Organic redox flow batteries (ORFBs) are promising for grid-scale energy storage applications, but they have a large and complex research space that would be benefited by AI-guided, automated and high throughput electrochemical characterization to optimize objectives like voltage, capacity, and cycle life. We have developed an automated electrochemistry platform called FLOW-AIDE (Flexible Laboratory for Optimizing Wide-ranging Autonomous Investigations and Discoveries in Electrochemistry) that automates electrolyte delivery into a flow cell using a series of peristaltic pump channels and selector valves. There is one universal software that controls both the electrolyte delivery system and electrochemical testing, and an ultraviolet-visible (UV-Vis) spectrometer has recently been installed on FLOW-AIDE to enable in situ characterization. In situ characterization of the ORFB electrolyte (redox active material, solvent, and supporting salt) is necessary to diagnose battery metrics like state of charge and state of health. In this project, we aim to use UV-Vis spectrometry to characterize crossover rates and state of charge during cycling of the redox active materials as a function of battery parameters like ion exchange membrane, cycling rate, and active material concentration. This work will support the overall goal of accelerating ORFB research and development by providing insight into the behavior of ORFB redox active materials under cycling conditions.
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Job Type
Full-time
Career Level
Intern
Education Level
No Education Listed