Recent Advances in the Development of Organic and Organometallic Redox Shuttles for Lithium-Ion Redox Flow Batteries

Designing Alkylammonium Cations for Enhanced Solubility of Anionic Active Materials in Redox Flow Batteries: The Role of Bulk and Chain Length

Advancing grid-scale energy storage technologies is crucial for realizing a fully renewable energy landscape, with non-aqueous redox flow batteries (NRFBs) presenting a promising solution. One of the current challenges in NRFBs stems from the low energy density of redox active materials, primarily due to their limited solubility in non-aqueous solvents. Herein, this study explores the solubility of vanadium(IV/V) bis-hydroxyiminodiacetate (VBH) crystals in acetonitrile, aiming to use them as anionic catholytes in NRFBs. We focused on enhancing VBH solubility by modifying the structure of the alkylammonium cation. Employing periodic density functional theory and a solvation model, we calculated the dissolution free energy( Δ G d i s * ${({\rm \Delta }{G}_{dis}^{^{\ast}}}$ ), which includes sublimation (Δ G s u b * ${{\rm \Delta }{G}_{sub}^{^{\ast}}}$ ) and solvation (Δ G s o l * ${{\rm \Delta }{G}_{sol}^{^{\ast}}}$ ) energies. Our results indicate that neither elongating straight-chain alkyl groups beyond a tetrabutylammonium baseline nor introducing bulky substituents at the nitrogen center significantly enhances solubility. However, the introduction of carbon spacers combined with terminal bulky substituents markedly improves solubility by favorably altering bothΔ G s u b * ${{\rm \Delta }{G}_{sub}^{^{\ast}}}$ andΔ G s o l * ${{\rm \Delta }{G}_{sol}^{^{\ast}}}$ . These findings underline the nuanced impact of cation structure on solubility and suggest a viable approach to optimize VBH-based anionic catholytes. This advancement promises to enhance NRFB efficiency and sustainability, marking a significant step forward in energy storage technology.

A novel 3D nitrogen-doped porous carbon supported Fe-Cu bimetallic nanoparticles composite derived from lignin: an efficient peroxymonosulfate activator for naphthalene degradation

A novel 3D nitrogen-doped porous carbon supported Fe-Cu bimetallic nanoparticles composite (Fe-Cu-N-PC) was prepared via direct pyrolysis by employing black liquor lignin as a main precursor, and it was utilized as a novel catalyst for PMS activation in degrading naphthalene. Under the optimum experimental conditions, the naphthalene degradation rate was up to 93.2% within 60 min in the Fe-Cu-N-PC/PMS system. The porous carbon framework of Fe-Cu-N-PC could facilitate the quick molecule diffusion of reactants towards the inner bimetallic nanoparticles and enriched naphthalene molecules from the solution by a specific adsorption, which increased the odds of contact between naphthalene and reactive oxygen species and improved the reaction efficiency. The quenching reaction proved that the non-free radical pathway dominated by 1O2 was the main way in naphthalene degradation, while the free radical pathway involving SO4·- and ·OH only played a secondary role. Moreover, owing to its high magnetization performance, Fe-Cu-N-PC could be magnetically recovered and maintained excellent naphthalene degradation rate after four degradation cycles. This research will offer a theoretical basis for the construction of facile, efficient, and green technologies to remediate persistent organic pollutants in the environment.

Impact of Pendent Ammonium Groups on Solubility and Cycling Charge Carrier Performance in Nonaqueous Redox Flow Batteries

The synthesis, characterization, electrochemical performance, and theoretical modeling of two base-metal charge carrier complexes incorporating a pendent quaternary ammonium group, [Ni(bppn-Me3)][BF4], 3', and [Fe(PyTRENMe)][OTf]3, 4', are described. Both complexes were produced in high yield and fully characterized using NMR, IR, and UV-vis spectroscopies as well as elemental analysis and single-crystal X-ray crystallography. The solubility of 3' in acetonitrile showed a 283% improvement over its neutral precursor, whereas the solubility of complex 4' was effectively unchanged. Cyclic voltammetry indicates an ∼0.1 V positive shift for all waves, with some changes in reversibility depending on the wave. Bulk electrochemical cycling demonstrates that both 3' and 4' can utilize the second more negative wave to a degree, whereas 4' ceases to have a reversible positive wave. Flow cell testing of 3' and 4' with Fc as the posolyte reveals little improvement to the cycling performance of 3' compared with its parent complex, whereas 4' exhibits reductions in capacity decay when cycling either negative wave. Postcycling CVs indicate that crossover is the likely source of capacity loss in complexes 3, 3', and 4' because there is little change in the CV trace. Density functional theory calculations indicate that the ammonium group lowers the HOMO energy in 3' and 4', which may impart stability to cycling negative waves while making positive waves less accessible. Overall, the incorporation of a positively charged species can improve solubility, stored electron density, and capacity decay depending on the complex, features critical to high energy density redox flow battery performance.

Density Functional Theory-Based Protocol to Calculate the Redox Potentials of First-row Transition Metal Complexes for Aqueous Redox Targeting Flow Batteries

Transition metal complexes are a promising class of redox mediators for targeting redox flow batteries due to the tunability of their electrochemical potentials. However, reliable time-efficient tools for the prediction of their reduction potentials are needed. In this work, we establish a suitable density functional theory protocol for their prediction using an initial experimental data set of aqueous iron complexes with bidentate ligands. The approach is then cross-validated using different complexes found in the redox-flow literature. We find that the solvation model affects the prediction accuracy more than the functional or basis set. The smallest errors are obtained using the COSMO-RS solvation model (mean average error (MAE)=0.24 V). With implicit solvation models, a general deviation from experimental results is observed. For a set of similar ligands, they can be corrected using simple linear regression (MAE=0.051 V for the initial set of iron complexes).

Computational design of quinone electrolytes for redox flow batteries using high-throughput machine learning and theoretical calculations

Molecular design of redox-active materials with higher solubility and greater redox potential windows is instrumental in enhancing the performance of redox flow batteries Here we propose a computational procedure for a systematic evaluation of organic redox-active species by combining machine learning, quantum-mechanical, and classical density functional theory calculations. 1,517 small quinone molecules were generated from the building blocks of benzoquinone, naphthoquinone, and anthraquinone with different substituent groups. The physics-based methods were used to predict HOMO-LUMO gaps and solvation free energies that account for the redox potential differences and aqueous solubility, respectively. The high-throughput calculations were augmented with the quantitative structure-property relationship analyses and machine learning/graph network modeling to evaluate the materials’ overall behavior. The computational procedure was able to reproduce high-performance cathode electrolyte materials consistent with experimental observations and identify new electrolytes for RFBs by screening 100,000 di-substituted quinone molecules, the largest library of redox-active quinone molecules ever investigated. The efficient computational platform may facilitate a better understanding of the structure-function relationship of quinone molecules and advance the design and application of all-organic active materials for RFBs.

Load Frequency Control of Microgrid System by Battery and Pumped-Hydro Energy Storage

Energy security is one of the main factors in the development and diffusion of microgrid applications. In networks operating without storage, the operation of their systems is greatly affected by sudden load demand and intermittent generation fluctuations. The main purposes of using energy storage systems in microgrids are stabilizing the intermittent generation of renewable energy sources locally, to ensure that energy production matches energy demands, participating in the frequency regulation process, maintaining the energy balance between generation and demand in renewable energy microgrids, and increasing energy reliability. This study investigates the frequency and power balance of an isolated microgrid system, by including storage systems (battery and pump-hydro). Realistic data for wind and solar sources are used for the optimal tuning of the proportional-integral controller, using the integral of the absolute error criterion multiplied by time, with a Quasi-Newton method. Simulation studies have been carried out, to investigate the performance of the microgrid system, by including the hydroelectric power plant system with pump storage for 24 h, under various operating conditions. The results reveal that by including the storage units in the system, it exhibits a more consistent and smooth dynamic performance, using renewable energy efficiently.

Redox Targeting of Energy Materials for Energy Storage and Conversion

The redox-targeting (RT) process or redox-mediated process, which provides great operation flexibility in circumventing the constraints intrinsically posed by the conventional electrochemical systems, is intriguing for various energy storage and conversion applications. Implementation of the RT reactions in redox-flow cells, which involves a close-loop electrochemical-chemical cycle between an electrolyte-borne redox mediator and an energy storage or conversion material, not only boosts the energy density of flow battery system, but also offers a versatile research platform applied to a wide variety of chemistries for different applications. Here, the recent progress of RT-based energy storage and conversion systems is summarized and great versatility of RT processes for various energy-related applications is demonstrated, particularly for large-scale energy storage, spatially decoupled water electrolysis, electrolytic N₂ reduction, thermal-to-electrical conversion, spent battery material recycling, and more. The working principle, materials aspects, and factors dictating the operation are highlighted to reveal the critical roles of RT reactions for each application. In addition, the challenges lying ahead for deployment are stated and recommendations for addressing these constraints are provided. It is anticipated that the RT concept of energy materials will provide important implications and eventually offer a credible solution for advanced large-scale energy storage and conversion.

A High-Energy Aqueous Manganese-Metal Hydride Hybrid Battery

Aqueous rechargeable batteries show great application prospects in large-scale energy storage because of their reliable safety and low cost. However, a key challenge in developing this battery system lies in its low energy density. Herein, a high-energy manganese-metal hydride (Mn-MH) hybrid battery is reported in which a Mn-based cathode operated by the Mn²⁺ /MnO₂ deposition-dissolution reactions, a hydrogen-storage alloy anode that absorbs and desorbs hydrogen in an alkaline solution, and a proton-exchange membrane separator are employed. Given the benefit derived from the high solubility and high specific capacity of the Lewis acidic MnCl₂ in the cathode and the low electrode potential of the MH anode, this aqueous Mn-MH hybrid battery exhibits impressive electrochemical properties with admirable discharge voltage plateaus up to 2.2 V, a competitive energy density of about 240 Wh kg^-1 (based on the total mass of the 5.5 m MnCl₂ solution and the hydrogen storage alloy electrode system), good cycling stability over 130 cycles, and a desirable rate capability. This work demonstrates a new strategy for achieving high-performance and low-cost aqueous rechargeable batteries.