Skip to main content

Investigating the Behavior of Redox-active Organic Molecules in Electrochemical Energy Storage through Experiment-Guided Computational Simulations

CP 114
Speaker(s) / Presenter(s):
Anton Perera

The long-anticipated implementation of using renewable sources such as solar and wind to meet the world’s energy demand is still limited by not having appropriate grid-level energy storage systems on a global scale. When considering grid-scale energy storage solutions, environmental concerns, and techno-economic viability play a crucial role in the practical implementation of such technology. To address this, redox-active organic molecules (ROMs) have been explored for many uses including serving as redox-active molecules in redox flow batteries (RFBs) and providing overcharge protection in lithium-ion batteries (LIBs). Nevertheless, in order to be a major player in electrochemical energy storage, further optimization of ROMs with respect to performance and stability is required. Achieving optimum performance and stability mandates a molecular-level understanding of the interactions between chemical compounds, solvent molecules, and any other supporting solutes in the medium. Hence we approached this research question in the context of redox-active organic molecules for non-aqueous redox-flow batteries (NARFBs) by narrowing down the chemical space to a few classes of molecules. Herein, we extensively studied it from multiple perspectives such as; (1) Examining the correlation of molecular structure of redox-active organic molecules (ROMs) to solubility at different states of charge using quantitative structure-property relationships (QSPR), (2) Investigating the effect of electrolytes (counter-anions) on the solubility of ROMs using molecular dynamics (MD) simulations interfacing with experiments and multiple linear regression, (3) Exploring the concentration dependence of electrolytes with MD to explain experimental behavior at very high concentrations and to identify optimum concentration ranges for NARFBs, and (4) Probing Bulk and Interfacial Interactions of ROMs in complex solutions under an applied potential using classical MD simulations. This multi-approach endeavor has informed us of the strengths and limitations of predictive modeling in non-trivial molecular systems with limited data and high variability and boundaries related to improving the solubility of ROMs using structural modifications. Thus, in our continued efforts, we discovered that the solubility of these ROMs can be dramatically improved up to three-fold by switching the counter-anion due to the flexibility and size of the counter-anions. Our exploration of high-concentrated electrolytes implies that changes to supporting electrolyte concentration are significantly more impactful to the solution’s transport properties with the crowding of electrolytes leading to non-Newtonian fluid-like regimes. Expanding classical MD simulations to capture bulk and interfacial properties opens up a new paradigm of using computationally less-expensive methods for high-throughput simulations. To address the limitations we encountered in this effort, we also developed systems to automate similar MD simulations and analyses with the goal of producing large datasets that may pave the path to generating machine-learning models to predict different performance matrices efficiently in the future. In summary, the results and theoretical insights gained through these collective efforts would set the foundations for optimizing the performance and stability of ROMs thus helping experimentalists design better materials for electrochemical energy storage.