforts. In addition to experimental solubility, we also provide eight distinctive quantum descriptors including optimized geometry derived from high-throughput density functional theory calculations along with six molecular descriptors for each molecule. SOMAS builds a critical foundation for future efforts in artificial intelligence-based solubility prediction models.

25 ENERGY STORAGE↗
DOE OSTI2022

Highly Stable, Low Redox Potential Quinone for Aqueous Flow Batteries**

Abstract Aqueous organic redox flow batteries are promising candidates for large‐scale energy storage. However, the design of stable and inexpensive electrolytes is challenging. Here, we report a highly stable, low redox potential, and potentially inexpensive negolyte species, sodium 3,3′,3′′,3′′′‐((9,10‐anthraquinone‐2,6‐diyl)bis(azanetriyl))tetrakis(propane‐1‐sulfonate) (2,6‐N‐TSAQ), which is synthesized in a single step from inexpensive precursors. Pairing 2,6‐N‐TSAQ with potassium ferrocyanide at pH=14 yielded a battery with the highest open‐circuit voltage, 1.14 V, of any anthraquinone‐based cell with a capacity fade rate <10 %/yr. When 2,6‐N‐TSAQ was cycled at neutral pH, it exhibited two orders of magnitude higher capacity fade rate. The great difference in anthraquinone cycling stability at different pH is interpreted in terms of the thermodynamics of the anthrone formation reaction. This work shows the great potential of organic synthetic chemistry for the development of viable flow battery electrolytes and demonstrates the remarkable performance improvements achievable with an understanding of decomposition mechanisms.

Wu, Min↗
DOE OSTI2021

Bipolar Redox‐Active Molecules in Non‐Aqueous Organic Redox Flow Batteries: Status and Challenges

Abstract In this Review, recent advances in the development of organic bipolar redox‐active molecules (BRMs) for redox‐flow batteries (RFBs) are discussed, with special emphasis on their utilization in non‐aqueous systems. BRMs are single molecules that can be used as both anolyte and catholyte. Their unique redox chemistry enables identical components to be present in RFBs, which has distinct advantages in storage, mitigating crossover and compound degradation. Recent scientific innovations have uncovered three main strategies in preparing these bipolar species: developing stable radicals that are capable of both positive and negative redox reactions, covalently bridging electron donor‐acceptor motifs on one single molecule, and forming biredox eutectic mixtures through physically mixing active components. These approaches not only enabled symmetric flow battery design, but also resulted in electroactive materials with improved properties such as solubility, stability, and cell voltage. Nevertheless, much is still to be done. Importantly, developing BRMs that are competitive with vanadium RFBs in all performance indicators (e. g. solubility >1.0 M, voltage output >2.0 V, and cycling longevity >10 000 cycles) remains a challenge. Mechanistic studies including molecular dynamics, plausible degradation processes, and electrode/solution interface are necessary to peer into key parameters that dominate their battery performance. Accordingly, we review the current status and suggest future opportunities in these areas.

Li, Min↗