Redox-flow batteries are an emerging energy storage technology that can pair with intermittent renewable energy technologies. There remains a need, however, to understand physicochemical relationships among the solvent, electrolyte salt, and redox-active molecules that comprise catholyte and anolyte solutions. To examine this relationship, we detail a systematic study wherein the concentrations of the redox-active molecule 2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPO) and TBAPF 6 electrolyte salts are varied over concentrations of 1 mM to over 1000 mM in acetonitrile. Three series were investigated:(1) varying the concentration of TEMPO while holding the concentration of TBAPF 6 constant, (2) varying the concentration of TBAPF 6 while holding the concentration of TEMPO constant, and (3) varying both the concentration of TEMPO and TBAPF 6 with a 5:1 TBAPF 6 :TEMPO ratio. Cyclic voltammetry data from macro-and microelectrodes were used to quantify diffusion coefficients and heterogeneous electron transfer rates, and these metrics were connected to the conductivity and viscosity to develop clear trends over the entire concentration range. Fundamental chemical interactions that lead to changes in physical properties were implicated via vibrational spectroscopy and molecular dynamics (MD) simulations. Trends in conductivity and viscosity for systems were inversely related and correlated to trends in diffusion coefficients and heterogeneous electron transfer rates. Intuitively, faster diffusion and electron-transfer rates occurred with lower TEMPO concentrations and higher TBAPF 6 concentrations, with the majority of conditions falling in the general proximity of literature values (k 0 = 0.1−0.5 cm/s, D ≈ (2.0−4.0) × 10 −5 cm 2 /s). At the highest TBAPF 6 concentrations, vibrational spectroscopy and MD simulations show that intermolecular interactions were more nuanced, and solvation and ion-pairing effects begin to influence electrochemical and physical properties. This functional approach including electrochemical and physical characterization paired with MD simulations provides a template for methodically studying systems for redox flow battery applications.

The development of redox-active molecules (ROM) with large solubilities in all states of charge in organic electrolytes is imperative to the continued development of non-aqueous redox flow batteries. The capability...

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Due to their property of decoupled power and capacity, non-aqueous redox flow batteries (NAqRFBs) provide an alternate solution to address the increase needed in grid storage. Phenothiazine (PT) class of derivatives possess desired properties such as high potential and chemical stability for redox-active catholyte materials for NAqRFBs. Nevertheless, most of the currently studied redox-active organic materials (ROMs), including certain phenothiazines suffer from low solubility specifically in their charged states and how the solubility trends change in charged states remains a mystery. Improving the solubility of ROMs without sacrificing stability or the redox potential requires a molecular-level understanding of how solubility changes in ROMs in general or for a specific class of materials. In fact, procurement of a universal understanding and ability to predict molecular solubility would serve the scientific community in well as solubility plays such an important role in almost every sub-discipline in chemistry, physics, engineering and, medicine. Quantitative structure-property relationships (QSPR) are known to be highly efficient due to their simplicity and ease of use. QSPR are mathematical relationships that link chemical structure and a chemical property (i.e. solubility) in a quantitative manner for a series of compounds. Hence, we used an approach of combining experiments and computational simulations with the aid of QSPR with the two major objectives of (1) Numerically predicting solubility of PTs at different states of charge and solution environments and (2) Understanding solubility trends and their physiochemical basis. These predictive models were constructed utilizing numerous experimental and computed molecular descriptors. A database of experimental, electronic structure, geometrical, topological descriptors containing around 1900 descriptors for neutral and radical cation forms of PT derivatives was constructed and the best descriptors were selected using various data science methods. Herein, we were able to establish a computational workflow that is robust and efficient in the optimization of conformationally flexible PT derivatives followed by parameter extraction.The major focus in the QSPR study was on the radical cation systems since the solubility usually suffers when going from neutral to charged state which is undesirable when considering NAqRFBs. QSPR models that can capture the solubility trends and predict the solubility of the validation set of compounds were validated with different statistical validation techniques. The statistical models developed were able to predict the solubility of compounds and were comparable with the experiments. Interestingly, these models were able to predict the solubility of the radical cation form of the compound secBuPT in 0.5 M tetraethylammonium tetrafluoroborate-acetonitrile (TEA/BF4-ACN) and pure acetonitrile (ACN) within a 10% deviation from the experimental value before experimental testing. Moreover, the analysis of molecular descriptors that...