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Updated: Aug 12, 2025
Using Cyclic Voltammetry, UV-Vis-NIR, and EPR Spectroelectrochemistry to Analyze Organic Compounds
Published on: October 18, 2018
Predicting the Solubility of Organic Energy Storage Materials Based on Functional Group Identity and Substitution
Madison R Tuttle1, Emma M Brackman1, Farshud Sorourifar2
1Department of Chemistry & Biochemistry, The Ohio State University, 100 West 18th Avenue, Columbus, Ohio43210, United States.
Abstract:
Organic electrode materials (OEMs) provide sustainable alternatives to conventional electrode materials based on transition metals. However, the application of OEMs in lithium-ion and redox flow batteries requires either low or high solubility. Currently, the identification of new OEM candidates relies on chemical intuition and trial-and-error experimental testing, which is costly and time intensive. Herein, we develop a simple empirical model that predicts the solubility of anthraquinones based on functional group identity and substitution pattern. Within this statistical scaffold, a training set of 18 anthraquinone derivatives allows us to predict the solubility of 808 quinones. Internal and external validations show that our model can predict the solubility of anthraquinones in battery electrolytes within log S ± 0.7, which is a much higher accuracy than existing solubility models. As a demonstration of the utility of our approach, we identified several new anthraquinones with low solubilities and successfully demonstrated their utility experimentally in Li-organic cells.
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