Aaron Hollas

The feasibility of using TEMPO catholyte in long-cycling aqueous redox flow batteries depends on the effective mitigation of the ring-opening side reactions.

Solubility is crucial for redox flow batteries as it affects their energy density. A data-driven approach based on AI/ML models can speed up the development of highly soluble redox active materials, but accurate solubility prediction remains elusive because of the lack of relevant databases. To overcome this deficiency, we developed a high-throughput experimentation process that combines a robotically controlled platform with high-throughput methodology to collect large-scale and high-quality solubility data. We demonstrate the potential utility and applicability of this high-throughput process by measuring the aqueous and non-aqueous solubilities of redox active materials and studying the effect of additives on their solubilities for both aqueous and non-aqueous redox flow battery applications. A redox flow battery based on our optimized negative electrolyte formulation and ferrocyanide positive electrolyte offers highly stable performance over 18 days (>100 cycles) with consistent capacity and a 24% boost in energy density.

The solvation free energy of organic molecules is a critical parameter in determining emergent properties such as solubility, liquid-phase equilibrium constants, pK_a and redox potentials in an organic redox flow battery. In this work, we present a machine learning (ML) model that can learn and predict the aqueous solvation free energy of an organic molecule using the Gaussian process regression method based on a new molecular graph kernel. To investigate the performance of the ML model for electrostatic interaction, the nonpolar interaction contribution of the solvent and the conformational entropy of the solute in the solvation free energy, three data sets with implicit or explicit water solvent models, and contribution of the conformational entropy of the solute are tested. We demonstrate that our ML model can predict the solvation free energy of molecules at chemical accuracy with a mean absolute error of less than 1 kcal mol⁻¹ for subsets of the QM9 dataset and the Freesolv database. To solve the general data scarcity problem for a graph-based ML model, we propose a dimension reduction algorithm based on the distance between molecular graphs, which can be used to examine the diversity of the molecular data set. It provides a promising way to build a minimum training set to improve prediction for certain test sets where the space of molecular structures is predetermined.

Tautomerization side reactions that limit cycling stability in hydroxy-substituted phenazines can be minimized by judicious location of the hydroxy groups on the phenazine, as demonstrated both computationally and experimentally.

Engineering suitable redox molecules: In a flow battery, catholyte and anolyte are stored in separate tanks, and pumps are used to circulate the fluids into a stack with electrodes separated by a thin membrane. Such batteries are ideal for large-scale grid storage applications; however, suitable redox molecules are currently limited. Feng et al. used “molecular engineering” to modify an inexpensive precursor (9-fluorenone) as the basis for an organic-based redox flow battery (see the Perspective by Hu and Liu). The authors tested a series of variant molecules in a redox flow battery in which the reactions involve reversible ketone hydrogenation and dehydrogenation in an aqueous electrolyte. These reactions have advantageous features, including two-electron redox and operation in air and at elevated temperatures (50°C), that are more suitable for real-world applications. Science , abd9795, this issue p. 836 ; see also abi5911, p. 788

Redox flow battery (RFB) offers great promise to provide transformational progress for large-scale energy storage technology. As the energy-bearing redox active species are dissolved and externally stored in liquid electrolytes, their physiochemical properties dictate the energy density, specific capacity, and cycle life thereby become a single most critical component of RFB. For instance, the concentration and chemical stability of redox active species within the electrolyte will determine the system-specific energy density and temperature window for the RFB operation, respectively¹. With the growing interest in developing sustainable RFB systems, there is a pressing task to identify the optimal electrolyte. This led to an active search for an ideal electrolyte which can hold a higher concentration of redox active species with wide chemical and thermal stability. Most electrolyte research has been focused on the empirical study of the effects of the pH, additives and solvent composition². Using combined spectroscopic and computational studies we established an electrolyte design formulation based on molecular solvate structure tuning^{3, 4}. This helps us to optimize the solubility and redox potential of redox molecule, exemplifying a generic electrolyte design strategy for RFB (see Figure 1). In this presentation, we will discuss the virtual screening and electrolyte design procedures for selecting functional moieties, additive salt and co-solvent to enhances the much-needed redox molecule solubility and stability. References M. Vijayakumar, W. Wang, Z. Nie, V. Sprenkle and J. Hu, Journal of Power Sources 241, 173-177 (2013). M. Vijayakumar, Z. Nie, E. Walter, J. Hu, J. Liu, V. Sprenkle and W. Wang, ChemPlusChem 80 (2), 428-437 (2015). K. S. Han, N. N. Rajput, M. Vijayakumar, X. L. Wei, W. Wang, J. Z. Hu, K. A. Persson and K. T. Mueller, J Phys Chem C 120 (49), 27834-27839 (2016). L. Li, S. Kim, W. Wang, M. Vijayakumar, Z. Nie, B. Chen, J. Zhang, G. Xia, J. Hu, G. Graff, J. Liu and Z. Yang, Advanced Energy Materials 1 (3), 394-400 (2011). Figure 1

Grid-scale battery storage devices have garnered increased attention for their ability to balance the intermittency of ever-expanding renewable energy deployment and to mediate periods of peak power demand. The redox flow battery has emerged as a viable alternative to traditional solid state batteries. With decoupled electrode and electrolyte storage vessels, the redox flow battery offers design flexibility where capacity and power may be independently tuned. The current state-of-the-art flow battery systems utilize vanadium-based electrolytes, however, the high cost of vanadium has hindered wide-scale deployment.¹ The use of organic molecules as electrolyte materials has emerged as a potentially lower cost alternative.^2,3 Presented will be our recent efforts in developing aqueous-soluble organic molecules as electrolyte materials for redox flow batteries. Structurally related molecules have undergone rational design to affect solubility and redox potential via the introduction of varying substituents on the parent molecule. Promising candidates have been incorporated into a full flow cell and undergone flow cell optimization. An exemplary candidate, when coupled with the benchmark ferri/ferrocyanide catholyte, delivers an OCV of 1.35 V at 50% SOC and achieves stable cycling over extended periods (Figure 1). References Zhang, M.; Moore, M.; Watson, J.S.; Zawodzinski, T.A.; Counce, R.M. J. Electrochem. Soc. 2012, 159, A1183. Park, M.; Ryu, J.; Wang, W.; Cho, J. Nat. Rev. Mater. 2016, 2, 16080. Soloveichik, G.L. Chem. Rev. 2015, 115, 11533. Figure 1