The proposed project aims at a closed-loop discovery of organic redox flow battery electrolytes. In this continuous workflow, properties of organic molecules are predicted using machine learning (ML) models and/or computed using quantum mechanical models, which allows leveraging the costs of the experiments. Then, the lead candidates are synthesized and characterized using automated systems. Finally, the results of characterization are used for adjusting the computational models. We focus on a specific class of organic molecules –diquats– that show high redox reversibility and good chemical stability. A virtual screening pipeline will be developed using proprietary software provided by Kebotix Canada.

Industry Partner(s):Kebotix Canada

Academic Institution:The University of Toronto

Academic Researcher: Aspuru-Guzik, Alan

Focus Areas: Advanced Manufacturing, Energy, Quantum

Platforms: Cloud, GPU, Parallel CPU