Chibueze Amanchukwu (UChicago): AI+ Science Schmidt Fellows Speaker Series

Organized by the University of Chicago’s Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship Program.

Agenda
4:00pm – 4:45pm:  Presentation
4:45pm – 5:00pm:  Q&A
5:00pm – 5:30pm: Reception

Meeting location
William Eckhardt Research Center. Room 401
5640 S Ellis Avenue, Chicago, IL 60637
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Abstract: Rechargeable batteries are pivotal in addressing many of society’s decarbonization goals. Unfortunately, developing new rechargeable battery chemistries can take decades. A big reason why is the infinite chemical space one must traverse to find a battery material that works. In this talk, I will focus on a battery material called the electrolyte. The electrolyte consists of salts dissolved in solvents (at different concentrations, in different mixtures); hence the chemical space is practically infinite. We have pursued a data-driven approach for electrolyte discovery. I will give three vignettes about (1) our development of forward design models that can map electrolyte composition to a property prediction. We show highly accurate models for the prediction of three important electrolyte properties (ionic conductivity, oxidative stability, and Coulombic efficiency. (2) development of active learning models paired with experimental feedback to smartly navigate the chemical space and increase the diversity of high performing electrolytes. Finally, (3) our newest work on generative models to map electrolyte properties to electrolyte composition.

Bio: Chibueze Amanchukwu is a Neubauer Family Assistant Professor in the Pritzker School of Molecular Engineering at the University of Chicago and holds a joint appointment at Argonne National Laboratory. His research is focused on enabling long duration electrical (batteries) and chemical energy storage for a sustainable energy future. His team is especially interested in modifying electrolyte and ion solvation behavior to control electrochemical processes occurring in batteries and electrocatalytic transformations such as carbon dioxide capture and conversion. They couple data science, computation, synthesis, and characterization to holistically understand ion transport in electrolytes and control interfacial reactions for efficient and cheap long duration storage.

His work has been recognized with the NSF CAREER Award, DOE Early Career Award, ECS-Toyota Young Investigator Fellowship, CIFAR Azrieli Global Scholar Award, and the 3M Nontenured Faculty Award. He obtained his PhD in chemical engineering as a NDSEG Fellow at MIT and was a TomKat Center Postdoctoral Fellow at Stanford University.

Parking
Campus North Parking
5505 S Ellis Ave
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