Collaborative Research: Redox Electrolyte Co-design for Enhanced Solubility and Stability (RECESS)

About This Grant

Batteries play a tremendous role in our society and economy. From portable electronics and sensors to hybrid and electric transportation to our nation’s electrical grid, batteries provide an important way to store energy across large differences in scale. However, there is continued need to build better, safer batteries so that they can store more energy, be charged and discharged more times, and be assembled with cheaper and more readily available components. Addressing these challenges starts with the materials inside of the battery. This project seeks to design new battery components that are made from earth abundant materials dissolved in water. These materials can be cheaper and safer than those found in conventional lithium-ion batteries, but they are not currently as powerful. Moreover, as these materials are made from mixtures of different chemicals at different concentrations, the space for design is tremendous. To aid in the search through this complex chemical space, this project will develop and deploy robotic experiments and machine learning models to rapidly vary component combinations, record their properties, and make predictions as to new systems to explore. Promising materials will be tested in batteries to evaluate how they perform. Through this project, researchers will be trained as new battery scientists who understand both the chemistry and engineering of emerging battery science, and they will learn how to develop and use artificial intelligence to expedite discovery. The results of this investigation will help guide efforts to enhance our nation’s energy economy and support energy security. Water-based battery chemistries offer abundant, non-toxic, and non-flammable solutions to energy storage challenges. The goal of this project is to design and analyze redox electrolytes with large concentrations of redox-active, earth-abundant, ligand-metal coordination complexes capable of storing multiple electron equivalents in the metal and surrounding ligand framework. The overarching hypothesis is that a framework for the co-design of redox electrolytes can be derived from systematic and concerted molecular synthesis and experimental characterization coupled with autonomous materials formulation, electrochemical characterization experiments, and development of aligned machine learning (ML) models. Solubility and stability will be regulated by the chemistry imbued to the metal complexes by sulfonation of the redox-active ligands and through judicious formulation of the aqueous electrolyte. Coupled with the human-centered electrolyte formulation and electrochemical characterization, autonomous formulation and electrochemical experiments and high-throughput computations will be implemented to expand the redox electrolyte chemical space being explored. A publicly accessible data infrastructure will be developed and released, and the data will be used to develop ML models to identify and optimize co-design principles for redox electrolytes. This project will also train professional scientists in a multidisciplinary project combining experimentation, computation, automation, data infrastructures, and artificial intelligence (AI), guiding our nation’s energy economy and supporting energy security. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.