Hard Lessons from the Field
The data is in: the application of A.I. to battery development can significantly accelerate R&D, even in cases where the underlying processes are complex and the datasets are small. But what differentiates a successful application of battery informatics from an unsuccessful one?
A lot of things, according to Aionics CEO Dr. Austin Sendek, who has overseen dozens of modeling projects in his role as Aionics CEO and as a researcher at Stanford University.
Two key factors that predict whether a battery informatics effort will be successful are the types of models used and how much is already known about the underlying dataset.
Using a combination of published and never-before-seen research to illustrate these points, Dr. Sendek will share best practices he’s observed from his work in making sure data-driven modeling is as productive as possible.
In Aionics Fortnightly Episode 8, Dr. Sendek hosted Aionics Chief Scientist Prof. Venkat Viswanathan as he detailed his learnings as a battery informatics researcher and the path that led him to Aionics — and in Episode 11, the two swap roles as Prof. Viswanathan hosts Dr. Sendek to get his perspective on the field.
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Austin Sendek - CEO of Aionics, Inc
Austin Sendek is the Founder and CEO of Aionics, Inc. and a visiting scholar in the Department of Materials Science & Engineering at Stanford University. He was named to Forbes 30 Under 30 in Energy in 2019 and holds a Ph.D. in Applied Physics from Stanford University.