Developing a Predictive Solubility Model for Monomeric and Oligomeric Cyclopropenium-Based Flow Battery Catholytes

Abstract

The implementation of redox active organics in nonaqueous redox flow batteries requires the design of molecules that exhibit high solubility (>1 M) in all battery-relevant redox states. Methods for forecasting nonaqueous solubility would be valuable for streamlining the identification of promising structures. Herein we report the development of a workflow to parametrize and predict the solubility of conformationally flexible tris-(dialkylamino)cyclopropenium (CP) radical dications. A statistical model is developed through training on monomer species. Ultimately, this model is used to predict new monomeric and dimeric CP derivatives with solubilities of >1 M in acetonitrile in all oxidation states. The most soluble CP monomer exhibits high stability to electrochemical cycling at 1 M in acetonitrile without a supporting electrolyte in a symmetrical flow cell.

Dual function organic active materials for nonaqueous redox flow batteries

“…42 Further, Robinson et al demonstrated feasibility of doing supporting-salt-free symmetric nonaqueous RFB cycling utilizing an ionic cyclopropenium derivative. 43 However, an all organic full flow cell cycling in a supporting-saltfree environment has not yet been reported. 56 In a common ion-exchange system, both redox-active species (posolyte and negolyte) contained positively charged groups, and common counter ions migrate between positive and negative sides of the cell through an ion-exchange membrane to maintain the electroneutrality of the cell.…”

Molecular dynamics based descriptors for predicting supramolecular gelation

“…Although the size of this dataset is modest, previous studies in different elds have shown to deliver a promising predictive model with similar dataset sizes, by using models with a low complexity or by means of chemically relevant descriptors. 14,23,24…”

Quantitative Mapping of Molecular Substituents to Macroscopic Properties Enables Predictive Design of Oligoethyleneglycol-Based Lithium Electrolytes

“…In addition, the experimental conductivity and viscosity data do not show satisfactory trends with any one of the 4 DFT-calculated substituent parameters discussed above ( Figure S16 and S17), meta ( Figure S13b) and para ( Figure S14b) Hammett constants, or the dipole moments of each substituent ( Figure S15b). Thus, as has been observed in other contexts such as catalysis, 47,48 the experimental conductivity and viscosity data cannot be captured using a single substituent parameter.…”

“…46 Lastly, methods based on linear free energy relationships (LFERs) have been widely used to elucidate mechanisms of chemical reactions and catalytic transformations. 1,2,[47][48][49] For example, multi-dimensional regression analysis has been shown to provide insights into the complex thermodynamic and kinetic effects in determining reaction selectivity. 47 Nevertheless, such approaches require access to relevant descriptors (e.g., Hammett parameters or other calculated substituent parameters) that are unique to each substituent; such descriptors and methods have not, to our knowledge, been developed in the context of lithium electrolyte materials.…”